10. SCHOOL OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE

Mathematics, Statistics and Computer Science together constitute a school with wide scope for interaction aiming at excellence in fundamental research and applications.

The University of Madras is known for its nurturing the genius in Srinivasa Ramanujan, the great mathematical luminary whose mathematics is engaging the attention of leading mathematicians even today for its profoundness and applications. The University department of Mathematics was created in 1927. The Ramanujan Institute of Mathematics, founded by Dr.Rm.Alagappa Chettiar came into existence in 1957. In 1967, with the assistance from UGC it become a Centre of Advanced Study in Mathematics merging the two units. This centre is now known as the Ramanujan Institute for Advanced Study in Mathematics (RIASM). The RIASM offers Masters, M.Phil. and . programmes.

An independent Department of Statistics started functioning in 1941 and became a full fledged department of study and research from 1975 under the leadership of Prof.K.N.Venkataraman. The department offers Masters, M.Phil and Ph.D. Programmes. The department also offeres M.Sc. Actuarial Science programme under UGC Innovative programme.

Study of Computer Science in the University began in 1984. An independent department was instituted in 1995. The Department of Computer Science concentrates research in the areas of Parallel Algorithms, Architectures and Applications, Parallel Computing, Computational Geometry and it too has a well equipped Computer Laboratory. The department currently offers Master of Computer Applications and programmes.

Faculty

Dr. P.Thangavel, Ph.D. - Chairperson

RIAS in Mathematics

S. Parvathi, Ph.D. - Director and HeadK. Parthasarathy, Ph.D. - ProfessorPremalatha Kumaresan, Ph.D. - Professor M. Loganathan, Ph.D. - Professor V. Thangaraj, Ph.D. - Professor R. Sahadevan, Ph.D. - ProfessorG.Balasubramanian, Ph.D. - ProfessorG.P.Yuvaraj, Ph.D. - ReaderN.Agarwal Sushama, Ph.D. - Lecturer

Statistics

G.Gopal, Ph.D. - Professor and HeadP.Dhanavanthan, Ph.D. - Professor M.R.Srinivasan, Ph.D. - ProfessorT. Anbupalam, Ph.D. - Lecturer M.R. Sindhumol - LecturerK.M.Sakthivel - Lecturer (on contract)

Computer Science

P.Thangavel, Ph.D. - Professor and Head S.Gopinathan, M.Sc. - LecturerP.L. Chitra, M.C.A. - LecturerSornam, M.Sc., M.C.A. - LecturerB.Lavanya - Lecturer

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M.Sc. MATHEMATICS M.Sc Mathematics (CBCS) 2007 – 2009.

CreditCourse Code

Title of the Course C/E/S L T P C

Times New Roman

SEMESTER I

C001 Linear Algebra C 3 1 0 4 M.LoganathanC002 Real Analysis C 3 1 0 4 G.P.YouvarajC003 Ordinary Differential Equations C 3 1 0 4 R.SahadevanC004 Computational Mathematical Laboratory– I C 0 0 4 4 Guest Faculty

Elective E 2 1 0 3UOM S 001 Soft Skill* S 2

SEMESTER IIC005 Algebra C 3 1 0 4 S.ParvathiC006 Topology C 3 1 0 4 G.P.YouvarajC007 Partial Differential Equations C 3 1 0 4 Guest FacultyC008 Seminar C 3 1 0 4 Faculty Concerned

Elective E 2. 1 0 3UOM S 002 Soft Skill* S 2

SEMESTER IIIC009 Complex Analysis C 3 1 0 4 Guest FacultyC010 Measure & Integration theory C 3 1 0 4 Premalatha KumaresanC011 Probability theory C 3 1 0 4 V.ThangarajC012 Computational Mathematical Laboratory–II C 3 1 0 4 R.Sahadevan

Elective E 2 1 0 3Elective E 2 1 0 3

UOM S 003 Soft Skill* S 2UOM I 001 Internship** S 2

SEMESTER IVC013 Advanced Analysis C 3 1 0 4 K.ParthasarathyC014 Differential Geometry C 3 1 0 4 Premalatha KumaresanC015 Functional Analysis C 3 1 0 4 Sushama Agrawal

Elective E 2 1 0 3Elective E 2 1 0 3

UOM S 004 Soft Skill* S 2

Note: Compulsory Components for Postgraudate ProgrammesCore Courses - 60 Credits minimum Elective Courses - 18 Credits minimumSoft Skill Courses - 08 Credits minimumInternship - 02 CreditsTotal - 88 Credits minimum

Elective Courses Offered by the RIASM

Course Code

Title of the Course C/E/S/SS

Credits Faculty

L T P CMSI E001 Discrete Mathematics E 2 1 0 3 Guest FacultyMSI E002 Number Theory and

CryptographyE 2 1 0 3 Guest Faculty

2

MSI E003 Programming and Soft Computations E 1 1 1 3 Guest FacultyMSI E004 Computer Based Numerical Methods E 1 1 1 3 Guest FacultyMSI E005 Lie Algebras E 2 1 0 3 Guest FacultyMSI E006 Stochastic Processes E 2 1 0 3 V.ThangarajMSI E007 Representation Theory of Finite Groups E 2 1 0 3 S.Parvathi MSI E008 Graph Theory E 2 1 0 3 M.LoganathanMSI E009 Lie Groups of Transformations and

Ordinary Differential EquationsE 2 1 0 3 R.Sahadevan

MSI E010 Lie Groups of Transformations andPartial Differential Equations

E 2 1 0 3 R.Sahadevan

MSI E011 Potential Theory in Rn E 2 1 0 3 Premalatha KumaresanMSI E012 Linear Lie groups E 3 0 0 3 K.ParthasarathyMSI E013 Banach Algebras and Operator theory E 3 0 0 3 Agrawal Sushama N.MSI E014 Algebraic Number Theory E 2 1 0 3 S.ParvathiMSI E015 Mathematical Theory of Electromagnetic

Waves E 2 1 0 3 G.P.Youvaraj

Self-Study CoursesMSI S001 Algebraic Theory of Numbers SS 0 4 0 4 S.ParvathiMSI S002 Algebraic Topology SS 0 4 0 4 M.LoganathanMSI S003 Financial Calculus SS 0 4 0 4 V.ThangarajMSI S004 Fuzzy Analysis SS 0 4 0 4 N.Agrawal SushamaMSI S005 Harmonic Function Theory SS 0 4 0 4 Premalatha KumaresanMSI S006 Introduction to Fractals SS 0 4 0 4 K.ParthasarathyMSI S007 Lie Groups and Lie Algebras SS 0 4 0 4 K.ParthasarathyMSI S008 Probability on Abstract Spaces SS 0 4 0 4 V.ThangarajMSI S009 Quantum Computations SS 0 4 0 4 V.ThangarajMSI S010 Quantum Groups SS 0 4 0 4 S.Parvathi

P.G.DIPLOMA IN COMPUTATIONAL MATHEMATICS AND STATISTICS.

Paper Title of the course L T P CI SEMESTERMSI C076 Discrete Mathematics 3 1 - 4MSI C077 Mathematics of Finance and Insurance 4 1 - 5II SEMESTER MSI C078 Computational Mathematics 3 1 1 5MSI C079 Introduction to Information Technology + Computational

Laboratory – I 2 1 1 4

III SEMESTER MSI C080 Computational Statistics 3 1 1 5MSI C081 Computer Programming in C and C+++ Computational

Laboratory – II 2 1 1 4

IV SEMESTERMSI C082 Game Theory and Strategy 4 1 - 5MSI C083 Internet and Java Programming + Computational Laboratory –II 2 1 1 4

M.Phil DEGREE PROGRAMME (CBCS) 2006 – 2007

Course Title of the Course CoreCredits

Faculty

3

Code

L T P CMSI C001 Algebra C 4 1 0 5 M.Loganathan MSI C002 Analysis C 4 1 0 5 Agrawal Sushama MSI C003 Topology and

GeometryC 4 1 0 5 K.Parthasarathy

MSI C004 Dissertation andViva-voce

C 21 All Faculty Members.

Masters Courses - Abstract

MSI C001 Linear Algebra 3 1 0 4 M.Loganathan / Guest Faculty

Pre-requisite: Undergraduate Level Mathematics.

Course Objective:To lay the foundation for a variety of courses.

Unit I

Review of Vector spaces - Linear Transformations - Representation of Transformations by Matrices- Linear Functionals.- Algebra of Polynomials- Determinants – Properties of determinants- Characteristic Polynomials- Characteristic values – Characteristic vectors – minimal Polynomials.

Unit II

Invariant subspaces - Direct sum Decompositions - Diagonalization of linear operators – Primary Decomposition Theorem

Unit III

Cyclic Vectors – Cyclic subspaces – Cyclic Decomposition Theorem- Generalised Cayley- Hamilton Theorem- Rational form – Jordan Canonical form. Unit IV

Bilinear forms - positive - definite, symmetric and Hermitian forms – Sylvester’s theorem.

Unit V

Spectral representation of symmetric, Hermitian and normal operators - Applications. Books for Reference:

Kenneth Hoffman and Ray Kunze, Linear Algebra. Prentice Hall of India Private Ltd. New Delhi 2005.

Michel Artin, Algebra. Prentice Hall of India Private Ltd. New Delhi 1994.

MSI C002 Real Analysis 3 1 0 4 G.P.Youvaraj Pre-requisite: Undergraduate Level Mathematics.

Course Objective:

To provide a systematic development of Riemann – Sticltjes integral and the calculus on Rn

Unit I

4

Riemann – Stieltjes Integral: Definition and Properties of the Integral – Integration and Differentiation - Integration of vector valued functions

Unit II

Sequences and Series of functions : Pointwise Convergence – Uniform Convergence – Weierstrass Approximation Theorem.

Unit III

Special Functions: Power Series – Exponential and Logarithmic Functions – Trigonometric Functions – Fourier series – Gamma function.

Unit IV

Functions of Several Variables: Derivatives of a function from Rn to Rm – Chain Rule – Partial Derivatives – Derivatives of Higher order.

Unit V

Basic Theorems of Differential Calculus: Inverse function Theorem – Implicit function Theorem – Rank Theorem.

Books for Reference:

Text Book: Walter Rudin, Principles of Mathematical Analysis, Third Edition, McGraw Hill 1976.

MSI C003 Ordinary Differential Equations 3 1 0 4 R.SahadevanPre-requisite: Undergraduate Level Mathematics.

Course objective:

To learn mathematical methods to solve higher ordinary and partial differential equations and apply to dynamical problems of practical interest.

Unit I:

HIGHER ORDER LINEAR EQUATIONSGeneral Theory of nth order Linear Equations - Homogeneous equations with Constant Coefficients - The Method of Undetermined Coefficients - The Method of Variation of Parameters

Unit II :

POWER SERIES SOLUTIONS AND SPECIAL FUNCTIONSSeries Solutions of First Order Equations - Second Order Linear Equations – Ordinary Points - Regular singular Points - Gauss's Hyper-geometric Equation

Unit III :

SOME SPECIAL FUNCTIONS OF MATHEMATICAL PHYSICS AND EXISTENCE AND UNIQUENESS THEOREMLegedre Differential Equation: Solutions and its Properties - Bessel's Differential equations: Solutions and its Properties - The Method of Successive approximations -  Existence Uniqueness Theorem.

Unit IV :

NONLINEAR DIFFERENTIAL EQUATIONS AND STABILITYThe Phase plane- Linear systems – Autonomous systems and stability – Almost Linear systems- Competing species – Predator Prey equations – Liapunov method

MSI C004 Computational Mathematical Laboratory – I 0 0 2 2 Guest FacultyPre – requisite:

Calculus, Linear Algebra, basic knowledge of Differential Equations and some knowledge of Programming Language.

Course Objective:

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This is the first of two-semester Computational Mathematical Laboratory sequence (MSI 1008 to MSI 2008). In this sequence, we will emphasize the fundamentals of numerical computation and analysis: to explain how, why, and when numerical methods can be expected to work along with soft computational techniques using MAPLE/MATHEMATICA.

Section I : Mathematical Software : MAPLE/MATHEMATICA

Plotting Curves-Composition of functions, inverses-Sequences and series (finite and infinite sum)-Slope of a line, a secant, a tangent-Equations of tangents-Limit and continuity-2-D and 3-D graphs-Symbolic - Differentiation and Symbolic Integration- Conversion of coordinates, Areas in Polar coordinates- Symbolic manipulation on matrices - Solution to equations - Solution to Differential equations.

Section II : Programming Exercises using C++

1. Non-Linear Equations1.1 Bisection Method1.2 Regula-falsi Method1.3 Newton-Raphson Method1.4 Secant Method1.5 Fixed Point Iteration

2. System of linear Equations2.1 Gauss Elimination2.2 Gauss-Seidel Method

3. Interpolation3.1 Lagrange’s Interpolation Formula3.2 Newton Interpolation Formula

4. Numerical Differentiation4.1 Differentiation using limits4.2 Differentiation using Extrapolation

5. Numerical Integration5.1 Composite Tapezoidal Rule5.2 Composite Simpson’s 1/3 Rule

6. Numerical Solution to Differential Equations6.1 Euler’s Method6.2 Taylor’s Method of order 46.3 Runge-Kutta Method of order 46.4 Milne-Simpson Method

MSI C005 Algebra 3 1 0 4 S.ParvathiPre-requisite: Undergraduate Level Mathematics.Course Objective:

To lead the aspirant to modern aspects of Algebra.

Unit I

Review of Basic Group theory: Groups - homomorphisms, isomorphisms, - cosets, quotient groups .Symmetry: Group of motions of the plane - finite groups of motions - Solvable groups- nilpotent groups.

Unit II

Group actions- Counting formula - symmetric groups - Sylow theorems.

Unit III

Field theory – Algebraic and transcendental elements – degree of a field extension – adjunction of roots – algebraically closed fields - splitting fields.

Unit -IV

6

Normal extension – Galois Correspondence.

Unit V

Galois theory- Galois Fields - Applications of Galois theory – Classical groups.MSI C006 Topology 3 1 0 4 G.P.YouvarajPre-requisite: Undergraduate Level Mathematics and MSI C002.

Course objective:

Topology is a basic discipline of pure Mathematics. Its ideas and methods have transformed large parts of geometry and analysis. It has also greatly stimulated the growth of abstract algebra. Much of modern pure mathematics must remain a closed book to person who dose not acquire a working knowledge of at least the elements of Topology.

Unit I

Topological spaces - subspaces – product spaces – continuous functions - homeomorphisms .

Unit II

Connectedness - compactness

Unit III

Separation properties - Urysohn's lemma - Tietze's extension theorem .

Unit IV

Separable and second countable spaces – metrization theorems.

Unit V

Homotopy - fundamental group – induced homomorphisms - covering spaces - fundamental group of the circle.

MSI C007 Partial Differential Equations 3 1 0 4 Guest Faculty

Course objective:

To give an introduction to mathematical techniques in and analysis of partial differential equations.

FIRST ORDER EQUATIONS : Cauchy problem – Linear equations - Integral surfaces-Surfaces orthogonal to a given system – Compatible system – Charpits mathod – Special types of first order equations – Solutions satisfying given conditions – Jacobi’s method.

SECOND ORDER EQUATIONS – Linear equations with constant and variable coefficients – characteristic curves – The solution of hyperbolic equations – Separation of variables – The method of integral transforms. The Laplace equation – Elementary solutions – Families of equi-potential surfaces-Boundary value problems- Separation of Variables- wave equation – elementary solutions- Riemann,Volteera solution – Diffusion equation and its Solutions.

NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS WITH APPLICATIONS:Introduction- One dimensional nonlinear wave equation- Method of Characteristics-Linear and nonlinear dispersive wave- The Kortewerg de Vries equation and solitons.

MSI C008 Seminar 2 0 0 2 All Faculty Members

Objectives :

To develop written, oral and visual presentation skills To prepare students for Paper/Thesis/Dissertation writing practice in Mathematics

Course Outline :

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Each student is assigned a topic for term paper and seminar. It is an individual work. During the term, the student will meet periodically the faculty to discuss different stages of the term paper preparation and seminar.

Preparation of Term Paper : Choosing a Topic in consultation with the Student Advisor – Finding sources of materials – Gathering the relevant findings – Outlining the Paper – Writing the first draft (manuscript) – Converting into Compuscript (using Latex) and Editing the paper as advised by the Advisor.

Exposure to collect research papers and to prepare documentation of results in a scientific manner with proper citation principles will form integral part of the course.

Every student is expected to give at least 3 seminar talks during the course of study. Topics for seminars will be approved by the faculty. Preparation of seminar talks in the form of compuscripts (using mathematical software Latex) is compulsory and talks based on the Term paper be delivered using blackboard/ OHP/ LCD.

Evaluation is based on the (i) Preparation of the compuscript (30%) (ii) Presentation style (30%) (iii) Oral presentation (50%). Passing minimum 50% of (i), (ii) and (iii) put together.

Books for Reference :

1. English Expression :

1. Carey, G.V. Punctuation, Cambridge University Press.2. Partridge, E. Usage and Abusuge : A guide to good English, Middlesex, Penguin.

2. Research Writing :

1. Berry, R. : How to write a Research paper. Pergamon Press, London. 2. Cooper, B.C. : Writing Technical Reports, Middlesex , Penguin.3. Turabian, Kate L. : A manual for writers of term paper, Thesis and Dissertations,

University of Chicago Press.3. Mathematical Typesetting Software:

1. Leslie Lamport . LaTeX : A Documentation Preparation System User's Guide and Reference Manual , Addison Wesley, Mass, 1994.2. Goossens, Rahtz, and Mittelbach .The LaTeX Graphics Companion , Addison Wesley , Mass, 1997.3. George Gratzer . First Steps in LaTeX  Birhauser, 19994. George Gratzer . Math Into LaTeX  ,Birhauser, 2000.5. F. Mittelbach and M Goossens with Braams, Carlisle, and Rowley , The LaTeX Companion, second edition  , Addison Wesley. Mass, 2004

4. Mathematical Writing :

1. N.E.Steenrod, P.R.halmos, M.M.Schiffer and J.E.Dieudonne. How to write Mathematics, AMS Publication, 1973.2. Steven G.Krantz. A Primer of Mathematical Writing, AMS Publication, 19973. Ellen Swanson, Mathematics into Type, (updated Edition) AMS Publication, 1999.4. Steven G. Krantz. Mathematical Publishing, AMS Publication, 2005

MSI C009 Complex Analysis 3 1 0 4 Guest Faculty Pre-requisite: Undergraduate Level Complex Analysis .

Course Objective:

This course provides

(i) A modern treatment of classical Complex Analysis

Unit I

A quick review of basic Cauchy Theory: Cauchy’s Theorem and Cauchy’s integral formula for convex regions, Morera’s Theorem, power series representation of analytic functions, zeros of analytic functions, open mapping theorem, argument principle, Rouche’s theorem, maximum modulus theorem, Schwarz lemma, Weierstrass theorem on limits of analytic functions.

8

Unit II

Isolated singularities, Laurent series, Casorati-Weierstrass theorem, meromorphic functions, Mittag-Leffler’s theorem, Weierstrass product theorem, gamma function.

Unit III

Homology and homotopy versions of Cauchy’s theorem, simply connected regions, normal families, Riemann mapping theorem.

Unit IV

Harmonic functions, mean value property, Poisson integral, Dirichlet problem for the disc, Harnack’s inequality. Harnack’s principle.

Unit V

Riemann zeta function, functional equation, Euler product, elliptic functions, Weierstrass -function.

MSI C010 Measure and Integration Theory 3 1 0 4 Premalatha KumaresanPre-requisite: Undergraduate level Mathematics

Course Objective:

To develop the theory of integration via: measure, the knowledge of which is essential for working in most branches of modern Analysis.

Lebesgue outer measure, Measurable sets, Regularity, Measurable functions, Borel and Lebesgue Measurability.

Unit II

Integration of non- negative functions, the general integral. Integration of series, Riemann and Lebesgue integrals.

Unit III

Functions of bounded variation, Differentiation and Integration, Abstract measure spaces, Completion of a measure

Unit IV

Signed measures, Hahn, Jordan Decompositions, Radon Nikodym derivatives, Lebesgue Decomposition.

Unit V

Measurability in a product space, the product measure and Fubini’s theorem, Lebesgue measure in Euclidean space.

MSI C011 Probability Theory 3 1 0 4 V.ThangarajPre-requisite: Under Graduate level Calculus

Course objective:

This course provides- An axiomatic treatment of probability theory and an interplay between measure and probability- Different tools to solve mathematical problems.

Unit I

Unit I

9

Probability spaceAxiomatic definitions for probability space(finite, countably infinite and uncountably infinite outcome spaces)- Events – Fields of events- - fields of events – conditional probability and Bayes’ theorem

Unit II

Random Variables and their distributions Random Variables – distributions function – decomposition of distribution function – probability mass function and Probability density function – Classification of Random Variables – Moments and inequalities – Functions of Random Variables – Discrete and continuous distributions

Unit III

Independence, conditioning and ConvergenceIndependence of events – of - fields –of Random Variables- conditional expectation – Radon – Nikodym derivatives – convergence of Random Variables(in Prob., a.s., in dist., r-th mean)

Unit IV

Characteristic functions Definitions and Simple properties – Inversion theorem – Moments and Characteristic functions – Weak convergence

Unit V

Limit TheoremsZero –one Laws – WLLN and SLLN for iid and id random variables. CLT for iid and id random variables

MSI C012 Computational Mathematical Laboratory-II 0 0 2 2 R.Sahadevan

Description :Introduction to computer graphics and mathematical computer programming in MAPLE, as tools for the solution of mathematical problems and for mathematical experimentation. Programming topics will include data types, expressions, statements, control structures, procedures and recursion. Examples and practical work will include computing with integers, polynomials, matrices, data files and numerical approximations. Practical work will form an integral part of the course and assessment.

Course Objective:

Students will learn to apply Maple to more advanced computation than that introduced in Computational Mathematics I. The main themes of the course are these:

Mathematical problem solving. Visualising mathematical objectives via computer graphics and animation. Approximate numerical solution.

Computer programming. Data structures: numbers; sequences, sets and lists; tables and arrays; algebraic structures. Program structures: conditional execution, loops and iteration; operators, procedures and functions; mapping over a structure; recursion. Date types: type testing; implementing polymorphism.Mathematics-> Algorithms-> Programs. Selected applications, such as implementing vector and matrix algebra; elementary data processing.Topics to be covered from following the Course:

Linear Algebra, Real and Complex Analysis, Differential Geometry and Differential Equations

MSI C013 Advanced Analysis 3 1 0 4 K.Parthasarathy Pre-requisite: Undergraduate level Mathematics, MSI C002, C005 and MSI C008.

Course objective: Treatment of some advanced topics in Real, Complex and Fourier analysis.

Unit I

Differential forms, integration of forms, Stokes’ theorem classical vector analysis.

Unit II

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Ahlfors’ Schwarz lemma, Pick’s lemma, hyperbolic geometry in the unit disc, Schottky’s theorem, the Big Picard theorem.

Unit III

Analytic continuation, the monodromy theorem, Riemann surfaces, uniformization theorem and covering surfaces.

Unit IV

Fourier series: Dirichlet’s theorem, norm convergence, Fejer’s theorem, Riemann-Lebesgue lemma uniqueness theorem, completeness of exponentials in L2, Parseval formula, isoperimetric inequality, heat equation.

Unit V

Fourier transforms: Convolution, differentiation and Fourier transform, Schwartz space of rapidly decreasing functions, inversion and plancherel theorems. MSI C014 Differential Geometry 3 1 0 4 Premalatha Kumaresan Pre-requisite: MSI C001 and MSI C005

Course Objective:

To give a modern introduction to differential geometry of curves and surfaces.

Unit I

Plane curves, space curves, arc length, curvature, Frenet Serret Formula.

Unit II

Smooth surfaces: Examples of Smooth surfaces tangent, normal and orientability, first fundamental form,curves and surfaces, isometries.

Unit III

Curvature of smooth surfaces : Weingarten map and the second fundamental form, normal, principal, Gaussian and mean curvatures.

Unit IV

Surfaces of constant mean curvature, Gauss map, Geodesics.

Unit V

Gauss’s theorema of Egregium, Gauss equation – Codazzi-Mainardi Equations, isometries of surfaces,

MSI C015 Functional Analysis 3 1 0 4 Agrawal Sushama N. Pre-requisite: Knowledge of MSI C002 and C005.

Course objective:

Functional Analysis embodies the abstract approach to analysis. It highlights the interplay between algebraic structure and distance structures. It also provides a major link between Mathematics and its applications.

Fundamentals of normed spaces, Completeness, continuity of linear maps, Hahn Banach theorems and their applications.

Dual spaces, dual of lP, Lp , Uniform boundedness principle, closed graph and open mapping theorems

Inner product spaces, orthonormal sets - ,Riesz - Fischer theorems, Riesz Representation theorem.

Unit IUnit IIUnit III

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Bounded operators and adjoints, Projections, Projection theorem , Normal, Unitary and self-adjoint operators, spectrum of a bounded operator

Compact Operators, Spectral Theorem for Compact Selfadjoint Operators.

Syllabi for various Elective Courses MSI E001 Discrete Mathematics 2 1 0 3 Guest facultyPre-requisite: High school Level Mathematics:

Course Objective:

To introduce some basic mathematical concepts that are used in many computer science courses. To

develop skills to use these concepts in certain practical applications.

Unit I

Mathematical Logic: Connection – Normal Forms – Theory of Inferences –Predicate Calculus.

Unit II

Set Theory: Operations on Sets – Basic Set Identities – Relations and Orderings.

Unit III

Recursion: Functions – Recursive Functions – Partial Recursive Functions.

Unit IV

Graph Theory: Basic Concepts of Graph Theory- Paths – Connectedness – Matrix Representation of Graphs – Trees – List structures and Graphs

Unit V

Grammers and Languages: Free Semigroups – Grammers and Languages. MSI E002 Number Theory & Cryptography 2 1 0 3 Guest FacultyPre-requisite: Undergraduate Level Mathematics:

Course Objective:

To provide an introductory course in Number theory.To Introduce the fast growing and relevant topic of cryptography as an application of Number theory

Unit I

Elementary Number theoryDivisibility and the Euclidean Algorithm, Congruences, Finite fields and Quadratic residues, Cryposystems, Enciphering matrices, Public key Cryptography, RSA, Discrete Log, Knapsack, Primality and Factoring.

Unit II

Introduction to classical cryptosystemsSome simple crypto systems , en ciphering matrices, DES

Unit III

Finate fields and quadratic residuesFinate fields, quadratic residues and reciprocity.

Unit IV

Unit IV Unit V

12

Public Key CryptographyThe idea of a public key Cryptography, RSA, Discrete Log, Algorithms to find discrete logs in finite Fields: Shank’s giant – step - baby -step algorithm, Silver-Pohlig – Hellman’s algorithm, Diffie – Hellman key - exchange system, ElGamal, zero – knowledge protocols.

Unit V

Primality-Factoring and Elliptic curves.Pseudoprimes and strong Pseudoprimes, some methods to factor a composite integer:Pollard’s rho method, fermat factorization and factor bases, the quadratic Sieve method, elliptic curves-basic facts, elliptic curve cryptosystems

MSI E003 Programming and Soft Computations 2 1 0 3 Guest Faculty

Tokens, Expressions and Control Structures – Functions in C++

Classes and Objects – Constructors and Destructors

Operator Overloading and Type conversions - Inheritance

Pointers – Virtual Functions and Polymorphism – Templates and Exception handlingUnit V

Maple / Mathematica Commands (without programming)

MSI E004 Computer Based Numerical Methods 2 1 0 3 Guest Faculty

The solution of Nonlinear Equations f(x)=0Iteration for solving x=g(x) – Bracketing methods for locating a root – Initial approximations and convergence criteria – Newton-Raphson and secant methods- Aitken’s and Steffensen’s and Muller’s methods

The solution of Linear systems AX= B Upper triangular linear systems-Gaussian elimination and pivoting-Matrix inversion- Triangular factorization- Interpolation-Lagrange approximation – Newton polynomials

Unit III

Numerical Differentiation, Integration and optimizationApproximating a derivative – Numerical differentiation formulae – quadrature – Composite trapezoidal and Simpson’s rule – recursive rules – Romberg Integration – Minimisation of a function.

Solution of Differential EquationsDifferential Equations – Euler’s method – Heun method- Taylor series method – Runga-Kutta methods – Predictor-Corrector methods

Unit V

Solution to Partial differential methods Hyperbolic quations – Parabolic equations – Elliptic equations.

Contents and Treatment as in :John H.Mathews, Numerical Methods for Mathematics, Science and Engineering (2nd Edn.), Prentice Hall, New Delhi, 2000

Unit I Unit II Unit III Unit IV Unit I Unit II Unit IV

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MSI E005 Lie Algebras 2 1 0 3 Guest Faculty Pre-requisite: Knowledge of MSI C001 and C004

Course objective:

To initiate the study of Lie Algebras

Unit I

Basic Concepts of Lie Algebras

Unit II

Ideals and homomorphisms

Unit III

Solvable and nilpotent Lie algebras

Unit IV

Semisimple Lie algebras : Theorems of Lie and Cartan, Killing form

Unit V

Complete reducibility of representations and representation of sl(2,F).

MSI E006 Stochastic Processes 2 1 0 3 V.ThangarajPre-requisite: MSI C010

Course objective:

This course aims To introduce standard concepts and methods of stochastic modeling To analyze the variability that are inherent in natural, engineering and medical sciences To provide new prespective, methodology, models and intuition and aid in other mathematical

and statistical studies

Unit I

Markov chains, an introduction- Definitions, Transition probability matrix of a Markov chain, some Markov chain models, First Step Analysis, some special Markov chains, Functionals of Random Walks and Success runs

Unit II

Long run behaviour of Markov chains - Regular Markov chains - Transition probability matrices – Examples, Classification of states, Basic limit theorem of Markov chains, Reducible Markov chains

Unit III

Poisson Processes - Poisson distribution and Poisson Processes, Law of rare events, distributions associated with Poisson Processes, Uniform Distribution and Poisson Processes, Spatial Poisson Processes, Compound and Marked Poisson ProcessesUnit IV

Continuous time Markov chains - Pure birth processes – Pure Death processes, Limiting behaviour of birth and death Processes, birth and death Processes with absorbing states , Finite state Continuous time Markov chains, A Poisson Process with a Markov intensity

Unit V

Renewal phenomena – Definitions, examples, the Poisson Process viewed as a renewal process

MSI E007 Representation Theory of Finite Groups 2 1 0 3 S.ParvathiPre-requisite: MSI C001 and C004

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Course Objective:

To highlight the importance of combination of techniques used from group theory,ring theory and linear algebraTo motivate the students for further study

Classical groups: General linear group , Orthogonal group, Symplectic group, Unitary group.

Group representation, conjugate representation, G-invariant spaces - irreducible representations - Schur’s lemma

The Group Algebra - Maschke’s theorem - characters. Orthogonality relations for characters – Number of irreducible representations

Permutation representations - Regular representation. Representations of Symmetric groups

Representation of Finite abelian groups - Dihedral groups.

MSI E008 Graph Theory 2 1 0 3 M.LoganathanPre-requisite: Undergraduate Level Mathematics.

Unit I

Graphs – Vertex degrees - Sub-graphs - Paths and cycles - Connected graphs - Connected components

Unit II

A cyclic graphs – Trees - Cut edges - Cut vertices – Spanning Tree .

Unit III

Euler tours - Euler graphs - Hamiltonian paths - Hamiltonian graphs - Closure of a graph.

Unit IV

Planar graphs - Euler’s formula- Vertex colouring - Chromatic number - Chromatic polynomial – R - Critical graphs.

Unit V

Edge colouring - Edge Chromatic number - Dual of a plane graph -Map colouring - Four and five colour theorems.

MSI E009 Lie Groups of Transformations and Ordinary Differential Equations

2 1 0 3 R.Sahadevan

Pre-requisite: MSI C002 and C005

Course Objective:

To introduce for advanced research in mathematics and applications of Lie group.

Unit I

Introduction - Lie groups of transformations - infinitesimal transformations.

Unit II

Extended group transformations and infinitesimal transformations (one independent and one dependent variables).

Unit III

Unit I Unit IIUnit III

Unit IV Unit V

15

Lie Algebras and applications.

Unit IV

Invariance of first and second order ordinary differential equations.

MSI E010 Lie Groups of Transformations andPartial Differential Equations

2 1 0 3 R.Sahadevan

Pre-requisite: MSI E009

Unit I

Introduction - Lie groups of transformations - infinitesimal transformations.

Unit II

Extended group transformations and infinitesimal transformations.

Unit III

Invariance of a partial differential equations of first and second order - elementary examples.

Unit IV

Noether's theorem and Lie Backlund symmetries.

MSI E011 Potential Theory in Rn 2 1 0 3 Premalatha KumaresanPre-requisite: MSI C009

Harmonic functions - Dirichlet problem.

Functions harmonic on a ball - Directed families of harmonic functions.

Super harmonics functions – Equivalent definitions - Minimum principle.

Properties of Super harmonic functions

Directed families of super harmonic functions – Properties of surface and volume mean values.

MSI E012 Linear Lie Groups 3 0 0 3 K.Parthasarathy

Unit I

Linear Lie Groups: Definition and examples, the exponential map and the Lie algebra of a linear Lie groups.

Unit II

The Lie Correspondents, Homomorphisms. Unit III

Basic Representation Theory, irreducible representations of SU(2) and SO(3).

Unit IV

Characters, Orthogonality and Peter-Weyl Theorem.

Unit I Unit II Unit III Unit IV Unit V

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Unit V

Roots, Weights and Weyl’s Formulas. MSI E013 Banach Algebras and Operator Theory 3 0 0 3 Agrawal Sushama N.

Unit I

Banach Algebras definition, examples, ideals and quotients, invertibility and the Spectrum, Banach – Mazur theorem. Unit II

Spectral radius formula, Gelfand theory of commutative Banach Algebras.

Unit III

C* - Algebras, Selfadjoint, normal, unitary operators on a Hilbert space, Projectors. Unit IV

Gelfand – Naimark Theorem for commutative C* - algebras, continuous functional Calculus for normal operators, Positive Operators and Square root.

Unit V

Borel functional Calculus for normal operators, Spectral measures, Spectral Theorem for bounded normal operators.

MSI E014 Algebraic Number Theory 2 1 0 3 S.ParvathiPre-requisite: MSI C001 and C005

Course Objective:

To provide basic understanding of Algebraic Number Theory

Unit I

Algebraic Background – Symmetric Polynomials – Modules – Free Abelian Groups

Unit II

Algebraic Numbers – Conjugates and Discriminants – Algebraic integers – Integral Bases – Norms and Traces – Rings of Integers – Noetherian rings and Noetherian Modules.

Unit III

Quadratic fields and Cyclotomic fields – and integers in Quadratic fields and Cyclotomic fields

Unit IV

The group of units – The factorization into irreducible elements – examples of non-unique factorization into irreducibles – Euclidean Quadratic fields.

Unit V

Prime factorization of ideals - Dedekind rings- the norm of an ideal – class groups

MSI E015 Mathematical Theory of Electromagnetic Waves

2 1 0 3 G.P.Youvaraj

Pre – requisite: Vector Calculus, Real Analysis, Differential Equations.

Course Objective:

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This is aimed at introducing the mathematical theory behind electromagnetic wave propagation. While learning this theory we shall also understand acoustic wave propagation in bounded and unbounded regions. We shall also discuss the scattering aspect of both electromagnetic, and acoustic waves.

Course Contents:

1. Review of Vector Calculus1.1 Space Curves and Surfaces1.2 Gradient, Divergence, Curl 1.3 Green’s Theorem, 1.4 Gauss Divergence Theorem

2. Electromagnetic Fields2.1 Maxwell’s Equations2.2 Electromagnetic Waves2.3 Reduced Wave Equation

3. Solutions in Bounded Domain3.1 Fundamental Solutions of Reduced Wave equation3.2 Green’s Function3.3 Structure of Wave functions 3.4 Representation of Wave functions

4. Solutions in the Exterior Domain4.1 Structure of Wave functions 4.2 Sommerfeld’s Radiation Conditions4.3 Green’s Representation Theorem4.4 Far Field Patterns

5. Boundary Value Problems5.1 Boundary Value Problems in the bounded domain5.2 Boundary Value Problems in the Exterior domain5.3 Scattering and Inverse Scattering

Self-Study Courses for the Ramanujan Institute only

The detailed syllabi will be provided at the time of registration by the faculty concerned.

MSI S001 Algebraic Theory of Numbers SS 0 4 0 4 S.ParvathiMSI S002 Algebraic Topology SS 0 4 0 4 M.LoganathanMSI S003 Financial Calculus SS 0 4 0 4 V.ThangarajMSI S004 Fuzzy Analysis SS 0 4 0 4 N.Agrawal SushamaMSI S005 Harmonic Function Theory SS 0 4 0 4 Premalatha KumaresanMSI S007 Introduction to Fractals SS 0 4 0 4 K.ParthasarathyMSI S008 Lie Groups and Lie Algebras SS 0 4 0 4 K.ParthasarathyMSI S009 Probability on Abstract Spaces SS 0 4 0 4 V.ThangarajMSI S010 Quantum Computations SS 0 4 0 4 V.ThangarajMSI S011 Quantum Groups SS 0 4 0 4 S.Parvathi

P.G.DIPLOMA IN COMPUTATIONAL MATHEMATICS AND STATISTICS

SYLLABUS ABSTRACTSMSI C076 Discrete Mathematics 3 1 - 4

Objectives : To develop mathematical maturity and ability to deal with abstraction. To develop problem-solving skills in different aspects of application mathematics

Course Content:

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Unit-I :

Logic and the Language of Mathematics Propositions – Conditional propositions and Logical Equivalence – Quantifiers – Proofs – Mathematical Induction – Sets sequences and Strings – Number Systems – Relations – Equivalence Relations – Matrics of Relations – Functions.

Unit-II :

Counting Methods and the Recurrence Relations: Basic Principles Permutations and Combinations – Generalized Permutations and Combinations – Binomial Coefficients and Combinatorial Identities – The Pigeonhole Principle – Solving recurrence relations –Simple problems and applications

Unit-III :

Graph Theory: Paths and Cycles – Hamiltonian Cycles and the Traveling Salesman Problem – Representations of Graphs – Trees – Spanning trees – Minimal spanning trees – Binary trees – Tree Traversals.

Unit-IV :

Network models, Boolean algebras and Combinatorial circuits:Algorithms – A Maximal Flow Algorithms – The Max flow, Min cut Theorem – Matching – Combinatorial Circuits and heir properties – Boolean algebras – Boolean functions – Synthesis of circuits – Applications

Unit - V:

Automata, Grammars and LanguageSequential Circuits and Finite State Machines- Finite State Automata – Language and Grammars – Non-deterministic Finite State Automata – Relationships between Language and Automat

MSI C077 Mathematics of Finance and Insurance 4 1 - 5

Objectives :

To provide fundamentals in financial transactions, discounting, repayments, term structure, derivatives and stochastic interest rate models.

To gain practice to apply in Actuarial planning

Course Contents.

Unit-I :

Theory of Interest – The basic compound interest functions – Nominal rates of interest annuities payable p-thly – Discounted cash flow

Unit-II :

Capital redemption policies- The valuation of securities- Capital gains tax – cumulative sinking funds.

Unit-III :

Yield curves, discounted mean terms, matching and immunizationConsumer credit and Stochastic interest rates models

Unit-IV :

Morality table – Annuities, Assurances, Premiums – Functions other than yearly.

Unit-V :

Policy values – surrender and paid-up values: Bonus: Special policies – Applications of calculus : Population Theory

MSI C078 Computational Mathematics 3 1 1 5

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Objectives :

To develop computational problem-solving skills, ideas – To apply mathematical concepts other science and social science subjects.

Course Content:

Unit-I :

Graphs and Functions: Cartesian Coordinate Systems and Straight Lines – Linear and Quadratic Functions –Aids to Graphing Functions – Exponential and Logarithmic Functions – Analytical Geometry and the Conic Sections – Polar Coordinates – Area Computational in Polar Coordinates – Parametric Curves – Applications

Unit-II :

Systems of Linear Equations: Systems of Linear Equations in Two Variables – Systems of Linear Equations and Augmented Matrices – Gauss – Jordan Elimination – Matrices – Addition and Multiplication by a number – Matrix Multiplication – Inverse of a Square Matrix – Matrix Equations and Systems of Linear Equations – Leontief Input – Output Analysis. Unit-III :

Differential Calculus: Limits and Continuity – A Geometric Introduction – Computation of Limits – The Derivative of constants, Power Forms and Sums – Derivatives of Products and Quotients – Chain Rule: Power Form – Marginal Analysis in Business and Economics.

Unit – IV

Integral Calculus: Antiderivatives and Indefinite Integrals – Integration by Substitution – Differential Equations – Growth and Decay – Area under a curve – Definite Integrals – The Fundamental Theorem of Calculus – Applications in Business and Economics

Unit – V :

MAPLE Programming: Introduction to mathematical computer programming in MAPLE, as tools for the solution of mathematical problems and for the mathematical experimentation. Programming topics will include data types , expressions, statements, control structures, procedures and recursion. Example and practical work will include computing will integers, polynomials, matrices, data files and numerical approximations.

Computational Laboratory Exercises: MAPLE Exercises: Plotting Curves Compositions of functions, inverse Sequences and Series (finite and infinite sum) Slope of a line, a secant, a tangent Equations of tangent Limit and continuity 2-D and 3-D graphs Symbolic Differentiation and Symbolic Integration Conversion of coordinates. Areas in Polar coordinate Symbolic manipulation on matrices Solution to equation Solution to Differential equations.

MSI C079 Introduction to Information Technology + Computational Lab. – I 2 1 1 4

Objectives:

To provide basic understanding of information technology.

Course Content:

Unit – I :

Introduction to Computer – Classification of Digital Computer System – Computer Architecture – Number System- Memory unit – Input – Output Device.

Unit – II :

Logic Gates – Truth Table Introduction to Computer Software – Programming Languages.

Unit – III:

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Introduction to MS-WORD – Creating documents, Tables, Importing charts, Mails merge – Preparing bio-data –Copying Text and Pictures from Excel.

Unit – IV :

MS-ACCESS Creating Recruitment Databases and Create Application Table which has Applicant Name, Name Address, Phone Number, E-mail, etc – MS-ACCESS – Planning and Creating Tables and Using the features of Chart. Bar Chart, Pie.

Unit – V :

MS-EXCEL – Creating Tables Using EXCEL – Using Tables and Creating Graphs Usage of formulae and Built –in Functions – File Manipulations,.

POWER POINT – Inserting Clip Art and Pictures – Insertion of new slides – Presentation using Wizards – Usage of design Templates.

Computer Laboratory Exercises:

MS-WORD – To create Bio-Data – To create Bar Chart – To create Mail Merge – MS EXCEL1. Student Mark List

Bar Chart creation with Employee details – Pie-Chart – Company’s Growth from 1990- 2000-MS-POWER POIN-Birth day Greeting – Marriage Invitation –Demo in your specializations – MS-ACCESS-Employee Database Creation-Library Information System- Hospital Management System

MSI C080 Computational Statistics 3 1 1 5

Objective:

To provide a through grounding in classical-methods of statistical inference with an introduction to more new developments in statistical methodology. To provide students with the necessary technical skills and practical experience to enable them critically to evaluate research results and to carry out high quality empirical work for themselves. Emphasis throughout the course is on the application of statistical techniques rather than the development of theory.

UNIT- I :

Data and Statistics : Data – Data Sources - Descriptive Statistics: Tabular and Graphical Methods:- Summarizing the Qualitative Data and Quantitative Data – Exploratory Data Analysis (Stem and Leaf Display) – Cross tabulations and scatter diagrams Descriptive Statistics: Numerical methods :- Measures of location – measures of variability – Measures of relative location and detecting outliers – Exploratory Data Analysis – Measures of association between two variables – the weighted mean and working with grouped Data

UNIT-II :

Introduction to Probability – discrete probability distributions and Continuous distribution functions: Experiments – events – assigning probabilities – basic relationships of probability – conditional probability – Bayes theorem – Moments- binomial, Poisson and hyper-geometric distributions – uniform(continuous), normal. Exponential distributions.

UNIT-III :

Sampling and Sampling Distributions:- Sampling methods – Sampling distributions of sample mean and sample proportion – Point estimation and properties. - Tests of Goodness of Fit and Independence – Multinomial population, Poisson and Normal distributions – Test of independence.

UNIT-IV :

Analysis of Variance and Experimental Design:- Testing of the equality of k population means- – Completely randomized Design – Randomized Block design – Multiple comparison procedures -Factorial Experiments (22)

UNIT-V :

21

Simple linear and multiple Regressions :- The regression model – Least squares model – coefficient determination – Model assumptions – Testing of significance – using the estimated regression equation and prediction – Residual analysis - qualitative Independent variables in the case of multiple regression(binary response).

Computational Laboratory Exercises :EXCEL Exercises :

Tabular and Graphical Methods- Descriptive Statistics (mean, median, mode, variance and Standard deviation)-Discrete Probability Distributions (computing binomial and Poisson probabilities)-Continuous Probability distributions (Normal distribution)-Random Sampling -Interval Estimation of a Population mean (Large-Sample and Small-Sample cases)-Hypothesis Testing for mean (Large-Sample and Small-Sample cases)-Hypothesis Testing about the difference between two population means(Large-Sample, Small-Sample and Matched Sample)-Population variances (One population and two populations) -Tests of Goodness of fit and Independence -Analysis of Variance and Experimental Design ( Single-Factor Observational Studies and Completely randomized designs – Factorial Experiments(22))-Simple Linear Regression Analysis-Correlation Analysis

MSI C081 Computer Programming in C and C+++ Computational Laboratory – II

2 1 1 4

Objectives: To develop skill in writing codes in C and C++ programming languages

Course Content:

UNIT-I :

Identifiers – Keywords – Data Types – Access Modifiers – Data Type Conversions – Operators

UNIT-II :

Conditional Controls – Loop Control – Input/Output Operations – Function Prototypes – Function Arguments – Arrays – Structures – Unions – Pointers.

UNIT-III :

Introduction to OOPS – Overview of C++ - Classes – Structures

UNIT-IV :

Friend Functions – Constructors – Destructors – Arrays

UNIT-V :

Function Overloading, Operator Overloading – Inheritance – Polymorphism.

Computer Laboratory Exercises:

Programming Problems in C:Factorial of a number-Farenheit to Celicius-To count the no. of vowels and consonants in given string-Matrix manipulation-Palindrome checking-Fibonacci series

Programming Problems in C++:To calculate simple interest and compound interest using class and objects-Initialising and destructing the character array using constructor and destructor functions-Adding 2 complex numbers using operator overloading-To calculate volume of sphere , cube and rectangle using function overloading-Calculate the area of triangle and rectangle using single inheritance-To maintain student’s details using multiple inheritance

MSI C082 Game Theory and Strategy 4 1 - 5

Objectives:To provide mathematical game theory in an interdisciplinary context Course Content:

UNIT-I :

22

Two-person zero-sum games : The nature of game – matrix games: dominance and saddle points – matrix games: mixed strategies- Application to Anthropology: Jamaican Fishing- Application to Warfare: Guerrillas, Police, and Missiles - Application to Philosophy : Newcomb’s Problem and Free Will – Game trees- Application to Business: Competitive Decision making – Utility theory – Games against nature.

UNIT-II :

Two-person non-zero-sum games : Nash Equilibria and non-co-operative solutions – The Prisoner’s Dilemma – Applications to Social Psychology: Trust, Suspicion, and the F-Scale – Strategic Moves – Application to Biology : Evolutionarily Stable Strategies – The Nash Arbitration Scheme and Co-operative solutions- Application to Business: Management Labour Arbitration – Application to Economics: The duopoly Problem.UNIT-III :

N-Person Games : An introduction to N-person games – Application to Politics: Strategic Voting – N-person Prisoner’s Dilemma – Application to Athletics: Prisoner’s dilemma and the Football Draft – Imputations, Domination and Stable sets – Application to Anthropology: Pathan Organization.

UNIT-IV :

N-Person Games : The Core – The Shapley Value – Application to Politics: The Shapley-Shubik Power Index – Application to Politics: The Banshaf Index and the Canadian Constitution

UNIT-V :

N-Person Game : Bargaining sets – Application to Politics: Parliamentary Coalitions – The Nucleolus and the Gately Point – Application to Economics: Cost Allocation in India.

MSI C083 Internet and Java Programming + Computational Lab. –II 2 1 1 4

Objectives: To have hands-on experience on internet and to develop skills in writing codes for internet.

Course Content :

UNIT-I :

Internet Concepts – Internet Services – Types of Accounts – Media for Internet – ISP – TCP/IP and connection software – Dial-Up Networking - Setting up and Internet Connections.

UNIT-II :

Introduction to Web – Using the Web – URLs, Schemes, Host Names and Port Numbers – Using the Browser – Hypertext and HTML

UNIT-III :

Introduction to Java – Features of Java – Object Oriented Concepts – Lexical Issues – Data Types – Variables – Arrays – Operators

UNIT-IV :

Control Statements, Packages – Access Protection – Importing Packages – Interfaces

UNIT-V :

Exception Handling – Throw and Throws – Threads – Applets – Java Utilities – Code Documentation.

Computer Laboratory Exercises:Learn to use Internet Explorer and Netscape Navigator-Creation of E-Mail and sending messages-Chat-Greetings with Pictures-Downloading images-Voice mail service-Search Engines (Search a given topic and produce the details about that topic)-Design a web page of your favourite teacher, explaining his academic and personal facts and give suitable headings and horizontal rules. Design it in appropriate color-Design a web page advertising a product for marketing with charts of sales-Develop discussion forum for the purpose of communication between groups -Develop a page to send a mail to more than one person-Post a simple job site for the facility of the career.

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Department of Computer Science

Eligibility for Admission to Master of Computer Applications (M.C.A)

Candidate who have passed the under-mentioned degree examinations of this University or an examination of other institution recognized by this University as equivalent thereto provided they have undergone the course under 10+2+3 or 11+1+3 or 11+2+2 pattern or under the Open University System, shall be eligible for admission to the M.C.A. Degree Course under CBCS.

(a) B.C.A/B.E.S/B.Sc. in Computer Science/Mathematics/Physics/ Statistics / Applied Sciences OR (b) B.Com / Bachelor of Bank Management/B.B.A/B.L.M/B.A Corporate Secretaryship / B.A. Economics/ any other Bachelor’s Degree in any discipline with Business Mathematics and Statistics or Mathematics/Statistics in Main/Allied level OR (c) B.Sc., Chemistry with Mathematics and Physics as allied subjects OR (d) B.E/B.Tech/M.B.A OR (e) A Bachelor’s Degree in any discipline with Mathematics as one of the subjects at the Higher Secondary level (i.e. in +2 level of the 10+2 pattern)

Core and Elective Courses offered by the Department of Computer Science for M.C.A. Degree programme

Course Code Title of the Courses

Core/Electi

veCreditsL-T-P-C Course Faculty

MSI C324 Digital Principles C 3-0-0-3 S.GopinathanMSI C325 Programming in C C 3-0-0-3 PL. ChithraMSI C303 Object Oriented Data Structures C 3-0-0-3 B.Lavanya (B.L)MSI C332 Object Oriented Programming with C++ C 3-1-0-4 M.SornamMSI C333 C, C++ and Data Structures Lab. C 0-0-3-3 PL. Chithra/ G.F.

Elective E 2-1-0-3 Faculty Concerned

UOMS001 Soft Skill* S 2-0-0-2 Faculty Concerned

24

MSI C306 Computer Oriented Statistical Methods C 3-1-0-4 Guest FacultyMSI C307 Programming in Java C 3-0-0-3 PL.Chithra/G. F.MSI C308 Microprocessors and Applications C 3-0-1-4 S.GopinathanMSI C309 Visual Basic and Web Technology C 3-0-0-3 M.Sornam/B.LMSI C334 Java, Visual Basic and Web Design Lab. C 0-0-3-3 PL. Chithra &

M.Sornam / B.L.Elective E 2-1-0-3 Faculty

ConcernedUOMS002 Soft Skill* S 2-0-0-2 Faculty

ConcernedMSI C311 Operating Systems C 3-0-0-3 PL. Chithra/G.F.MSI C312 Design and Analysis of Algorithms C 3-0-0-3 P.ThanagvelMSI C313 Database Management Systems C 3-0-0-3 B.LavanyaMSI C314 Computer Graphics C 3-0-0-3 S.GopinathanMSI C335 Graphics and RDBMS Lab. C 0-0-3-3 S.Gopinathan/

B.LElective E 2-1-0-3 Faculty

ConcernedElective E 2-1-0-3 Faculty

ConcernedUOMS003 Soft Skill* S 2-0-0-2 Faculty

ConcernedUOMI 001 Internship-I S 0-0-2-2 Faculty

ConcernedMSI C316 Computer Networks C 3-1-0-4 P.ThangavelMSI C336 Unix and Shell Programming C 2-1-0-3 PL.ChithraMSI C337 Software Engineering C 3-1-0-4 S.GopinathanMSI C328 Network Programming and .NET C 3-0-0-3 M.Sornam & B.LMSI C329 Unix, Network Programming and .NET lab C 0-0-2-2 PL.Chitra,

M.Sornam & B.LElective E 3-0-0-3 Faculty

ConcernedElective E 3-0-0-3 Faculty

ConcernedUOMS004 Soft Skill* S 2-0-0-2 Faculty

ConcernedMSI C338 Mini Project and Group Discussion C 0-0-2-2 All FacultyMSI C322 Multimedia Systems C 3-0-1-4 B.Lavanya

Elective E 3-0-0-3 Faculty Concerned

Elective E 3-0-0-3 Faculty Concerned

Elective E 3-0-0-3 Faculty Concerned

UOMS005 Soft Skill* S 2-0-0-2 Faculty Concerned

UOMS006 Soft Skill* S 2-0-0-2 Faculty Concerned

MSI C339 Project Work C 0-0-20-20 All FacultyMSI E301 Computer Architecture E 3-0-0-3 Guest FacultyMSI E302 Principles of Compiler Design E 3-0-0-3 P.ThangavelMSI E303 Advanced Java Programming E 2-0-1-3 Guest FacultyMSI E304 Programming in COBOL E 2-0-1-3 Guest FacultyMSI E306 Artificial Neural Networks E 3-0-0-3 M.SornamMSI E307 Artificial Intelligence &Expert Systems E 3-0-0-3 Guest FacultyMSI E308 Distributed Computing E 3-0-0-3 Guest FacultyMSI E309 Data Mining and Warehousing E 3-0-0-3 Guest FacultyMSI E311 Software Project Management & Testing E 3-0-0-3 Guest FacultyMSI E312 Software Quality And Assurance E 3-0-0-3 Guest FacultyMSI E313 Digital Image Processing E 3-0-0-3 P.Thangavel/

PL.ChithraMSI E314 Computer Simulation & Modeling E 3-0-0-3 P.Thangavel/G.F.

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MSI E315 Computer Aided Design E 3-0-0-3 S.Gopinathan/M.Sornam

MSI E316 Pattern Recognition E 3-0-0-3 Guest FacultyMSI E321 Mobile Computing E 3-0-0-3 Guest FacultyMSI E317 Web-Commerce SS 2-2-0-4 Guest FacultyMSI E318 Object Oriented Analysis and Design SS 2-2-0-4 Guest Faculty

MSI E319 Introduction to Information Technology and Programming in C

E 2-0-1-3 Guest Faculty

MSI E320 Internet and Java Programming E 2-0-1-3 Guest Faculty

MSI C324 Digital Principles 3 0 0 3 S.Gopinathan

Number systems - compliments -logic gates-truth tables. Boolean algebra-truth table simplification of boolean function-Map method tabulation method - sequential logic-Flipflops-Registers-shiftreg-counters-processor design -design of an Accumulator Combinational Logic -adders, subtractors, decoders, encoders, multiplexer, demultiplexer. Processor design-arithmetic logic unit - status register - design of accumulator. Computer design - system configuration - computer instructions. MSIC325 Programming in C 3 0 0 3 PL.Chithra

Identifiers, Keywords, Data Types, Access Modifiers, Data Type Conversions, Operators, Conditional Controls - Loop Control – Input/Output Operations, Function Prototypes, Function Arguments - Pointers. Arrays, Accessing Array Elements, Dynamic Memory Allocation, Storage Classes, Structures, Unions, character I/O, String I/O, Formatting Input/Output file, Command Line Arguments.

MSIC303 Object Oriented Data Structures 3 0 0 3 B.Lavanya ADT- asymptotic notations- algorithmic analysis - classes and objects - concepts OOP - Arrays, representation of arrays - linked lists - circular linked lists - Stacks and queues - Binary trees - binary search tree - binary tree traversals--threaded binary tree - binary tree representation of trees - Graphs - spanning trees - shortest paths - sorting and searching - hashing- balanced trees - B-trees – Tries – AVL Tree, SPLAY tree.

MSI C332 Object Oriented Programming in C++

3 1 0 4 M.Sornam

Introduction to OOPS – Overview of C++, Classes, Structures – Union - Friend Functions, Friend Classes – Inline Functions, Constructors – destructors – Static Members – Scope resolution Operator – Passing Objects to Functions, Array, Pointers – Function Overloading, Overloading Constructors. Operator Overloading – Inheritance - Protected Members - Polymorphism – virtual Functions - Exception Handling - I/O Streams – Formations I/O with IOS Class Functions and Manipulators.

MSIC333 C, C++ and Data Structures Lab. 0 0 3 3 PL.Chithra/B.Lavanya

Primality test, string manipulation, matrix manipulation, generating permutations and combinations, creating database for telephone numbers and related operations, file processing., etc.- C++ - Implementation of arrays (single and multidimensional), polynomial object and overload operators – circular linked lists – doubly linked lists – implementation of stacks and queues – circular queues – evaluation of expressions – sorting – AVL trees – insertion etc.

MSIC306 Computer Oriented Statistical Methods 3 1 0 4 Guest Faculty

Sample spaces - events - Axiomatic approach to probability - conditional probability - Independent events - Baye's formula - Random Variables - Continuous and Discrete - distribution function - Expectation, variance, coefficient of variation, moment generation function - Chebyshev's inequality Bivariate distribution - conditional and marginal distributions - Binomial, Poison and geometric Distributions - Uniform, Normal, Exponential and Gamma distributions. Correlation - Rank correlation - Linear Regression - Method of Least squares - Fitting of the curve of the form ax + b, ax2 + bx + c, abx and axb

Courses offered for other Departments/Schools

26

- multiple and partial correlation( 3 -variables only). sampling - simple random sampling - Systematic sampling and stratified random sampling - concepts of sampling distributions and standard error - point estimation - Interval Estimation of mean and proportion. Tests of Hypotheses - Critical Region - Errors - Level of significance - power of the test - Large sample tests for mean and proportion - Exact tests based on Normal, t, F and Chi-square distributions. Basic principles of experimentation - Analysis of variance - one way and two way classifications - computing randomized design - Randomized Block design - Time series Analysis - Measurement of Trend and Seasonal variations.

MSIC307 Programming in Java 3 0 0 3 PL.Chithra/G.F.

Differences with C++ - interfaces - packages - applications - Applet - threading - synchronization - errors and exception - graphics - input/output files - streams - applet life cycle - thread life cycle.

MSI C308 Microprocessors and Applications 3 0 1 4 S.Gopinathan

Prerequisite : MSI C324 Introduction to 8085/8086 Microprocessor Architecture and Pin Function. Introduction to 8086 Instruction Set – Data Transfer – Arithmetic – Logic – Shift – Compare – Jump – Loop – Flag – Stack – Subroutine Instructions – 8086 Instruction formats – Assembly Language - Programs with Examples. Interfacing Data Converter – Digital–to-Analog , Analog–to- Digital - Memory Interface - Address Space - Programmable Peripheral Interface (8255A) – 8279 Programmable Keyboard Interface – 8086 Interrupts – Direct Memory Access – Burst Mode and Cycle Stealing. Temperature Control Monitoring Systems – Traffic Light Control Interface – Stepper Motor Interface – Interfacing 7 Segment LED Display – Introduction to Operational Amplifier.

MSI C309 Visual Basic and Web Technology 3 0 0 3 M.Sornam/B.Lavanya

Visual Basic: Features - VB Application - Control/properties/methods - Dialog boxes - VB Language - procedures and functions - in built function - object variables- API function. Internet concepts, Type of Accounts, ISP-TCP/IP and Connection software, Designing Interactive Webpages, HTML, DHTML, Basic Scripting-Java script, VB script, XML,ASP, ASP.NET,VB.NET.

MSIC334 Java, Visual Basic and Web Design Lab. 0 0 3 3 PL.Chithra/M.Sornam/B.Lavanya

Sub-string removal from a string using string buffer class – determining the order of numbers generated randomly using random class – usage of data classes – string manipulation using char array – usage of vector class – thread based applications – Applets- working with frames and various controls – working with dialogs and menus – panels and layouts – incorporating graphics – working with colors and fonts, etc. Visual programming – building simple applications – working with intrinsic controls and ActiveX controls – applications with multiple forms, dialogs, menus – application using data controls, common dialogs – drag and drop events – database managements – creating ActiveX controls, etc. Web Technology – greeting with pictures – downloading text and images – design a web page of your teacher, about your personal details, for a latest product, for any educational institution, for railway reservation, for social awareness, for environmental awareness and design web page for a hospital, etc.

MSI C311 Operating Systems 3 0 0 3 PL.Chithra/G. F.

Multiprogramming - Time sharing - Distributed system - Real - Time systems - I/O structure - storage hierarchy - Hardware protection - General system architecture - Operating system services - System calls - System programs - System design and implementation. Processes - CPU scheduling - process synchronization - Deadlocks - Storage management - memory management - virtual memory - Secondary storage management - file system interface, implementation - secondary storage structure - protection - security - UNIX system.

MSI C312 Design and Analysis of Algorithms 3 0 0 3 P. Thangavel

Introduction - asymptotic time analysis. Divide and conquer Method: binary search, finding maximum and minimum, merge sort and quick sort. Greedy method: optimal storage on tapes, knapsack problem, minimum spanning trees and single source shortest path problem. Dynamic programming: multistage graphs, 0/1 knapsack and traveling salesman problem. Basic search and traversal techniques: And/Or graph, bi-connected components, depth first search. Backtracking: 8 queens problem, sum of subsets,

27

graph coloring, Hamiltonian cycle and knapsack problem. Branch and bound: 0/1 knapsack problem, traveling salesman problem.

MSIC313 Database Management Systems 3 0 0 3 B.Lavanya

Prerequisite: (MSI C303 ) Purpose of Database Systems - relational, hierarchical and network models - SQL - PL/SQL - Client Server Concepts - relational calculus - relational algebra - QBE - normalization - virtual records - DBTG model - query processing and interpretation - query optimizer - database recovery - security and integrity.

MSI C314 Computer Graphics 3 0 0 3 S.Gopinathan /G.F.

Line Generation : Circle Generation - Graphics Primitives - Display devices - Display file co-ordinates - Polygons : Polygon Filling - Scaling, Rotation & Translation Transformations - Display procedures - Segments - Segment manipulation - Raster Techniques - Windowing and Clipping - Device handling algorithms - Simulating devices - Echoing - Interactive Techniques - 3D Fundamentals - Projections - Clipping in 3D- 3D viewing transformation - Hidden surfaces and lines. Dimension - Binary space partition- Light, color and shading - Transparency - Shadows - Ray tracing - Halftones - Color - Gamma correction - Fractals - Splines.

MSIC335 Graphics and RDBMS Lab. 0 0 3 3 S.Gopinathan/ B.Lavanya

Generate line, circle and box etc., using graphics primitives – generate line, zigzag line using DDA algorithm – generate line, circle, ellipse using Bressenham’s algorithm - generate character using bit-map method and DDA line drawing method – 2D transformation for scaling, translation, rotation, reflection, shearing – 3D transformation for scaling, translation, rotation – line clipping, character clipping and polygon clipping – generate any type of 3D object etc. RBDMS – creation of database and performing the operation given below using menu driven programming - insert, delete, modification, and report preparation – payroll – mark sheet processing – savings bank account for banking – inventory – invoice – library information system – railway reservation – income tax processing system – election ballot system – telephone directory maintenance – etc.

MSIC316 Computer Networks 3 1 0 4 P.Thangavel

Prerequisite : MSI C311 Goals and Applications of networks - Network Architectures - OSI reference model and services - Network topology - Physical layer - Transmission media - switching methods- Data link layer Design issues - error detection and correction - elementary data link protocols - sliding window protocols-Protocol specification & verification. Network layer-design issues-Routing, congestion, inter networking, - Routing algorithms - Shortest path, Multipath, Centralized, Isolated, Flooding, Distributed, Optimal, flow Based, Hierarchical & Broadcasting - Congestion control algorithms - pre allocation of buffer, packet discarding, flow control, choke packets, deadlocks. Transport layer - design issues - Connection management - Addressing, Establishing & Releasing a connection, Timer based Connection Management, Multiplexing, Crash Recovery, Email, - Cryptography - case studies: Arcnet, Ethernet, Arpanet.

MSIC336 Unix and Shell Programming 2 1 0 3 PL.Chithra

File and Common Commands - Shell – Directories – Devices – Permission – The Grep Family Filters – Streams – Concepts of Shell – Trapping Exit Codes- Shell Programming – Standard Input/Output – file Access – System Calls-Interprocess Communication-DeadLock Detection-Scheduling algorithms- Inodes – Processes – Signals- Interrupts – Preprocessors – Manual Page.

MSIC337 Software Engineering 3 1 0 4 S.Gopinathan

Prerequisite : MSI C325 Software and Software Engineering - Software Metrics - Estimation - Planning. Software Requirement Analysis: Computer systems Engineering - Fundamentals of Requirement Concepts of Structured Analysis - SADT; Object Oriented Analysis and Data Modeling - Alternate analysis techniques -

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Specification techniques. Software Design and Implementation : Programming Languages and Coding. Software Testing Techniques and Strategies. Software Quality Assurance. Software Maintenance - Software Configuration Management. Computer Aided Software Engineering Integrated CASE Environments (I-CASE ).

MSI C328 Network Programming and .NET 3 0 0 3 M.Sornam and B.Lavanya

Prerequisite : MSI C309

OOPs Fundamentals – Programming Concepts – Application Frame Work, Project Utility – MFC Library – Bar Chart with Resources. Graph Applications – Word Processor Applications – OLE Features and Specifications Continual Application, ActiveX Controls, Com – DHTML – ATL Vs ACTIVEX-Overview of ActiveX Scripting-Java Scripting – Standalone scripts-ActiveX Controls- Creating ActiveX Controls- ActiveX Documents- ActiveX Document Architecture-URL Monikers- Hyper linking interface- Working with URL Monikers- Overview of ISAPI- ISAPI Extension-ISAPI Filter-Designing IIS Application-Building IIS Application-Building Data Driven DHTML Application- ActiveX documents-Technology Migration Wizard-Modified Code-Launching and Testing document-Testing the DLL. “Beginning ASP.NET 1.1 with VB.NET 2003” -- Chris Ullman,John Kauffman, Chris Hart, David Sussmann.--- Wiley Publishing Inc. , WROX.Introduction – Server Controls and variables – Control structures – Procedural Programming – Subroutines and Functions – Event driven programming – Objects – Database Management – ADO.NET – ASP.NET Server Controls – Web Controls - .NET Assemblies – Error Handling – Web Services – ASP.NET Security.

MSIC329 Unix,Network Programming and .NET Lab. 0 0 2 2 PL.Chithra , M.Sornam and B.L

Shell script to solve quadratic equation – menu driven – user friendly changing modes – simple script for all control structures – process scheduling – authorized access – using pipes to calculate NCR – inter process communication using message queues – IPU using pipes – implementation of wait and signal using counting semaphores - automatic counter update problem – signaling process – deadlock detection - producer, consumer problems. creating menus – implementing keyboard accelerators – checking / un-checking and enabling / disabling menus – inserting and removing menus at runtime – floating popup menus – MDI with cascaded and tiled window – creating model and modeless dialog box - creating status bar – using list box with Clist Box class - using edit box with Cedit Box class – working of spin button controls – creating graphics editor etc. Network programming – working with java scripts – creating ActiveX controls – OLE server – OLE container – working with URL monikers – creating an ISAPI extension - creating an ISAPI editor – building IIS application – data driven DHTML application – ActiveX documents. Create a web form for an On-line Library.-Password Checking-Display records from a Database-Web server controls implementation-On-line shopping site-Quiz application-Usage of range validator control-Palindrome Checking-Sensex Application-Implementation of Cookies

MSIC338 MiniProject and Group Discussion 0 0 2 2 All Faculty

Each student will take a specific problem for the Mini Project and solve it using any one of latest tool and submit the report.

MSI C322 Multimedia Systems 3 0 1 4 B.Lavanya

Prerequisite : MSI C314

Evaluation of Multimedia - Components of Multimedia system - Hardware - Multimedia PC-Memory and Storage devices for multimedia - ODD and CD Technology and standards - Input devices - Output devices - Communication devices and peripheral connections. Software components of multimedia - text, audio, image and video processing - Elementary and Authoring tools - Interactive video and 3D Graphics in Multimedia. Multimedia Information Systems - Extending RDBMS to Image Management Systems, and voice Information Systems - MPEG, JPEG, DVI and UVC standards applied to multimedia and Distributed Information Systems. Organizing, Deign, production and Testing of Multimedia projects. Case studies in Education - Industrial Design - Presentation of software and concepts of virtual reality – video compression, audio compression, video conferencing and mobile multimedia.

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MSIC339 Project Work 0 0 20 20 All Faculty

Each student will do a project work and submit report of their work carried.

MSIE301 Computer Architecture 3 0 0 3 Guest Faculty Data representation - micro operations - Register transfer - micro programmed control - Central processing unit - Pipe lining - Vector processing and Array processors. Computer Arithmetic. Input-output organization - Memory organization - multi processors MSIE302 Principles of Compiler Design 3 0 0 3 P. Thangavel

Introduction - Finite Automata and lexical Analysis. Syntax Analysis - Context free grammars - Derivations and parse trees - Basic parsing techniques - LR parsing - Syntax - directed translation - symbol tables. Code optimization, generation - Error detection and recovery.

MSIE303 Advanced Java Programming 2 0 1 3 Guest Faculty

Servelet Overview, Java Webserver, Servelet Chaining, Session Management, Using JDBC in Servelets, Applet to Servelet Communication, Java Beans EJB Architecture, Design and Implementation, EJB Session Beans, EJB Entity Beans, Implementation and Entity Direction of EJB, JSP,J2EE

MSIE304 Programming in COBOL 2 0 1 3 Guest Faculty

Introduction to COBOL-IDENTIFICATION Division-PROCEDURE Division-Debugging and program testing- Keyboard Input and screen Display-Output formatting –Arithmetic Operations-Report design and coding-Conditional Operations-Designing and writing Control Break programs-Data Validation design and coding-processing Arrays/Tables-Processing multidimensional Tables-Sorting-Master-Transaction File Processing-Indexed File Processing-Program Management.

MSIE306 Artificial Neural Networks 3 0 0 3 M.Sornam

Prerequisite : MSI C316

Basics of ANN - Characterization of biological neural networks - Artificial intelligence Vs Neural networks - Principles and Promises - Learning rules. Functional Units - Activation functions - Feed forward ANN - single layer network Limitation - Need for Multi-layer network - Capabilities - Back propagation algorithm - applications - limitations. Feedback ANN - Hopfield network - Architecture - Dynamics - energy function - Applications - optimization - Traveling Salesman Problem - A/D converter. Feedback and feed forward networks - Competitive learning algorithm - weight initialization issues solving convex combination method - Noise addition and Neighborhood method - feature mapping - self organizing map - Applications. Neural architectures for complex pattern recognition tasks - counter propagation network - applications - image compression - function approximation look up table - Bi-directional Associative Memory - Variations on BAM - Applications.

MSIE307 Artificial Intelligence &Expert Systems 3 0 0 3 Guest Faculty

Prerequisite : MSI C303

Evolution of Artificial Intelligence production systems - search strategies - Hill climbing, backtracking graph search - algorithm A and A *, monotone restriction specialized production systems - AO* algorithm. Searching game trees: Minimax Procedure alpha beta pruning - predicate calculus - Answer extraction - knowledge based systems - knowledge processing, inference techniques. Expert system Definition - stages in development - knowledge representation and acquisition techniques - building expert systems - Forward and Backward Chaining - Tools - Explanation facilities - Meta Knowledge - fuzzy reasoning - case study: Mycin. Applications of A.I - Natural language processing and understanding - perception - Learning using Neural nets.

MSIE308 Distributed Computing 3 0 0 3 Guest Faculty

Prerequisite : MSIC313

Models for Distributed Computing - Remote procedure calls - Switched multiprocessor - Bus based multi-computer - Switched multi-computers - Network operating systems and NFS - Time distributed systems - Transparency - Flexibility - Reliability - performance - scalability - The client - server model - Blocking

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and un-buffered primitives - Implementation of client-server model. Synchronization in distributed systems - Clock synchronization - Mutual exclusion - Election algorithms - Atomic transactions - Dead locks in distributed system - Threads - Thread usage and implementation of thread packages - processor allocation - Distributed File System - Implementation of new trends in distributed file systems - Distributed databases.

MSIE309 Data Mining and Warehousing 3 0 0 3 Guest Faculty

Main operations: Clustering, Classification, Regression, Neural Networks, Feature Selection, Deviation, Detection – Context of Data mining – Four approaches to Data mining – Data mining Methodology – Three pillars of Data mining – Data for Data mining – Dirty Data – Settling Data mining Environment – Data Warehouse Database – Analyzing context of Data Warehouse, Basic Data Warehouse Architecture, Online Analytical Processing Systems (OLAP). Success and failure stories of Data mining - Survey of existing mining & OLAP Products. Applications in Web mining.

MSIE311 Software Project Management & Testing

3 0 0 3 Guest Faculty

Introduction to Software Project Management- Software project versus other types of project- problems- management control- Stakeholders- Requirement Specification – Information and control in organizations Introduction to step wise project planning- Select-identify scope and objectives- waterfall model- v-process model-spiral model- software prototyping- ways of categorizing prototypes- tools- incremental delivery- selecting process model -Software effort estimation- introduction- where-problems with over and under estimates- basis for software estimating- software effort estimation technique- expert judgment-COCOMO -Activity Planning- Objectives- Project schedules- projects and activities- sequencing and scheduling activities- sequencing and scheduling problem-job sequencing-n jobs through two machines, two jobs through m-machines and n-jobs through m-machines, PERT and CPM techniques-critical path-Normal path and crash time-Resource allocation-Resource leveling and smoothing.

MSIE312 Software Quality And Assurance 3 0 0 3 Guest Faculty

Introduction - Quality and the quality system - standards and procedures technical activities. Software tasks - management responsibility - quality system - contract review - design control - document control - purchasing - product identification and traceability. Process control - checking - identification of testing tools - control of nonconforming product - Corrective action. Handling, storage, packing and delivery - Quality records - Internal quality audits - Training - Servicing - statistical techniques. QA and new technologies - QA and Human - Computer interface - process modeling - standards and procedures. ISO-9001 - Elements of ISO 9001 - Improving quality system - Case study.

MSIE313 Digital Image Processing 3 0 0 3 P.Thangavel/PL.Chithra

Prerequisite : MSI C314

Introduction - Problems and Applications - Two dimensional systems and Mathematical preliminaries - Linear Systems and Shift invariance - Fourier Transform - Properties - Fourier Series - Matrix theory results - Block Matrices and kronecker products. Image perception - light, luminance, Brightness and Contrast - MTF of Visual systems - Monochrome vision models - image fidelity criteria - color representation. Digital image sampling and quantization - 2D sampling theory - image reconstruction from samples, Bandlimited images, sampling theorem, Nyquist rate, Aliasing and foldover frequencies - image quantization - Optimum mean square Quantizer. Image Enhancement - point operations - contrast structuring, clipping & thresholding etc - Histogram modeling - spiral operations - special averaging & low pass filtering, Directional Smoothing, median filtering, Replication, Linear interpolation, Magnification & interpolation (Zooming) - false color and pseudo color. Image restoration - Image observation models - Inverse and Wiener filtering - Least square filters - Image Analysis - Edge Detection - Boundary extraction - Boundary representation - Region representation - Image Segmentation - Classification Techniques - Image understandings. Image Data Compression - Pixel coding - PCM, Entropy coding, Runlength, Bitplane extraction - Predictive techniques - Delta Modulation line by line DCPM etc - Interface - Coding of two tone images.

MSIE314 Computer Simulation & Modeling 3 0 0 3 P.Thangavel

Prerequisite : MSI C306

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Introduction to Simulation: types of system - Discrete and Continuous Systems - Model of a System - Types of Models - Discrete-Event System Simulation - Steps in a Simulation Study; Simulation Examples. Discrete and continuous simulation Languages -study and use of one language in detail. Simulation of Manufacturing and Material Handling Systems - Simulation of Queuing Systems - Random-Number Generation- Tests for Random Numbers. Random Variate Generation: Inverse Transformation Technique:- Uniform Distribution - Exponential Distribution - Weibull Distribution - Triangular Distribution - Empirical Continuous Distribution - Discrete Distribution - Direct Transformation for the Normal Distribution - Convolution Method for Erlang Distribution - Acceptance - Rejection Technique: Poisson Distribution - Gamma Distribution. Input Data Analysis: Data Collection - Identifying the Distribution with Data - Parameter Estimation - Goodness-of- Fit Tests:- Chi-Square Test - Kolmogorov-Smirnov Test; Selecting Input Models without Data - Multivariate and Time-Series Input Models. Verification and Validation of Simulation Models - Calibration and Validation of Models - Output Data Analysis - Alternative System Designs

MSIE315 Computer Aided Design 3 0 0 3 S.Gopinathan/M.Sornam

Prerequisite : MSI C314

Introduction to CAD; Role of Computers in the design process. Hardware - Input devices, Display devices, Output devices, Computation devices. Computer Graphics Software and Data Base - Software configuration of a Graphics System - Data Base Structure and content - Wire Frame Modeling, Surface Modeling, Solid Modeling. Numerical Control, The beginning of CAM : Conventional Numerical Control - Components of an NC system - NC procedure - Coordinate systems - Applications. NC Part Programming - Manual Part Programming. NC Programming with Interactive Graphics. Computer Controls in NC - Computer and Direct Numerical Control - Adaptive Control Machining system. Applications: CAD for LSI/VLSI applications: Device circuit and process modeling for IC technology: optimization techniques in IC design: Design automation, Design for testability: Specific examples. Mechanical Drafting: Basic CAD Two-dimensional drafting, mechanical CAD software, developing a mechanical database, solid modeling. Electrical applications: Advantages of computer graphics systems for electrical design and drafting, CAD as an aid to electrical designers and drafters, production of an electrical schematic or wiring diagram, production of a printed-circuited board design, designing integrated circuits. Piping and Instrumentation diagrams: Setting up the system, applying P and ID, creating the drawing, drawing revisions, text drawing annotation, text revisions, drawing formats, report generation, documentation: Plotters. Solid Modeling: Converging technologies of CAD, CAM and CAE, interacting with SM systems, display requirements. Cartography: Mapping applications - uses and users, map production, automated cartography. Case Studies: LPKF, Unigraphics CAD/CAM Software, NISA Finite Element Analysis Software, GOS CAD Package. MSIE316 Pattern Recognition 3 0 0 3 Guest Faculty

Prerequisite : MSI C306

Basic concepts, Fundamental Problems, Design concepts and examples. Decision Function: Role of decision functions in Pattern recognition, Linear and Generalised decision functions, concepts of pattern space and weight space. Geometrical properties. Implementation of decision functions, Multivariable functions. Pattern Classification : Pattern Classification by distance functions, Likelihood function - Minimum distance classification. Clusters and cluster seeking algorithms. Introduction to the problem of feature selection and extraction. Binary feature selection, Statistical and Structural Feature Extraction. Introduction to Tree languages and Syntactic Pattern Recognition. Syntactic Pattern Recognition on the Basis of Functional approximation Syntactic pattern description, recognition grammars. Acquisition and Utilisation of Access Patterns in Relational Data Base Implementation, Knowledge Acquisition Algorithms.

MSIE321 Mobile Computing 3 0 0 3 Guest Faculty

Introducing the mobile internet-Key Services for the mobile internet-making internet “Mobile” – challenges and pitfalls – Overview of the wireless application protocol – Implementing WAP services – WML – Wireless binary extensible markup language – enhances WML – User interface design - Advanced WAP – Tailoring content to the Client – Push Messaging.

MSIE317 Web – Commerce 2 2 0 4 Guest Faculty

Pre-Requisite: MSI C313

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Environment - Opportunities - Modes - Security - E-Cash - E-Payment - E-Transaction - E-Mail Technologies for E-Commerce - Web Site Establishment - Internet Resources - Advertising - Publishing issues - Approaches - Legalities - Technologies.

MSIE318 Object Oriented Analysis & Design 2 2 0 4 Guest Faculty

Prerequisite : MSI C326/ MSI C307

Systems Development - Object Basics - Development Life Cycle - Methodologies - UML - Use-Case Models - Object Analysis - Object Relations - Design Processes - Design Axioms - Class Design - Object Storage - Object Interoperability - View Layer - Software Quality Assurance - System Usability - Measuring User Satisfaction - Case Studies.

Elective Courses offered for other Departments/Schools

MSI E319 Introduction to Information Technology and Programming in C 2 0 1 3 Guest Faculty

Introduction to Computer – Classification of Digital Computer System – Computer Architecture – Number System – Memory Unit – Input–Output Device – Logic Gates – Truth Table. Introduction to Computer Software - Programming Language C– Identifiers – Keywords – Data Types – Access Modifiers – Data Type Conversions – Operators – Conditional Controls – Loop Control – Input/Output Operations – Function Prototypes – Function Arguments – Arrays – Structures-Implementing some Problems Using ‘C’ Language. Introduction to MS-WORD, MS-ACCESS, MS-EXCEL – Creating Recruitment Database and Create Application Table - Creating Tables Using EXCEL - Creating Graphs – MS-ACCESS – Planning and Creating Tables and Using the feature of Chart, Bar Chart, Pie Chart etc. Introduction to Internet – Creating an E-Mail Account using E-mail Service.

MSI E320 Internet and Java Programming 2 0 1 3 Guest Faculty

Internet Concepts – Internet Services – Types of Accounts – Media for Internet – ISP – TCP/IP and connection software – Dial-Up Networking - Setting up and Internet Connections. Introduction to Java – Features of Java – Object Oriented Concepts – Lexical Issues – Data Types – Variables – Arrays – Operators – Control Statements, Packages – Access Protection – Importing Packages – Interfaces – Exception Handling – Throw and Throws – Threads – Applets – Java Utilities – Code Documentation.

Department of Computer ScienceEligibility for Admission to Master of Science in Computer Science Bachelor's degree in Computer Science or Computer Science & Technology or B.C.A. degree of University of Madras or any other degree accepted as equivalent thereto by the Syndicate.

M.Sc. Degree Programme in Computer Science – List of Core Courses Course Code Title of the Courses

Core/Electi

veCreditsL-T-P-C Course Faculty

MSIC401 Mathematics for Computer Science C 3-1-0-4 Guest Faculty(G.F.)

MSIC402 Design and Analysis of Algorithms C 3-0-1-4 P.ThangavelMSIC414 Information Theory C 3-1-0-4 P.ThangavelMSIC404 Java and Operating Systems Lab. C 0-0-2-2 GuestFaculty

Elective E 3-0-0-3 Faculty ConcernedElective E 3-0-0-3 Faculty Concerned

UOMS001 Soft Skill* S 2-0-0-2 Faculty ConcernedMSIC405 Theory of Computation C 3-1-0-4 M.Sornam/G.F.MSIC406 Computer Networks C 3-1-0-4 P.ThangavelMSIC407 Advanced Database Systems C 3-0-0-3 B.Lavanya/G.F.MSIC408 Advanced Database Systems Lab. C 0-0-2-2 B.Lavanya/G.F.

Elective E 3-0-0-3 Faculty ConcernedElective E 3-0-0-3 Faculty Concerned

UOMS002 Soft Skill* S 2-0-0-2 Faculty ConcernedMSIC409 Artificial Intelligence C 3-0-0-3 M.Sornam/G.F.MSIC410 Digital Image Processing C 3-1-0-4 P.Thangavel/

PL.ChithraMSIC415 Multimedia Systems C 3-0-1-4 B.Lavanya

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MSIC412 Mini Project C 0-0-2-2 All FacultyElective E 3-0-0-3 Faculty ConcernedElective E 3-0-0-3 Faculty Concerned

UOMS003 Soft Skill* S 2-0-0-2 Faculty ConcernedUOMS004 Soft Skill* S 2-0-0-2 Faculty ConcernedUOMI001 Internship-I S 2-0-0-2 Faculty ConcernedMSIC416 Project Work C 0-0-20-20 All Faculty

Additional list of Elective courses:

Course Code Title of the Courses Electi

veCreditsL-T-P-C Course Faculty

MSIE401 Computer Graphics E 3-0-0-3 S.GopinathanMSIE402 Cryptography E 3-0-0-3 P.Thangavel/G.F.MSIE403 Unix and Shell Programming E 3-0-0-3 Guest FacultyMSIE404 Network Programming and .NET E 3-0-0-3 Guest Faculty

MSIC401 Mathematics for Computer Science 3 1 0 4 Guest Faculty

Set theory: Operations on sets – Basic set identities – Relations and orderings – Functions. Linear vector spaces: Linear operators – vectors in n-dimensions – matrix representation of vectors and operators in a basis – linear independence, dimension – inner product – Schwarz inequality – Orthonormal basis – Gram-Schmidth process – Eigen values and eigen functions of operators/matrices – Hermitian and Unitary operators/matrices – Cayley Hamilton theorem – Diagonalizing matrix. Linear differential equations: Second order linear differential equations – Strum-Liouville theory – Orthogonality of eigen functions – Illustration with Legendre, Laguerre, Hermite, Chebyshev differential equations - expansion of polynomials – location of zeros polynomials – Wronskian, ordinary and singular points – Dirac delta function. Laplace and Fourier transforms: Laplace Transforms – Solution of linear differential equations with constant coefficients – Fourier integral – Fourier transform – Fourier sine and cosine transforms – convolution theorems.

MSIC402 Design and Analysis of Algorithms 3 0 1 4 P. Thangavel

Introduction - asymptotic time analysis. Divide and conquer Method: binary search, finding maximum and minimum, merge sort and quick sort. Greedy method: optimal storage on tapes, knapsack problem, minimum spanning trees and single source shortest path problem. Dynamic programming: multistage graphs, 0/1 knapsack and traveling salesman problem. Basic search and traversal techniques - Bi-connected components, depth first search. Backtracking: 8 queens problem, sum of subsets, graph coloring, Hamiltonian cycle and knapsack problem. Branch and bound: 0/1 knapsack problem, traveling salesman problem.

MSIC414 Information Theory 3 1 0 4 P.Thangavel

Basics of Probability – conditional and joint probability – Baye’s theorem. Models for Information channel: Discrete Memoryless Channel, Binary Symmetric Channel (BSC), Burst Channel, Bit-error rates. Entropy and Shannon’s measure of Information. Channel capacity theorem. Rate and Optimality of Information transmission. Variable Length Codes: Prefix Codes, Huffmann Codes, Lempel-Zev (LZ) Codes. Optimality of these codes, Information Content of these Codes. Error Correcting and Detecting Codes: Finite fields, Hamming distance, Bounds of Codes, Linear (Parity Check) codes, Parity Check Matrix, Generator matrix, Decoding of Linear codes, Hamming Codes.

MSIC404 Java and Operating systems lab. 0 0 2 2 Guest Faculty

Java Programming: HTML to Servlet Applications - Applet to Servlet Communication - Designing online applications with JSP - Creating JSP program using JavaBeans - Working with Enterprise JavaBeans - Performing Java Database Connectivity - Creating Web services with RMI - Creating and Sending Email

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with Java - Building web applications. Operating systems: Inter Process Communication (IPC) using Message Queues - IPC using pipes - Implementation of wait and signal using counting semaphores -Implementation of wait and signal using binary semaphores - Atomic Counter update problem -Counting Semaphores at the user level using binary semaphores- Signaling processes - Deadlock detection (for processes passing messages) - Process Scheduling: FCFS , Least Frequently Used, Round Robin - Producer-Consumer problem with limited buffers - Dining-Philosopher Problem - Reader-Writer problem - Two Process Mutual Exclusion.

MSIC405 Theory of Computation 3 1 0 4 M.Sornam/G.F.

Introduction to finite Automata – Regular expression and languages – Algebraic Laws for regular expressions – Properties of regular languages – Pumping Lemma for regular expressions – Closure properties of regular languages – Decision properties of regular languages – Equivalence and minimization of Automata – Parse trees – Applications of context free grammars – Parsers – ambiguity in grammars and languages – Pushdown Automata – Properties of Context free languages – Introduction to Turing Machines – programming techniques for Turing Machines – Undecidability – Post’s correspondence problem – other undecidable problems.

MSI C406 Computer Networks 3 1 0 4 P.Thangavel

Goals and Applications of networks - Network Architectures - OSI reference model and services - Network topology - Physical layer - Transmission media - switching methods- Data link layer Design issues - error detection and correction - elementary data link protocols - sliding window protocols. MAC sublayer – general protocols. Network layer-design issues- Routing algorithms - Shortest path, Multipath, Centralized, Isolated, Flooding, Distance vector, link state, Hierarchical & Broadcasting - Congestion control algorithms - pre allocation of buffer, packet discarding, flow control, choke packets. Transport layer - design issues - Connection management - Addressing, Establishing & Releasing a connection, Timer based Connection Management, Multiplexing, Crash Recovery.

MSIC407 Advanced Database Systems 3 0 0 3 B.Lavanya/Guest Faculty

Purpose of Database Systems-Data models-Relational-hierarchical-network –relational calculus-relation algebra-DBA-Transaction Mgmt-Entity Relationship Diagrams-Normalization-SQL-QBE-QUEL-Query processing & interpretation-Query optimization-database recovery-security and integrity-object-based databases and XML-database system architecture-distributed databases-parallel databases-Application development and administration – advanced querying and information retrieval – advanced transaction processing-Case studies-Oracle , Microsoft SQL Server.

MSIC408 Advanced Database Systems Lab. 0 0 2 2 B.Lavanya/Guest Faculty

Library management system - bank transactions – inventory transaction system - question database and conducting quiz – creation of character animation – designing web pages – creation of image animation –applications to show the masking effect etc.

MSIC409 Artificial Intelligence 3 0 0 3 M.Sornam / G.F.

Evolution of A.I- Production system-Search strategies-Hill climbing-Backtracking graph search-Algorithm A & A*- AO* algorithm. Adversarial search-Searching game trees-Minimax Procedure, alpha beta pruning-Reactive machines-Stimulus-Response Agents-Knowledge Representation & reasoning – Predicate Calculus-Knowledge based systems- Reasoning using Horn clauses- Maintenance in Dynamic Knowledge bases- Rule learning- Knowledge representation by networks-Semantic Networks- non-monotonic reasoning, frames, scripts-Natural Languages processing –RTN,ATN,Parsing of CFGs-Probabilistic Theory- Bayes Networks-Communication & Integration –Multiple agents.

MSIC410 Digital Image Processing 3 1 0 4 P.Thangavel/PL.Chithra

Introduction – steps in image processing, Image acquisition, representation, sampling and quantization, relationship between pixels. – color models – basics of color image processing.Image enhancement in spatial domain – some basic gray level transformations – histogram processing – enhancement using arithmetic , logic operations – basics of spatial filtering and smoothing. Image enhancement in Frequency domain – Introduction to Fourier transform: 1- D, 2 –D DFT and its inverse transform, smoothing and sharpening filters. Image restoration: Model of degradation and restoration process – noise models – restoration in the presence of noise- periodic noise reduction.. Image segmentation: Thresholding and region based segmentation. Image compression: Fundamentals –

35

models – information theory – error free compression –Lossy compression: predictive and transform coding. JPEG standard.

MSI C415 Multimedia Systems 3 0 1 4 B.Lavanya

Evaluation of Multimedia - Components of Multimedia system - Hardware - Multimedia PC-Memory and Storage devices for multimedia - ODD and CD Technology and standards - Input devices - Output devices - Communication devices and peripheral connections. Software components of multimedia - text, audio, image and video processing - Elementary and Authoring tools - Interactive video and 3D Graphics in Multimedia. Multimedia Information Systems - Extending RDBMS to Image Management Systems, and voice Information Systems - MPEG, JPEG, DVI and UVC standards applied to multimedia and Distributed Information Systems. Organizing, Deign, production and Testing of Multimedia projects. Case studies in Education - Industrial Design - Presentation of software and concepts of virtual reality – video compression, audio compression, video conferencing and mobile multimedia.

MSIC412 Mini Project 0 0 2 2 All FacultyEach student will carry out a project on a selected problem and submit a report.

MSIC416 Project Work 0 0 20 20 All FacultyEach student will do a project work and submit report of work carried out.

MSI E401 Computer Graphics 3 0 0 3 S.Gopinathan

Line Generation : Circle Generation - Graphics Primitives - Display devices - Display file co-ordinates - Polygons : Polygon Filling - Scaling, Rotation & Translation Transformations - Display procedures - Segments - Segment manipulation - Raster Techniques - Windowing and Clipping - Device handling algorithms - Simulating devices - Echoing - Interactive Techniques - 3D Fundamentals - Projections - Clipping in 3D- 3D viewing transformation - Hidden surfaces and lines. Dimension - Binary space partition- Light, color and shading - Transparency - Shadows - Ray tracing - Halftones - Color - Gamma correction - Fractals - Splines.

MSI E402 Cryptography 3 0 0 3 P.Thangavel/G.F.

Conventional Encryption: Conventional encryption model – DES –RC 5 – Introduction to AES - Random number generation. Number Theory: Modular arithmetic – Euler’s theorem – Euclid’s algorithm – Chinese remainder theorem – Primarily and factorization –Discrete logarithms – RSA algorithm - Public key Cryptography: Principles – RSA algorithm – key management- Diff – Hellman key exchange - Message Authorization and Hash functions: Hash functions-Authentication requirements –Authentication function- Message authentication codes –Secure Hash algorithms - Digital Signature and Authentication Protocols : Digital Signature-Authentication Protocols –Digital signature standard.

MSIE403 Unix and Shell Programming 2 1 0 3 PL.Chithra

File and Common Commands - Shell – Directories – Devices – Permission – The Grep Family Filters – Streams – Concepts of Shell – Trapping Exit Codes- Shell Programming – Standard Input/Output – file Access – System Calls-Interprocess Communication-DeadLock Detection-Scheduling algorithms- Inodes – Processes – Signals- Interrupts – Preprocessors – Manual Page.

MSI E404 Network Programming and .NET 3 0 0 3 M.Sornam and B.Lavanya

OOPs Fundamentals – Programming Concepts – Application Frame Work, Project Utility – MFC Library – Bar Chart with Resources. Graph Applications – Word Processor Applications – OLE Features and Specifications Continual Application, ActiveX Controls, Com – DHTML – ATL Vs ACTIVEX-Overview of ActiveX Scripting-Java Scripting – Standalone scripts-ActiveX Controls- Creating ActiveX Controls- ActiveX Documents- ActiveX Document Architecture-URL Monikers- Hyper linking interface- Working with URL Monikers- Overview of ISAPI- ISAPI Extension-ISAPI Filter-Designing IIS Application-Building IIS Application-Building Data Driven DHTML Application- ActiveX documents-Technology Migration Wizard-Modified Code-Launching and Testing document-Testing the DLL. “Beginning ASP.NET 1.1 with VB.NET 2003” -- Chris Ullman,John Kauffman, Chris Hart, David Sussmann.--- Wiley Publishing Inc. , WROX.

36

Introduction – Server Controls and variables – Control structures – Procedural Programming – Subroutines and Functions – Event driven programming – Objects – Database Management – ADO.NET – ASP.NET Server Controls – Web Controls - .NET Assemblies – Error Handling – Web Services – ASP.NET Security.

MASTER OF PHILOSOPHY PROGRAMME M.Phil in Computer Science (Full Time )Duration of the course : One Year (Two Semester )

Eligibility for Admission :

A Masters Degree in Computer Science or Information Technology or M.C.A. Degree of the University of Madras or any other University recognized by the Syndicate as equivalent thereto, provided that those who have qualified for the Master’s Degree prior to 1st January 1991 must have secured a minimum of 50 percent of marks and those who have qualified for the master’s degree on or after 1 st

January 1991 must have secured a minimum of 55 percent of marks. For SC/ST candidates who have qualified on or after 1st January 1991 a concession of 5 percent of marks shall be given in the minimum eligibility marks

Course Code Title of the Courses Core/Electi

ve

L-T-P-C Faculty

First SemesterMSI C101 Research Methodology C 3-2-0-5 Guest FacultyMSI C102 Advance course on Computing C 3-2-0-5 P.ThangavelMSI E101 Selected Topics in Algorithms E 3-2-0-5 P.Thangavel/

G.F.MSI E102 Artificial Neural Networks E 3-2-0-5 P.Thangavel/

G.FMSI E103 Digital Image Processing E 3-2-0-5 P.Thangavel/

G.FMSI E104 Wireless Networks E 3-2-0-5 P.Thangavel/

G.FSecond SemesterMSI C103 Dissertation and Viva-voce C 6+15=21 P.Thangavel/

G.F.

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M.Sc. Computer Science (Self Supportive)Eligibility for Admission to Master of Science in Computer Science Bachelor's degree in Computer Science or Computer Science & Technology or B.C.A. degree of University of Madras or any other degree accepted as equivalent thereto by the Syndicate.

M.Sc. Degree Programme in Computer Science – List of Core Courses Course Code Title of the Courses

Core/Electi

veCreditsL-T-P-C Course Faculty

MSIC401 Mathematics for Computer Science C 3-1-0-4 Guest Faculty(G.F.)

MSIC402 Design and Analysis of Algorithms C 3-0-1-4 P.ThangavelMSIC414 Information Theory C 3-1-0-4 P.ThangavelMSIC404 Java and Operating Systems Lab. C 0-0-2-2 GuestFaculty

Elective E 3-0-0-3 Faculty ConcernedElective E 3-0-0-3 Faculty Concerned

UOMS001 Soft Skill* S 2-0-0-2 Faculty ConcernedMSIC405 Theory of Computation C 3-1-0-4 M.Sornam/G.F.MSIC406 Computer Networks C 3-1-0-4 P.ThangavelMSIC407 Advanced Database Systems C 3-0-0-3 B.Lavanya/G.F.MSIC408 Advanced Database Systems Lab. C 0-0-2-2 B.Lavanya/G.F.

Elective E 3-0-0-3 Faculty ConcernedElective E 3-0-0-3 Faculty Concerned

UOMS002 Soft Skill* S 2-0-0-2 Faculty ConcernedMSIC409 Artificial Intelligence C 3-0-0-3 M.Sornam/G.F.MSIC410 Digital Image Processing C 3-1-0-4 P.Thangavel/

PL.ChithraMSIC415 Multimedia Systems C 3-0-1-4 B.Lavanya

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MSIC412 Mini Project C 0-0-2-2 All FacultyElective E 3-0-0-3 Faculty ConcernedElective E 3-0-0-3 Faculty Concerned

UOMS003 Soft Skill* S 2-0-0-2 Faculty ConcernedUOMI001 Internship-I S 2-0-0-2 Faculty ConcernedMSIC416 Project Work# C 0-0-22-22 All FacultyUOMS004 Soft Skill** S 2-0-0-2 Faculty Concerned** Instead of UOMS004: Soft Skill , any other additional elective course may be opted by M.Sc. Computer Science students, so as to earn 88 credits.

Additional list of Elective courses: Course Code Title of the Courses Electi

veCreditsL-T-P-C Course Faculty

MSIE401 Computer Graphics E 3-0-0-3 S.GopinathanMSIE402 Cryptography E 3-0-0-3 P.Thangavel/G.F.MSIE403 Unix and Shell Programming E 3-0-0-3 Guest FacultyMSIE404 Network Programming and .NET E 3-0-0-3 Guest Faculty

MSIC414 Information Theory 3 1 0 4 Guest Faculty

Basics of Probability – conditional and joint probability – Baye’s theorem. Models for Information channel: Discrete Memoryless Channel, Binary Symmetric Channel (BSC), Burst Channel, Bit-error rates. Entropy and Shannon’s measure of Information. Channel capacity theorem. Rate and Optimality of Information transmission. Variable Length Codes: Prefix Codes, Huffmann Codes, Lempel-Zev (LZ) Codes. Optimality of these codes, Information Content of these Codes. Error Correcting and Detecting Codes: Finite fields, Hamming distance, Bounds of Codes, Linear (Parity Check) codes, Parity Check Matrix, Generator matrix, Decoding of Linear codes, Hamming Codes.

MSI C415 Multimedia Systems 3 0 1 4 B.Lavanya

Evaluation of Multimedia - Components of Multimedia system - Hardware - Multimedia PC-Memory and Storage devices for multimedia - ODD and CD Technology and standards - Input devices - Output devices - Communication devices and peripheral connections. Software components of multimedia - text, audio, image and video processing - Elementary and Authoring tools - Interactive video and 3D Graphics in Multimedia. Multimedia Information Systems - Extending RDBMS to Image Management Systems, and voice Information Systems - MPEG, JPEG, DVI and UVC standards applied to multimedia and Distributed Information Systems. Organizing, Deign, production and Testing of Multimedia projects. Case studies in Education - Industrial Design - Presentation of software and concepts of virtual reality – video compression, audio compression, video conferencing and mobile multimedia.

MSIC416 Project Work 0 0 22 22 All FacultyEach student will do a project work and submit report of work carried out.

MSIE403 Unix and Shell Programming 2 1 0 3 PL.Chithra

File and Common Commands - Shell – Directories – Devices – Permission – The Grep Family Filters – Streams – Concepts of Shell – Trapping Exit Codes- Shell Programming – Standard Input/Output – file Access – System Calls-Interprocess Communication-DeadLock Detection-Scheduling algorithms- Inodes – Processes – Signals- Interrupts – Preprocessors – Manual Page.

MSI E404 Network Programming and .NET 3 0 0 3 M.Sornam and B.Lavanya

OOPs Fundamentals – Programming Concepts – Application Frame Work, Project Utility – MFC Library – Bar Chart with Resources. Graph Applications – Word Processor Applications – OLE Features and Specifications Continual Application, ActiveX Controls, Com – DHTML – ATL Vs ACTIVEX-Overview of ActiveX Scripting-Java Scripting – Standalone scripts-ActiveX Controls- Creating ActiveX Controls- ActiveX

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Documents- ActiveX Document Architecture-URL Monikers- Hyper linking interface- Working with URL Monikers- Overview of ISAPI- ISAPI Extension-ISAPI Filter-Designing IIS Application-Building IIS Application-Building Data Driven DHTML Application- ActiveX documents-Technology Migration Wizard-Modified Code-Launching and Testing document-Testing the DLL. “Beginning ASP.NET 1.1 with VB.NET 2003” -- Chris Ullman,John Kauffman, Chris Hart, David Sussmann.--- Wiley Publishing Inc. , WROX.Introduction – Server Controls and variables – Control structures – Procedural Programming – Subroutines and Functions – Event driven programming – Objects – Database Management – ADO.NET – ASP.NET Server Controls – Web Controls - .NET Assemblies – Error Handling – Web Services – ASP.NET Security.

MASTER OF PHILOSOPHY PROGRAMME M.Phil in Computer Science (Full Time )Duration of the course : One Year (Two Semester )

Eligibility for Admission :

A Masters Degree in Computer Science or Information Technology or M.C.A. Degree of the University of Madras or any other University recognized by the Syndicate as equivalent thereto, provided that those who have qualified for the Master’s Degree prior to 1st January 1991 must have secured a minimum of 50 percent of marks and those who have qualified for the master’s degree on or after 1 st

January 1991 must have secured a minimum of 55 percent of marks. For SC/ST candidates who have qualified on or after 1st January 1991 a concession of 5 percent of marks shall be given in the minimum eligibility marks

Course Code Title of the Courses Core/Electi

ve

L-T-P-C Faculty

First SemesterMSI C101 Research Methodology C 3-2-0-5 Guest FacultyMSI C102 Advance course on Computing C 3-2-0-5 P.ThangavelMSI E101 Selected Topics in Algorithms E 3-2-0-5 P.Thangavel/

G.F.MSI E102 Artificial Neural Networks E 3-2-0-5 P.Thangavel/

G.FMSI E103 Digital Image Processing E 3-2-0-5 P.Thangavel/

G.FMSI E104 Wireless Networks E 3-2-0-5 P.Thangavel/

G.FSecond SemesterMSI C103 Dissertation and Viva-voce C 6+15=21 P.Thangavel/

G.F.

Department of StatisticsM.Sc Actuarial Science (Proposed Syllabus for the academic year 2007 - 08)

A – CORE COURSESCourse Code

Title of the Course C/E/S L T P C

I SEMESTERMSI C 201 Probability Theory C 3 1 0 4

40

MSI C 202 Financial Mathematics – I C 3 1 0 4MSI C 203 Probability Distributions C 3 1 0 4MSI C 215 Principles and Practice of Insurance C 2 0 0 2

Elective 1 E 2 1 0 3

Elective 2 E 2 1 0 3

UOM S001 Soft Skill S 2

II SEMESTERMSI C 204 Survival Models C 3 1 0 4MSI C 205 Statistical Inference C 3 1 0 4MSI C 206 Financial Mathematics – II C 3 1 0 4MSI C 216 Life Contingencies – I C 3 1 0 4MSI C 207 Computational Laboratory - I C 0 0 2 2

Elective 3 E 2 1 0 3

Elective 4 E 2 1 0 3

UOM S002 Soft Skill S 2

III SEMESTERMSI C 209 Stochastic Modeling C 3 1 0 4MSI C 210 Risk Models C 3 1 0 4MSI C 217 Life Contingencies – II C 3 1 0 4MSI C 218 Financial Economics C 2 1 0 3

Elective 5 E 2 1 0 3UOM S003 Soft Skill S 2UOM I001 Internship S 2

IV SemesterMSI C 219 Joint Life and Pension Benefits C 3 1 0 4MSI C 212 Corporate Financial Management C 2 1 0 3MSI C 213 Computational Laboratory - II C 0 0 2 2MSI C 214 Project & Viva voce C 3 1 0 4

Elective 6 E 2 1 0 3UOM S004 Soft Skill S 2

B – ELECTIVE COURSES :

Course Code

Title of the Course L T P C

MSI E 201 Object oriented programming with C++ 3 0 0 3MSI E 202 Principles of Economics 3 0 0 3MSI E 204 Numerical Methods 3 0 0 3MSI E 205 Finance and Financial Reporting 3 0 0 3MSI E 207Resource optimization principles 3 0 0 3

41

MSI E 208 Data Analysis using R & SAS 1 0 2 3

42

Syllabi for various Courses of M.Sc. (Br. II(B)) Actuarial Science

MSI C201 PROBABILITY THEORY

UNIT 1 : Sample space – events. Random variables – distribution functions and its properties – moments – expectation – variance – conditional probability – Baye’s theorem – computational probabilities – simple problems from Industrial and Actuary.

UNIT 2 : Moment generating function – pgf – cumulant generating functions – evaluation of moment using these functions – functions of random variables – simple applications.

UNIT 3 : Characteristic functions – properties – inversion formulae – uniqueness theorem – moments problem – Levy Cramer theorems – simple problems.

UNIT 4 : Independence – pairwise and complete independence - convolution - conditional expectation - smoothing properties – Martingales – simple problems.

UNIT 5 : Laws of large numbers weak and strong law of large numbers – simple applications – central limit theorems (iid and id) – normal approximation – simple applications.

Books for Study and Reference :

Bhat, B.R. (1999) : Modern Probability Theory, 3rd ed. New Age International Pvt. Ltd., New Delhi.

Ash, R.B. (1972) : Real Analysis and Probability, Academic press, New York.Ross,Sheldon,M.(1984): A First Course in Probability, 2nd ed. McMillan, New York.Freund, JE (1998) : Mathematical Statistics, Prentice Hall International.

MSI C202 FINANCIAL MATHEMATICS - I

UNIT 1 : Rates of interest – Simple and Compound interest rates –Effective rate of interest - Accumulation and Present value of a single payment – Nominal rate of interest – Constant force of interest d - Relationships between these rates of interest - Accumulation and Present value of single payment using these rates of interest – accumulation and present value of a single payment using these symbols - when the force of interest is a function of t, d(t). Definition of A(t1, t2), A(t), u(t1, t2) and u(t). Expressing accumulation and present value of a single payment using these symbols - when the force of interest is a function of t, d(t).

UNIT 2 : Series of Payments(even and uneven) - Definition of Annuity(Examples in real life situation) – Accumulations and Present values of Annuities with level payments and where the payments and interest rates have same frequencies - Definition and Derivation of , , , , Definition of Perpetuity and derivation for and -Examples - Accumulations and Present values of Annuities where payments and interest rates have different frequencies. Definition

and derivation of , , ,

UNIT 3 : Increasing and Decreasing annuities – Definition and derivation for , and - Annuities

payable continuously - Definition and derivation of , , , - Annuities where payments are increasing

continuously and payable continuously – definition and derivation of , .

UNIT 4 : Loan schedules – Purchase price of annuities net of tax – Consumer credit transactions

UNIT 5 : Fixed interest securities – Evaluating the securities – Calculating yields – the effect of the term to redemption on the yield – optional redemption dates – Index linked Bonds – evaluation of annuities subject to Income Tax and capital gains tax.

Books for Study and Reference :

Institute of Actuaries ActEd. Study Materials.McCutcheon, J.J., Scott William, F. (1986) : An introduction to Mathematics of Finance,

London HeinemannButcher,M.V.,Nesbitt, Cecil,J. (1971) : Mathematics of compound interest, Ulrich’s Books.Bowers, Newton L.et al (1997):Actuarial Mathematics, Society of Actuaries, 2nd ed.

43

MSI C203 PROBABILITY DISTRIBUTIONS

UNIT 1 : Discrete distributions – Binomial – Poisson – Multinomial – Hyper geometric – Geometric – discrete uniform – their characteristics and simple applications.

UNIT 2 : Continuous distributions – Uniform - Normal – exponential – Gamma – Weibull – Pareto – lognormal – Laplace – logistic distributions – their characteristics and applications.

UNIT 3 : Bivariate and Multivariate Normal – Compound and truncated distributions – convolutions of distributions.

UNIT 4 : Sampling distributions t, c2 and F distributions and their interrelations and characteristics – order statistics and their distribution – distribution of sample and mid range.

UNIT 5 : Applications of multivariate – normal distributions – principal components analysis – discriminant analysis – factor analysis – cluster analysis – Canonical correlations.

Books for Study and Reference :Fruend, John, E. (1992) : Mathematical Statistics, 5th ed., Prentice Hall International.Forguson, T.S. (1967) : Mathematical Statistics, Academic Press, New York.Gibbons, J.D. (1985) : Non parametric Statistical Inference, Marcel Dekker, New York.Hogg,R.V. & Craig (1972): Introduction to Mathematical Statistics, 3rd ed., McGraw HillJohnson, R.A. and Wichern, D.W. (1982) : Applied Multivariate Statistical Analysis, 2nd ed., Prentice Hall,

Englewood Cliffs, New Jersey.Mood, A.M., Graybill, F.A., and Boes, D.C. (1974) : An introduction to the theory of

Statistics, 3rd ed. McGraw Hill Book companyRohatgi, V.K. and Ebsanes Saleh, A.K. Md. (2002) : An introduction to Probability and

Statistics, 2nd Ed., John Wiley & Sons, Inc., New York.

MSI C215 PRINCIPLES AND PRACTICE OF INSURANCE

UNIT 1 : Concept of Risk- The concept of Insurance.Classification of Insurance- Types of Life Insurance, Pure and Terms- Types of General Insurance, Insurance Act, Fire, Marine, Motor, Engineering, Aviation and Agricultural - Alternative classification- Insurance of Property, Pecuniary interest, liability and person. Distribution between Life and General Insurance.History of Insurance in general in India. Economic Principles of Insurance – Insurance regulatory and development Act.

UNIT 2 : Legal Principles of Insurance- The Indian Contract Act, 1872- insurable interest - Utmost Good faith- indemnity- subrogation – Contribution- Proximate Cause - Representations- Warranties- Conditions. Theory of rating- Actuarial principles- Mortality Tables- Physical and Moral Hazard. Risk appraisal- Risk Selection- Underwriting. Reinsurance- Concept and Methods.

UNIT 3 : Life insurance organisation : The Indian context. The distribution system, function of appointment and continuance of agency, remuneration to aents, trends in Life insurance distribution channels.Plans of Life Insurance – need levels, term life insurance increasing / decreasing term policy, whole life insurance, endowment insurance, money back endowment plan, marriage endowment plan, education annuity plan, children deferred assurance plans, annuities. Group insurance – nature of group insurance, types of group insurance, gratuity liability, group superannuating scheme, other group schemes, social security schemes. Other special need plan – industrial life insurance, salary saving scheme, disability plans – critical illness plans.

UNIT 4 : Application and acceptance – prospectus – proposal forms and other related documents, age proof, special reports. Policy document – need and format – preamble, operative clauses, proviso, schedule, attestation, conditions and privileges, alteration, duplicate policy.

UNIT 5 : Premium, premium calculation, Days of grace, Non-Forfeiture options, lapse and revival schemes. Assignment nominations loans – surrenders, foreclosures, Married Women’s property Act Policy, calculations. Policy claims, maturity claims, survival benefit payments, death claims, waiver of evidence of title, early claims, claim concession, presumption of death, Accident Benefit and Disability Benefit , settlement options, Valuations and Bonus, distribution of surplus. Types of re-insurance, exchange control regulations, payment of premia, payment of claims etc.

Books for study and Reference :Neill, Alistair, Heinemann, (1977) : Life contingencies.Gerber, Hans, U. (1997) : Life insurance mathematics, Springer, Swiss Association of

Actuaries.Booth,Philip,M.et al(1999):Modern Actuarial theory and practice, Chapman & Hall.Daykin,Chris,D. et al(1994): Practical risk theory for Actuaries, Chapman and Hall.

44

Panjer, Harry,H. (1998) : Financial economics with applications to investments, Insurance and pensions. The Actuarial foundation.

MSI C204 SURVIVAL MODELS

UNIT 1 : Concept of Survival Models

UNIT 2 : Estimation procedures of Life time Distributions – Cox Regression model – Nelson and Aalen Estimates

UNIT 3 : Two state Markov Model

UNIT 4 : Multi state Markov Models - Statistical Models of transfers between multiple states, Derivation of relationships between probabilities of transfer and transition intensities. Maximum Likelihood Estimators(MLE) for the transition intensities in models of transfers between states with piecewise constant transition intensities.

UNIT 5 : Binomial and Poisson models of mortality – MLE for probability of death – Comparison with Multi state models.

Books for Study and Reference:Institute of Actuaries Acted. Study Materials.Neill, Allistair (1977) : Life contingencies, Heinemann. Elandt-Johnson, Regina C; Johnson, Norman L., 2nd ed. (1999) : Survival Models and

data analysis, John Wiley.Marubini, Ettore, Valsecchi, Marai Grazia, Emmerson, M. (1995) : Analysis of Survival

data from Clinical Trials and observation of studies, John Wiley.

MSI C205 STATISTICAL INFERENCE

UNIT 1 : Estimation Methods : Properties of a good estimator – unbiasedness – efficiency – Cramer Rao bound – sufficiency – Methods of estimation – Methods of moments – Maximum likelihood method – minimum chisquare – method of least squares and their properties.

UNIT 2 : Neyman Pearson theory of testing of hypothesis UMP and UMPU tests – chisquare tests – locally most powerful tests – large sample tests – testing linear hypothesis.

UNIT 3 : Non parametric inference :The Wilcoxon signed rank test – The Mann-Whitney – Wilcoxon Rank sum test – the runs test – chi-squire test of goodness of fit test – Kolmogorov-Smirnov goodness of fit test – Kruskal Wallies test – Friedman test .

UNIT 4 : Confidence sets and intervals – exact and large sample confidence intervals – shortest confidence intervals.

UNIT 5 : Elements of Bayesian inference – Bayes theorem – prior and posterior distribution – conjugate and Jeffreys priors – Baysian point estimation – minimax estimation – loss function – conflux loss functions – Bayesian interval estimation and testing of hypothesis.

Books for Study and Reference :

Rohatgi, V.K. and Ebsanes Saleh, A.K. Md. (2002) : An introduction to Probability and Statistics, 2nd Ed., John Wiley & Sons, Inc.

Mood, A.M. Graybill, F.A. and Boes, D.C. (1974) : An introduction to the theory of Statistics, 3rd Ed., McGraw Hill Book Company.

MSI C206 FINANCIAL MATHEMATICS – II

UNIT 1 : Investment Project Appraisal – Discounted Cash flow techniques.

UNIT 2 : Investment and Risk characteristics of different types of Assets for Investment for investment purposes

UNIT 3 : Delivery price and the value of a Forward contract using arbitrage free pricing methods

UNIT 4 : Term structures of interest rates

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UNIT 5 : Simple Stochastic interest rate Models

Books for Study and Reference :

Rohatgi, V.K. and Ebsanes Saleh, A.K. Md. (2002) : An introduction to Probability and Statistics, 2nd Ed., John Wiley & Sons, Inc.

Mood, A.M. Graybill, F.A. and Boes, D.C. (1974) : An introduction to the theory of Statistics, 3rd Ed., McGraw Hill Book Company.

MSI C216 LIFE CONTINGENCIES – I

UNIT 1 : Exposed to risk

UNIT 2 : Assurance functions - Annuity functions

UNIT 3 : Life Tables

UNIT 4 : (i) Estimations of EPV’s of Assurance and Annuity functions (ii) Net premiums & provisions

UNIT 5 : Variable benefits & with profit policies

Books for Study and Reference:Institute of Actuaries Acted. Study Materials.Neill, Allistair (1977) : Life contingencies, Heinemann.Gerber, Hans U. (1997) : Life insurance Mathematics, Springer, Swiss Association of

Actuaries, 3rd edition.

MSI C207 COMPUTATIONAL LABORATORY – I

Objectives : The implementation of standard numerical algorithms are mastered and results are calculated with precision. The strengths and limits of each algorithm are understood as well as which technique is most suitable for a given problem. Lab time is used to master code writing in C++ .

Mathematical Exercises :

1. Algebraic equations 1.1. Bisections method1.2. Secant method1.3. Newton-Raphson method

2. System of linear equations 2.1 Gaussian Elimination2.2 Gauss-Seidal Iteration2.3 Gauss- Jordan Iteration2.4 Matrix operations

3. Interpolation and curve Fitting1.1 Lagrange Interpolation1.2 Newton polynomials1.3 Straight line fitting1.4 Curve fitting

4. Numerical differentiation and integration4.1 Differentiation4.2 Trapezoidal and Simpson’s 1/3 rule

5. Solution to differential equations5.1 Euler method5.2 Runge – Kutta method of order 25.3 Runge – Kutta method of order 35.4 Predictor – corrector method

6. Statistical Methods6.1 Formation of frequency distribution

C++ Programming Exercises Statistical Exercises

46

6.2 Calculation of moments – mean and variance6.3 Computation of correlations and regression coefficients6.4 Fitting and probability distributions6.5 ANOVA (one-way, two-way)6.6 Tests of significance based on t, c2 and F.

7. Inference7.1 Method of moments7.2 Method of maximum likelihood7.3 Confidence intervals based on t, c2 and F.7.4 MP test.

MSI C209 STOCHASTIC MODELING

UNIT 1 : Stochastic process : Definitions and classification (based on state space and time) of Stochastic Processes – various types of stochastic processes.Markov chains : n-step TPM – classification states canonical representation of TPM – finite MC with transient states – No Claim Discount policy – Accident Proneness.

UNIT 2 : Irreducible Markov Chain with ergodic states : Transient and limiting behaviour – first passage and related results – applied Markov chains – industrial mobility of labor – Educational advancement – Human resource management – term structure – income determination under uncertainty – A Markov decision process.

UNIT 3 : Simple Markov processes : Markov processes – general properties – Poisson processes – Birth problem – death problem – birth and death problem – limiting distribution. Flexible manufacturing systems – stochastic model for social networks – recovery, relapse and death due to disease – Health, sickness and Death model – Martial status.

UNIT 4 : Stationary processes and time series – Stochastic models for time series – the auto regressive process – moving average process – mixed auto regressive moving average processes – time series analysis in the time domain – Box-Jenkins model for forcasting.

UNIT 5 : Brownian motion and other Markov processes – Hitting times – maximum variable – arc sine laws – variations of Brownian motion – stochastic integral – Ito and Levy processes – applications to Actuarial Science.

Books for Study and Reference :

Bhat, U.N. and Miller, G.K. (2002) : Elements of applied stochastic processes 3rd ed. Wiley Inter, New York.

Brzezniak, Z and Zastawniak, T. (1998) : Basic Stochastic Processes : A course through Exercises, Springer, New York.

Grimmett, G., Stirzaker, D. (1992) : Probability and Random Processes, Oxford University Press.

Kulkarni, V.G. (1995) : Modelling and Analysis of Stochastic Systems, Thomson Science and Professional.

Ross, S.M.(1996): Stochastic processes, John Wiley & Sons, Inc., New York Institute of Actuaries : ActEd Study materials

MSI C210 RISK MODELS

UNIT 1 : Concept of Decision theory and its applications – Concepts of Bayesian statistics – Calculation of Bayesian Estimators.

47

UNIT 2 : Calculate probabilities and moments of loss distributions both with and without simple reinsurance arrangements – Construct risk models appropriate to short term insurance contracts and calculate MGFs and moments for the risk models both with and without simple reinsurance arrangements. - Calculate and approximate the aggregate claim distribution for short term insurance contracts.

UNIT 3 : Explain the concept of ruin for a risk model – Calculate the adjustment coefficients and state Lundberg’s inequality – Describe the effect on the probability of ruin of changing parameter values and of simple reinsurance arrangements.

UNIT 4 : Describe and apply the fundamental concepts of credibility theory – Describe and apply the fundamental concepts of simple experience rating systems – Describe and apply techniques for analyzing a delay(or run-off) triangle and projecting the ultimate position

UNIT 5 : Explain the fundamental concepts of a generalized linear model(GLM), and describe how a GLM may be applied.

Books for Study and Reference :

Institute of Actuaries Acted. Study Materials.Hossack, Ian B; Pollard, John H; Zenhwirth, Benjamin (1999) : Introductory Statistics

with applications in General Insurance, Cambridge University Press. 2nd ed.Klugman, Stuart A. et al. (1998) : Loss Models: from data to decisions, John WileyDaykin Chris, D; Pentikainen, Teivo; Pesonen, Martti (1994) : Practical Risk theory for

Actuaries, Chapman & Hall.

MSI C217 LIFE CONTINGENCIES – II

UNIT 1 : Gross premiums and provisions

UNIT 2 : Profit Testing

UNIT 3 : Determining provisions using profit testing

UNIT 4 : Factor affecting mortality & selections

UNIT 5 : Single figure indices

Books for Study and Reference:Institute of Actuaries ActEd. Study Materials.Benjamin, B. Pollard, J.H. (1993) : The analysis of mortality and other actuarial

statistics, Faculty and Institute of Actuaries, 3rd ed. Gerber, Hans U. (1997) : Life insurance Mathematics, Springer, Swiss Association of

Actuaries, 3rd ed. Booth, Philip M et al., (1999) : Modern Actuarial Theory and Practice, Chapman &

Hall. Bowers, Newton L.et al (1997):Actuarial Mathematics, Society of Actuaries, 2nd ed.

MSI C218 FINANCIAL ECONOMICS

UNIT 1: Introduction to Financial Economics: - Recap of Utility Theory. The Efficient Markets Hypothesis: The three forms of EMH - The Evidence for or against each form of EMH.

UNIT 2: Measures of Investment Risk: - Measures of Risk - Relationship between Risk measures and Utility Functions.

UNIT 3: Portfolio Theory: - Portfolio Theory - Benefits of Diversification.

UNIT 4: Models of Asset Returns: - Multifactor Models - The Single Index Model.

UNIT 5: Asset Pricing Models: - The Capital Asset Pricing Models (CAPM) – Limitations of CAPM – Arbitrage Pricing Theory (APT).

Books for Study and Reference :

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Institute of Actuaries ActEd , CT8 Study material.Panjer, Harry, H. (1998) : Financial economics : with applications to investments,

insurance and pensions. The Actuarial foundations.

MSI C219 JOINT LIFE AND PENSION BENEFITSUNIT 1 : Simple annuities and assurances involving two lives.

UNIT 2 : Contingent and reversionary benefits

UNIT 3 : Competing risks

UNIT 4 : Multiple decrement tables

UNIT 5 : Pension benefits

Books for Study and Reference:Institute of Actuaries ActEd. Study Materials.Benjamin, B. Pollard, J.H. (1993) : The analysis of mortality and other actuarial

statistics, Faculty and Institute of Actuaries, 3rd ed. Booth, Philip M et al., (1999) : Modern Actuarial Theory and Practice, Chapman &

Hall. Gerber, Hans U. (1997) : Life insurance Mathematics, Springer, Swiss Association of

Actuaries, 3rd edition

MSI C212 CORPORATE FINANCIAL MANAGEMENT

UNIT 1 : Foundations of Finance : Time value of Money – NPV, IRR, and other Measures – Valuation of Common Stocks and Bonds.

UNIT 2 : Investment Analysis : Modern theory of Finance – Capital Budgeting Decision Rule – Capital Budgeting and Cash Flow Analysis – Capital Budgeting and Risk.

UNIT 3 : Variance Analysis – Importance of variance analysis – Material variance, labour variance, overhead variance. Working capital management – Factors determining working capital – Calculation of working capital.

UNIT 4 : Financial Planning : Financial Statements and Ratio Analysis – Short-term Financial Decisions – Long-term Financial Decisions.

UNIT 5 : Special Topics : Mergers and Acquisitions and Corporate Governance – Options and Corporate Finance.

Books for Study and Reference :Brealey, Myers and Marcus : Fundamentals of Corporate Finance, McGraw Hill.Ross, Westerfield and Jordan : Fundamentals of Corporate Finance, Tata McGraw Hill.Van Home and Wachowicz : Fundamentals of Financial Management, Prentice Hall

India.

MSI C213 COMPUTATIONAL LABORATORY – IIObjectives :

To provide exposure to Mathematical / Statistical software focusing more on writing source codes.

To analyse the given data by identifying appropriate tools.

Mathematical and Statistical Packages Exercises. S Plus/ SAS/ MAPLE/ MATHEMATICA/ MATLAB

1. Data Analysis : Identifying the statistical tool and analysing the data using the appropriate tools.(S PLUS/ SAS)

2. Symbolic manipulation using MAPLE/ MATHEMATICAExercises based on the subjects taught in III & IV semesters. (ie. Survival Analysis – Stochastic Models etc.)

3. Simulation study depending upon the requirement of the problem. (MATLAB)

49

MSI C214 PROJECT & VIVA VOCE

Objectives : To provide written, oral and visual presentation skills To develop team work.

Course Outline : Based on the interest of the students, they can choose their team and seminar topic. It can also an individual work. During the term, students will meet periodically the faculty to discuss different stages of the seminar. They are required to give three seminar presentations.

Project Work/ Internship :

Objectives : To develop student’s abilities to solve applied industrial and actuarial problems in a longer time frame than in usual in other courses. Students will learn how to search for known results and techniques related the project work. The students will present their project results as a written document and verbally.

Prerequisite : Completion of the course duration of first two semesters.

Course Outline :

The faculty will propose an array of problems in industrial / actuarial studies. Students may choose a problem from this list or propose of their own provided a faculty member / Guide approves it. This work may also be carried out as an internship programme.

On completion of the project work, each student is expected to

Submit a written document describing the results, mathematical developments, background material, bibliographical search etc.

Present orally in a seminar setting of the work done in the thesis Submit the software (if relevant) with appropriate documentation.

The students will meet regularly with the project guide / adviser to work out problems that appear

and adjust the goals and time frame accordingly.

MSI E201 OBJECT ORIENTED PROGRAMMING WITH C++

UNIT 1 : Principles of object oriented programming – beginning with C++ - Token, Expressions and Control structures.

UNIT 2 : Functions in C++ - Classes and objects.

UNIT 3 : Constructors and Destructors – operator overloading and type conversions

UNIT 4 : Inheritance : Extending classes – Pointers, Virtual Functions and Polymorphism.

UNIT 5 : Console I/O operations – working with files – object oriented systems development – Templates and Exception handling.

Books for Study and Reference :Balagurusamy (1999) : Object oriented programming with C++, Tata McGraw Hill

Company Ltd., New Delhi, 16th reprinting.Hubbard, J.R. (2000) : Programming with C++ 2nd ed., McGraw Hill, New York.

MSI E202 PRINCIPLES OF ECONOMICS

UNIT 1 : Market Mechanism – Supply and Demand interaction – Determination of equilibrium Elasticity of demand and Supply – Rational utility and consumption choice – Insurance system and its impact on Welfare.

UNIT 2 : Costs Revenue and output – Market structure – short and long run equilibrium in different markets – perfect competition, Monopoly, Monopolistic competition.

50

UNIT 3 : Macro Economics – Concepts of GDP, GNP, NNP – methods of calculating National Income – problems – difficulties and uses of National Income Analysis. Propensity to consume – multiplier – determinants of consumption.

UNIT 4 : Monetary and Fiscal policy – Government intervention – financial markets – exchange rates – International trade – Balance of payments.

UNIT 5 : Inflation types – interest rate and exchange rate – types of unemployment – public sector finances in an industrial economy.

Books for study and Reference :Stonier and Hague : Economic TheoryKovtsoyiannis : Modern micro economics ELBS publications.Samuelson Paul & Norhaus William (1998) : Economics, McGraw Hill.Allen, R.G.D. : Mathematical analysis for Economics, Macmillan.Panjer, Harry, H.(ed)(1998) : Financial Economics with applications to investments, Insurance and pension. The Actuarial foundation

MSI E204 NUMERICAL METHODS

UNIT 1 : Numerical coumputing and computers – Solving non-linear equations.

UNIT 2 : Solving set of equations.

UNIT 3 : Interpolation and curve fitting.

UNIT 4 : Numerical differentiation and Numerical integration.

UNIT 5 : Numerical solution of ordinary differential equations.

Books for Study and Reference :Gerald, C.F. and Wheatley, P.O. (1994) : Applied Numerical Analysis, Addison Wesley,

New York, 5th Ed.Press, W.B., Flannery, S. Teuddsky and Vetterling, W. (1989) : Numerical Recipes in C :

The art of Scientific computing. Rev. 1st ed., Cambridge University Press.Rice, John, R. (1983) : Numerical Methods, Software and Analysis, McGraw Hill, New York.Atkinson, K.E. (1978) : An introduction to Numerical Analysis, Wiley & Sons, New York.Sastry, S.S. (1987) : Introductory methods of numerical analysis, Prentice Hall of India,

New Delhi, (10th printing).

MSI E205 FINANCE AND FINANCIAL REPORTING

UNIT 1 : Introduction to Finance – Functions of Financial Management – Scope – Organisation – Sources of funds – Long term – Medium term and Short term – Financial risks.

UNIT 2 : Company Management – Types of business entity – pros and cons of limited company – legal documentation – corporate and personal taxation.

UNIT 3 : Capital structure – Net Income approach Net operating Income approach – M M approach Traditional approach – average and personal tax of the investors – concept of cost of capital – factors affecting cost of capital – specific and overall cost of capital.

UNIT 4 : Dividend decision and valuation of the firm – Determinants and constraints of a dividend policy – Financial Institution – IDBI, ICICI, IFCI, UTI, Commercial Banks, Insurance companies etc.

UNIT 5 : Financial reporting – Accounting principles – types – basic financial statement – kinds of reports – Nature of reports – guiding principles of reporting – necessary steps for good reporting.

Books for Study and Reference :Samuels, J.M., Wilkes, F.M., Brayshaw, R.E. (1995) : Management of company finance,

International Thomson, 6th ed.Brealey, Richard, A. (1999) : Principles of Corporate finance, McGraw Hill, 6th ed.Holmes, Geoffrey, Sugden, Alan (1999) : Interpreting company reports and accounts,

Prentice Hall, 7th ed.Pandey, I.M. : Financial Management.

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Prasannachandra : Financial ManagementKuchhal : Financial ManagementMoshal : Management AccountingInstitute of Actuaries ActEd , Study Material :

MSI E207 RESOURCE OPTIMIZATION PRINCIPLES

UNIT 1 : Linear programming problems - model formulation and graphical solution – various types of solutions – simplex method of solving linear programming –duality principles – dual simplex method.

UNIT 2 : Artificial variable techniques Big M method – two phase method – assignment problem – transportation problem – MODI method of finding optimal solutions.

UNIT 3 : Sequencing problem – replacement problems – game theory – zero sum games – graphical method – solution of games by LPP.

UNIT 4 : Decision analysis – components of decision making – decision making without probabilities – maximum – minimax regret – Hurwicz and equal likelihood criterion – decision making with probabilities – expected value – expected opportunity loss criterion.

UNIT 5 : Network flow models – shortest route problem – project management – the CPM and PERT Networks.

Books for Study and Reference :

Sharma, J.K. (1997) : Operations Research, Theory and applications, Macmillan.Taha, H.A. (1996) : Operations Research, 5th edition, Prentice Hall of India, New York.

MSI E208 DATA ANALYSIS USING R & SAS Prerequisite: compulsory knowledge in Advanced Statistical Inference and Survival Analysis

UNIT 1 : Graphs, Diagrams , Descriptive Statistics and Data Exploration Techniques

UNIT 2 : Bivariate Data Analysis, Multivariate Data Analysis

UNIT 3 : Non parametric Tests

UNIT 4 : Statistical Models ,Time series Analysis

UNIT 5 : Simulation Techniques

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Department of StatisticsM.Sc Actuarial Science (Proposed Syllabus for the academic year 2007 - 08)

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A – CORE COURSESCourse Code

Title of the Course C/E/S L T P C

I SEMESTERMSI C 201 Probability Theory C 3 1 0 4MSI C 202 Financial Mathematics – I C 3 1 0 4MSI C 203 Probability Distributions C 3 1 0 4MSI C 215 Principles and Practice of Insurance C 2 0 0 2

Elective 1 E 2 1 0 3

Elective 2 E 2 1 0 3

UOM S001 Soft Skill S 2

II SEMESTERMSI C 204 Survival Models C 3 1 0 4MSI C 205 Statistical Inference C 3 1 0 4MSI C 206 Financial Mathematics – II C 3 1 0 4MSI C 216 Life Contingencies – I C 3 1 0 4MSI C 207 Computational Laboratory - I C 0 0 2 2

Elective 3 E 2 1 0 3

Elective 4 E 2 1 0 3

UOM S002 Soft Skill S 2

III SEMESTERMSI C 209 Stochastic Modeling C 3 1 0 4MSI C 210 Risk Models C 3 1 0 4MSI C 217 Life Contingencies – II C 3 1 0 4MSI C 218 Financial Economics C 2 1 0 3

Elective 5 E 2 1 0 3UOM S003 Soft Skill S 2UOM I001 Internship S 2

IV SemesterMSI C 219 Joint Life and Pension Benefits C 3 1 0 4MSI C 212 Corporate Financial Management C 2 1 0 3MSI C 213 Computational Laboratory - II C 0 0 2 2MSI C 214 Project & Viva voce C 3 1 0 4

Elective 6 E 2 1 0 3UOM S004 Soft Skill S 2

B – ELECTIVE COURSES :

Course Code

Title of the Course L T P C

MSI E 201 Object oriented programming with C++ 3 0 0 3

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MSI E 202 Principles of Economics 3 0 0 3MSI E 204 Numerical Methods 3 0 0 3MSI E 205 Finance and Financial Reporting 3 0 0 3MSI E 207Resource optimization principles 3 0 0 3MSI E 208 Data Analysis using R & SAS 1 0 2 3

55

Syllabi for various Courses of M.Sc. (Br. II(B)) Actuarial Science

MSI C201 PROBABILITY THEORY

UNIT 1 : Sample space – events. Random variables – distribution functions and its properties – moments – expectation – variance – conditional probability – Baye’s theorem – computational probabilities – simple problems from Industrial and Actuary.

UNIT 2 : Moment generating function – pgf – cumulant generating functions – evaluation of moment using these functions – functions of random variables – simple applications.

UNIT 3 : Characteristic functions – properties – inversion formulae – uniqueness theorem – moments problem – Levy Cramer theorems – simple problems.

UNIT 4 : Independence – pairwise and complete independence - convolution - conditional expectation - smoothing properties – Martingales – simple problems.

UNIT 5 : Laws of large numbers weak and strong law of large numbers – simple applications – central limit theorems (iid and id) – normal approximation – simple applications.

Books for Study and Reference :

Bhat, B.R. (1999) : Modern Probability Theory, 3rd ed. New Age International Pvt. Ltd., New Delhi.

Ash, R.B. (1972) : Real Analysis and Probability, Academic press, New York.Ross,Sheldon,M.(1984): A First Course in Probability, 2nd ed. McMillan, New York.Freund, JE (1998) : Mathematical Statistics, Prentice Hall International.

MSI C202 FINANCIAL MATHEMATICS - I

UNIT 1 : Rates of interest – Simple and Compound interest rates –Effective rate of interest - Accumulation and Present value of a single payment – Nominal rate of interest – Constant force of interest d - Relationships between these rates of interest - Accumulation and Present value of single payment using these rates of interest – accumulation and present value of a single payment using these symbols - when the force of interest is a function of t, d(t). Definition of A(t1, t2), A(t), u(t1, t2) and u(t). Expressing accumulation and present value of a single payment using these symbols - when the force of interest is a function of t, d(t).

UNIT 2 : Series of Payments(even and uneven) - Definition of Annuity(Examples in real life situation) – Accumulations and Present values of Annuities with level payments and where the payments and interest rates have same frequencies - Definition and Derivation of , , , , Definition of Perpetuity and derivation for and -Examples - Accumulations and Present values of Annuities where payments and interest rates have different frequencies. Definition

and derivation of , , ,

UNIT 3 : Increasing and Decreasing annuities – Definition and derivation for , and - Annuities

payable continuously - Definition and derivation of , , , - Annuities where payments are increasing

continuously and payable continuously – definition and derivation of , .

UNIT 4 : Loan schedules – Purchase price of annuities net of tax – Consumer credit transactions

UNIT 5 : Fixed interest securities – Evaluating the securities – Calculating yields – the effect of the term to redemption on the yield – optional redemption dates – Index linked Bonds – evaluation of annuities subject to Income Tax and capital gains tax.

Books for Study and Reference :

Institute of Actuaries ActEd. Study Materials.McCutcheon, J.J., Scott William, F. (1986) : An introduction to Mathematics of Finance,

London HeinemannButcher,M.V.,Nesbitt, Cecil,J. (1971) : Mathematics of compound interest, Ulrich’s Books.Bowers, Newton L.et al (1997):Actuarial Mathematics, Society of Actuaries, 2nd ed.

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MSI C203 PROBABILITY DISTRIBUTIONS

UNIT 1 : Discrete distributions – Binomial – Poisson – Multinomial – Hyper geometric – Geometric – discrete uniform – their characteristics and simple applications.

UNIT 2 : Continuous distributions – Uniform - Normal – exponential – Gamma – Weibull – Pareto – lognormal – Laplace – logistic distributions – their characteristics and applications.

UNIT 3 : Bivariate and Multivariate Normal – Compound and truncated distributions – convolutions of distributions.

UNIT 4 : Sampling distributions t, c2 and F distributions and their interrelations and characteristics – order statistics and their distribution – distribution of sample and mid range.

UNIT 5 : Applications of multivariate – normal distributions – principal components analysis – discriminant analysis – factor analysis – cluster analysis – Canonical correlations.

Books for Study and Reference :Fruend, John, E. (1992) : Mathematical Statistics, 5th ed., Prentice Hall International.Forguson, T.S. (1967) : Mathematical Statistics, Academic Press, New York.Gibbons, J.D. (1985) : Non parametric Statistical Inference, Marcel Dekker, New York.Hogg,R.V. & Craig (1972): Introduction to Mathematical Statistics, 3rd ed., McGraw HillJohnson, R.A. and Wichern, D.W. (1982) : Applied Multivariate Statistical Analysis, 2nd ed., Prentice Hall,

Englewood Cliffs, New Jersey.Mood, A.M., Graybill, F.A., and Boes, D.C. (1974) : An introduction to the theory of

Statistics, 3rd ed. McGraw Hill Book companyRohatgi, V.K. and Ebsanes Saleh, A.K. Md. (2002) : An introduction to Probability and

Statistics, 2nd Ed., John Wiley & Sons, Inc., New York.

MSI C215 PRINCIPLES AND PRACTICE OF INSURANCE

UNIT 1 : Concept of Risk- The concept of Insurance.Classification of Insurance- Types of Life Insurance, Pure and Terms- Types of General Insurance, Insurance Act, Fire, Marine, Motor, Engineering, Aviation and Agricultural - Alternative classification- Insurance of Property, Pecuniary interest, liability and person. Distribution between Life and General Insurance.History of Insurance in general in India. Economic Principles of Insurance – Insurance regulatory and development Act.

UNIT 2 : Legal Principles of Insurance- The Indian Contract Act, 1872- insurable interest - Utmost Good faith- indemnity- subrogation – Contribution- Proximate Cause - Representations- Warranties- Conditions. Theory of rating- Actuarial principles- Mortality Tables- Physical and Moral Hazard. Risk appraisal- Risk Selection- Underwriting. Reinsurance- Concept and Methods.

UNIT 3 : Life insurance organisation : The Indian context. The distribution system, function of appointment and continuance of agency, remuneration to aents, trends in Life insurance distribution channels.Plans of Life Insurance – need levels, term life insurance increasing / decreasing term policy, whole life insurance, endowment insurance, money back endowment plan, marriage endowment plan, education annuity plan, children deferred assurance plans, annuities. Group insurance – nature of group insurance, types of group insurance, gratuity liability, group superannuating scheme, other group schemes, social security schemes. Other special need plan – industrial life insurance, salary saving scheme, disability plans – critical illness plans.

UNIT 4 : Application and acceptance – prospectus – proposal forms and other related documents, age proof, special reports. Policy document – need and format – preamble, operative clauses, proviso, schedule, attestation, conditions and privileges, alteration, duplicate policy.

UNIT 5 : Premium, premium calculation, Days of grace, Non-Forfeiture options, lapse and revival schemes. Assignment nominations loans – surrenders, foreclosures, Married Women’s property Act Policy, calculations. Policy claims, maturity claims, survival benefit payments, death claims, waiver of evidence of title, early claims, claim concession, presumption of death, Accident Benefit and Disability Benefit , settlement options, Valuations and Bonus, distribution of surplus. Types of re-insurance, exchange control regulations, payment of premia, payment of claims etc.

Books for study and Reference :Neill, Alistair, Heinemann, (1977) : Life contingencies.Gerber, Hans, U. (1997) : Life insurance mathematics, Springer, Swiss Association of

Actuaries.Booth,Philip,M.et al(1999):Modern Actuarial theory and practice, Chapman & Hall.Daykin,Chris,D. et al(1994): Practical risk theory for Actuaries, Chapman and Hall.

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Panjer, Harry,H. (1998) : Financial economics with applications to investments, Insurance and pensions. The Actuarial foundation.

MSI C204 SURVIVAL MODELS

UNIT 1 : Concept of Survival Models

UNIT 2 : Estimation procedures of Life time Distributions – Cox Regression model – Nelson and Aalen Estimates

UNIT 3 : Two state Markov Model

UNIT 4 : Multi state Markov Models - Statistical Models of transfers between multiple states, Derivation of relationships between probabilities of transfer and transition intensities. Maximum Likelihood Estimators(MLE) for the transition intensities in models of transfers between states with piecewise constant transition intensities.

UNIT 5 : Binomial and Poisson models of mortality – MLE for probability of death – Comparison with Multi state models.

Books for Study and Reference:Institute of Actuaries Acted. Study Materials.Neill, Allistair (1977) : Life contingencies, Heinemann. Elandt-Johnson, Regina C; Johnson, Norman L., 2nd ed. (1999) : Survival Models and

data analysis, John Wiley.Marubini, Ettore, Valsecchi, Marai Grazia, Emmerson, M. (1995) : Analysis of Survival

data from Clinical Trials and observation of studies, John Wiley.

MSI C205 STATISTICAL INFERENCE

UNIT 1 : Estimation Methods : Properties of a good estimator – unbiasedness – efficiency – Cramer Rao bound – sufficiency – Methods of estimation – Methods of moments – Maximum likelihood method – minimum chisquare – method of least squares and their properties.

UNIT 2 : Neyman Pearson theory of testing of hypothesis UMP and UMPU tests – chisquare tests – locally most powerful tests – large sample tests – testing linear hypothesis.

UNIT 3 : Non parametric inference :The Wilcoxon signed rank test – The Mann-Whitney – Wilcoxon Rank sum test – the runs test – chi-squire test of goodness of fit test – Kolmogorov-Smirnov goodness of fit test – Kruskal Wallies test – Friedman test .

UNIT 4 : Confidence sets and intervals – exact and large sample confidence intervals – shortest confidence intervals.

UNIT 5 : Elements of Bayesian inference – Bayes theorem – prior and posterior distribution – conjugate and Jeffreys priors – Baysian point estimation – minimax estimation – loss function – conflux loss functions – Bayesian interval estimation and testing of hypothesis.

Books for Study and Reference :

Rohatgi, V.K. and Ebsanes Saleh, A.K. Md. (2002) : An introduction to Probability and Statistics, 2nd Ed., John Wiley & Sons, Inc.

Mood, A.M. Graybill, F.A. and Boes, D.C. (1974) : An introduction to the theory of Statistics, 3rd Ed., McGraw Hill Book Company.

MSI C206 FINANCIAL MATHEMATICS – II

UNIT 1 : Investment Project Appraisal – Discounted Cash flow techniques.

UNIT 2 : Investment and Risk characteristics of different types of Assets for Investment for investment purposes

UNIT 3 : Delivery price and the value of a Forward contract using arbitrage free pricing methods

UNIT 4 : Term structures of interest rates

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UNIT 5 : Simple Stochastic interest rate Models

Books for Study and Reference :

Rohatgi, V.K. and Ebsanes Saleh, A.K. Md. (2002) : An introduction to Probability and Statistics, 2nd Ed., John Wiley & Sons, Inc.

Mood, A.M. Graybill, F.A. and Boes, D.C. (1974) : An introduction to the theory of Statistics, 3rd Ed., McGraw Hill Book Company.

MSI C216 LIFE CONTINGENCIES – I

UNIT 1 : Exposed to risk

UNIT 2 : Assurance functions - Annuity functions

UNIT 3 : Life Tables

UNIT 4 : (i) Estimations of EPV’s of Assurance and Annuity functions (ii) Net premiums & provisions

UNIT 5 : Variable benefits & with profit policies

Books for Study and Reference:Institute of Actuaries Acted. Study Materials.Neill, Allistair (1977) : Life contingencies, Heinemann.Gerber, Hans U. (1997) : Life insurance Mathematics, Springer, Swiss Association of

Actuaries, 3rd edition.

MSI C207 COMPUTATIONAL LABORATORY – I

Objectives : The implementation of standard numerical algorithms are mastered and results are calculated with precision. The strengths and limits of each algorithm are understood as well as which technique is most suitable for a given problem. Lab time is used to master code writing in C++ .

Mathematical Exercises :

8. Algebraic equations 8.1. Bisections method8.2. Secant method8.3. Newton-Raphson method

9. System of linear equations 2.1 Gaussian Elimination2.2 Gauss-Seidal Iteration2.5 Gauss- Jordan Iteration2.6 Matrix operations

10. Interpolation and curve Fitting3.1 Lagrange Interpolation3.2 Newton polynomials3.3 Straight line fitting3.4 Curve fitting

11. Numerical differentiation and integration4.3 Differentiation4.4 Trapezoidal and Simpson’s 1/3 rule

12. Solution to differential equations5.5 Euler method5.6 Runge – Kutta method of order 25.7 Runge – Kutta method of order 35.8 Predictor – corrector method

13. Statistical Methods6.7 Formation of frequency distribution

C++ Programming Exercises Statistical Exercises

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6.8 Calculation of moments – mean and variance6.9 Computation of correlations and regression coefficients6.10Fitting and probability distributions6.11ANOVA (one-way, two-way)6.12Tests of significance based on t, c2 and F.

14. Inference7.5 Method of moments7.6 Method of maximum likelihood7.7 Confidence intervals based on t, c2 and F.7.8 MP test.

MSI C209 STOCHASTIC MODELING

UNIT 1 : Stochastic process : Definitions and classification (based on state space and time) of Stochastic Processes – various types of stochastic processes.Markov chains : n-step TPM – classification states canonical representation of TPM – finite MC with transient states – No Claim Discount policy – Accident Proneness.

UNIT 2 : Irreducible Markov Chain with ergodic states : Transient and limiting behaviour – first passage and related results – applied Markov chains – industrial mobility of labor – Educational advancement – Human resource management – term structure – income determination under uncertainty – A Markov decision process.

UNIT 3 : Simple Markov processes : Markov processes – general properties – Poisson processes – Birth problem – death problem – birth and death problem – limiting distribution. Flexible manufacturing systems – stochastic model for social networks – recovery, relapse and death due to disease – Health, sickness and Death model – Martial status.

UNIT 4 : Stationary processes and time series – Stochastic models for time series – the auto regressive process – moving average process – mixed auto regressive moving average processes – time series analysis in the time domain – Box-Jenkins model for forcasting.

UNIT 5 : Brownian motion and other Markov processes – Hitting times – maximum variable – arc sine laws – variations of Brownian motion – stochastic integral – Ito and Levy processes – applications to Actuarial Science.

Books for Study and Reference :

Bhat, U.N. and Miller, G.K. (2002) : Elements of applied stochastic processes 3rd ed. Wiley Inter, New York.

Brzezniak, Z and Zastawniak, T. (1998) : Basic Stochastic Processes : A course through Exercises, Springer, New York.

Grimmett, G., Stirzaker, D. (1992) : Probability and Random Processes, Oxford University Press.

Kulkarni, V.G. (1995) : Modelling and Analysis of Stochastic Systems, Thomson Science and Professional.

Ross, S.M.(1996): Stochastic processes, John Wiley & Sons, Inc., New York Institute of Actuaries : ActEd Study materials

MSI C210 RISK MODELS

UNIT 1 : Concept of Decision theory and its applications – Concepts of Bayesian statistics – Calculation of Bayesian Estimators.

UNIT 2 : Calculate probabilities and moments of loss distributions both with and without simple reinsurance arrangements – Construct risk models appropriate to short term insurance contracts and calculate MGFs and moments for the risk models both with and without simple reinsurance arrangements. - Calculate and approximate the aggregate claim distribution for short term insurance contracts.

UNIT 3 : Explain the concept of ruin for a risk model – Calculate the adjustment coefficients and state Lundberg’s inequality – Describe the effect on the probability of ruin of changing parameter values and of simple reinsurance arrangements.

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UNIT 4 : Describe and apply the fundamental concepts of credibility theory – Describe and apply the fundamental concepts of simple experience rating systems – Describe and apply techniques for analyzing a delay(or run-off) triangle and projecting the ultimate position

UNIT 5 : Explain the fundamental concepts of a generalized linear model(GLM), and describe how a GLM may be applied.

Books for Study and Reference :

Institute of Actuaries Acted. Study Materials.Hossack, Ian B; Pollard, John H; Zenhwirth, Benjamin (1999) : Introductory Statistics

with applications in General Insurance, Cambridge University Press. 2nd ed.Klugman, Stuart A. et al. (1998) : Loss Models: from data to decisions, John WileyDaykin Chris, D; Pentikainen, Teivo; Pesonen, Martti (1994) : Practical Risk theory for

Actuaries, Chapman & Hall.

MSI C217 LIFE CONTINGENCIES – II

UNIT 1 : Gross premiums and provisions

UNIT 2 : Profit Testing

UNIT 3 : Determining provisions using profit testing

UNIT 4 : Factor affecting mortality & selections

UNIT 5 : Single figure indices

Books for Study and Reference:Institute of Actuaries ActEd. Study Materials.Benjamin, B. Pollard, J.H. (1993) : The analysis of mortality and other actuarial

statistics, Faculty and Institute of Actuaries, 3rd ed. Gerber, Hans U. (1997) : Life insurance Mathematics, Springer, Swiss Association of

Actuaries, 3rd ed. Booth, Philip M et al., (1999) : Modern Actuarial Theory and Practice, Chapman &

Hall. Bowers, Newton L.et al (1997):Actuarial Mathematics, Society of Actuaries, 2nd ed.

MSI C218 FINANCIAL ECONOMICS

UNIT 1: Introduction to Financial Economics: - Recap of Utility Theory. The Efficient Markets Hypothesis: The three forms of EMH - The Evidence for or against each form of EMH.

UNIT 2: Measures of Investment Risk: - Measures of Risk - Relationship between Risk measures and Utility Functions.

UNIT 3: Portfolio Theory: - Portfolio Theory - Benefits of Diversification.

UNIT 4: Models of Asset Returns: - Multifactor Models - The Single Index Model.

UNIT 5: Asset Pricing Models: - The Capital Asset Pricing Models (CAPM) – Limitations of CAPM – Arbitrage Pricing Theory (APT).

Books for Study and Reference :

Institute of Actuaries ActEd , CT8 Study material.Panjer, Harry, H. (1998) : Financial economics : with applications to investments,

insurance and pensions. The Actuarial foundations.

MSI C219 JOINT LIFE AND PENSION BENEFITSUNIT 1 : Simple annuities and assurances involving two lives.

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UNIT 2 : Contingent and reversionary benefits

UNIT 3 : Competing risks

UNIT 4 : Multiple decrement tables

UNIT 5 : Pension benefits

Books for Study and Reference:Institute of Actuaries ActEd. Study Materials.Benjamin, B. Pollard, J.H. (1993) : The analysis of mortality and other actuarial

statistics, Faculty and Institute of Actuaries, 3rd ed. Booth, Philip M et al., (1999) : Modern Actuarial Theory and Practice, Chapman &

Hall. Gerber, Hans U. (1997) : Life insurance Mathematics, Springer, Swiss Association of

Actuaries, 3rd edition

MSI C212 CORPORATE FINANCIAL MANAGEMENT

UNIT 1 : Foundations of Finance : Time value of Money – NPV, IRR, and other Measures – Valuation of Common Stocks and Bonds.

UNIT 2 : Investment Analysis : Modern theory of Finance – Capital Budgeting Decision Rule – Capital Budgeting and Cash Flow Analysis – Capital Budgeting and Risk.

UNIT 3 : Variance Analysis – Importance of variance analysis – Material variance, labour variance, overhead variance. Working capital management – Factors determining working capital – Calculation of working capital.

UNIT 4 : Financial Planning : Financial Statements and Ratio Analysis – Short-term Financial Decisions – Long-term Financial Decisions.

UNIT 5 : Special Topics : Mergers and Acquisitions and Corporate Governance – Options and Corporate Finance.

Books for Study and Reference :Brealey, Myers and Marcus : Fundamentals of Corporate Finance, McGraw Hill.Ross, Westerfield and Jordan : Fundamentals of Corporate Finance, Tata McGraw Hill.Van Home and Wachowicz : Fundamentals of Financial Management, Prentice Hall

India.

MSI C213 COMPUTATIONAL LABORATORY – IIObjectives :

To provide exposure to Mathematical / Statistical software focusing more on writing source codes.

To analyse the given data by identifying appropriate tools.

Mathematical and Statistical Packages Exercises. S Plus/ SAS/ MAPLE/ MATHEMATICA/ MATLAB

2. Data Analysis : Identifying the statistical tool and analysing the data using the appropriate tools.(S PLUS/ SAS)

4. Symbolic manipulation using MAPLE/ MATHEMATICAExercises based on the subjects taught in III & IV semesters. (ie. Survival Analysis – Stochastic Models etc.)

5. Simulation study depending upon the requirement of the problem. (MATLAB)

MSI C214 PROJECT & VIVA VOCE

Objectives : To provide written, oral and visual presentation skills To develop team work.

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Course Outline : Based on the interest of the students, they can choose their team and seminar topic. It can also an individual work. During the term, students will meet periodically the faculty to discuss different stages of the seminar. They are required to give three seminar presentations.

Project Work/ Internship :

Objectives : To develop student’s abilities to solve applied industrial and actuarial problems in a longer time frame than in usual in other courses. Students will learn how to search for known results and techniques related the project work. The students will present their project results as a written document and verbally.

Prerequisite : Completion of the course duration of first two semesters.

Course Outline :

The faculty will propose an array of problems in industrial / actuarial studies. Students may choose a problem from this list or propose of their own provided a faculty member / Guide approves it. This work may also be carried out as an internship programme.

On completion of the project work, each student is expected to

Submit a written document describing the results, mathematical developments, background material, bibliographical search etc.

Present orally in a seminar setting of the work done in the thesis Submit the software (if relevant) with appropriate documentation.

The students will meet regularly with the project guide / adviser to work out problems that appear

and adjust the goals and time frame accordingly.

MSI E201 OBJECT ORIENTED PROGRAMMING WITH C++

UNIT 1 : Principles of object oriented programming – beginning with C++ - Token, Expressions and Control structures.

UNIT 2 : Functions in C++ - Classes and objects.

UNIT 3 : Constructors and Destructors – operator overloading and type conversions

UNIT 4 : Inheritance : Extending classes – Pointers, Virtual Functions and Polymorphism.

UNIT 5 : Console I/O operations – working with files – object oriented systems development – Templates and Exception handling.

Books for Study and Reference :Balagurusamy (1999) : Object oriented programming with C++, Tata McGraw Hill

Company Ltd., New Delhi, 16th reprinting.Hubbard, J.R. (2000) : Programming with C++ 2nd ed., McGraw Hill, New York.

MSI E202 PRINCIPLES OF ECONOMICS

UNIT 1 : Market Mechanism – Supply and Demand interaction – Determination of equilibrium Elasticity of demand and Supply – Rational utility and consumption choice – Insurance system and its impact on Welfare.

UNIT 2 : Costs Revenue and output – Market structure – short and long run equilibrium in different markets – perfect competition, Monopoly, Monopolistic competition.

UNIT 3 : Macro Economics – Concepts of GDP, GNP, NNP – methods of calculating National Income – problems – difficulties and uses of National Income Analysis. Propensity to consume – multiplier – determinants of consumption.

UNIT 4 : Monetary and Fiscal policy – Government intervention – financial markets – exchange rates – International trade – Balance of payments.

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UNIT 5 : Inflation types – interest rate and exchange rate – types of unemployment – public sector finances in an industrial economy.

Books for study and Reference :Stonier and Hague : Economic TheoryKovtsoyiannis : Modern micro economics ELBS publications.Samuelson Paul & Norhaus William (1998) : Economics, McGraw Hill.Allen, R.G.D. : Mathematical analysis for Economics, Macmillan.Panjer, Harry, H.(ed)(1998) : Financial Economics with applications to investments, Insurance and pension. The Actuarial foundation

MSI E204 NUMERICAL METHODS

UNIT 1 : Numerical coumputing and computers – Solving non-linear equations.

UNIT 2 : Solving set of equations.

UNIT 3 : Interpolation and curve fitting.

UNIT 4 : Numerical differentiation and Numerical integration.

UNIT 5 : Numerical solution of ordinary differential equations.

Books for Study and Reference :Gerald, C.F. and Wheatley, P.O. (1994) : Applied Numerical Analysis, Addison Wesley,

New York, 5th Ed.Press, W.B., Flannery, S. Teuddsky and Vetterling, W. (1989) : Numerical Recipes in C :

The art of Scientific computing. Rev. 1st ed., Cambridge University Press.Rice, John, R. (1983) : Numerical Methods, Software and Analysis, McGraw Hill, New York.Atkinson, K.E. (1978) : An introduction to Numerical Analysis, Wiley & Sons, New York.Sastry, S.S. (1987) : Introductory methods of numerical analysis, Prentice Hall of India,

New Delhi, (10th printing).

MSI E205 FINANCE AND FINANCIAL REPORTING

UNIT 1 : Introduction to Finance – Functions of Financial Management – Scope – Organisation – Sources of funds – Long term – Medium term and Short term – Financial risks.

UNIT 2 : Company Management – Types of business entity – pros and cons of limited company – legal documentation – corporate and personal taxation.

UNIT 3 : Capital structure – Net Income approach Net operating Income approach – M M approach Traditional approach – average and personal tax of the investors – concept of cost of capital – factors affecting cost of capital – specific and overall cost of capital.

UNIT 4 : Dividend decision and valuation of the firm – Determinants and constraints of a dividend policy – Financial Institution – IDBI, ICICI, IFCI, UTI, Commercial Banks, Insurance companies etc.

UNIT 5 : Financial reporting – Accounting principles – types – basic financial statement – kinds of reports – Nature of reports – guiding principles of reporting – necessary steps for good reporting.

Books for Study and Reference :Samuels, J.M., Wilkes, F.M., Brayshaw, R.E. (1995) : Management of company finance,

International Thomson, 6th ed.Brealey, Richard, A. (1999) : Principles of Corporate finance, McGraw Hill, 6th ed.Holmes, Geoffrey, Sugden, Alan (1999) : Interpreting company reports and accounts,

Prentice Hall, 7th ed.Pandey, I.M. : Financial Management.Prasannachandra : Financial ManagementKuchhal : Financial ManagementMoshal : Management AccountingInstitute of Actuaries ActEd , Study Material :

MSI E207 RESOURCE OPTIMIZATION PRINCIPLES

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UNIT 1 : Linear programming problems - model formulation and graphical solution – various types of solutions – simplex method of solving linear programming –duality principles – dual simplex method.

UNIT 2 : Artificial variable techniques Big M method – two phase method – assignment problem – transportation problem – MODI method of finding optimal solutions.

UNIT 3 : Sequencing problem – replacement problems – game theory – zero sum games – graphical method – solution of games by LPP.

UNIT 4 : Decision analysis – components of decision making – decision making without probabilities – maximum – minimax regret – Hurwicz and equal likelihood criterion – decision making with probabilities – expected value – expected opportunity loss criterion.

UNIT 5 : Network flow models – shortest route problem – project management – the CPM and PERT Networks.

Books for Study and Reference :

Sharma, J.K. (1997) : Operations Research, Theory and applications, Macmillan.Taha, H.A. (1996) : Operations Research, 5th edition, Prentice Hall of India, New York.

MSI E208 DATA ANALYSIS USING R & SAS Prerequisite: compulsory knowledge in Advanced Statistical Inference and Survival Analysis

UNIT 1 : Graphs, Diagrams , Descriptive Statistics and Data Exploration Techniques

UNIT 2 : Bivariate Data Analysis, Multivariate Data Analysis

UNIT 3 : Non parametric Tests

UNIT 4 : Statistical Models ,Time series Analysis

UNIT 5 : Simulation Techniques

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STATISTICS

An independent Department of Statistics started functioning in 1941 and became a full fledged Department of study and research from 1975 under the leadership of Prof. K.N.Venkataraman. The Department offers Masters M.Phil. and Ph.D. programmes. The Department also offers P.G. Course in Actuarial Science, a self-supportive course under University Industry Community Interaction Centre (UICIC) of the University .

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STATISTICS(Course Proposals for the academic year 2007 – 2008)

A – CORE COURSESSubject Code

Title of the Course C/E/S L T P C

I SEMESTERMSI C101 Real Analysis C 3 1 0 4MSI C102 Linear Algebra C 3 1 0 4MSI C103 Distribution Theory C 3 1 0 4MSI C104 Measure Theory C 3 1 0 4

Elective 1 E 2 1 0 3Elective 2 E 2 1 0 3

UOM S001 Soft Skill S 2

II SEMESTERMSI C105 Probability Theory C 3 1 0 4MSI C106 Sampling Theory C 3 1 0 4MSI C107 Statistical Estimation Theory C 3 1 0 4MSI C108 Practical – I (Calculator Based) C 2 0 0 2

Elective 3 E 2 1 0 3Elective 4 E 2 1 0 3

UOM S002 Soft Skill S 2

III SEMESTERMSI C109 Multivariate Analysis C 3 1 0 4MSI C110 Testing Statistical Hypotheses C 3 1 0 4MSI C111 Design & Analysis of Experiments C 3 1 0 4

Elective 5 E 2 1 0 3UOM S003 Soft Skill S 2UOM I001 Internship S 2

IV SEMESTERMSI C112 Statistical Quality Management C 3 1 0 4MSI C113 Practical – II (Calculator Based) C 0 0 2 2MSI C114 Practical – III (Software Based) C 0 0 2 2MSI C115 Project Work / Dissertation C 0 6 0 6MSI C116 Reliability and Survival Analysis C 3 1 0 4

Elective 6 E 2 1 0 3UOM S004 Soft Skill S 2

B – ELECTIVE COURSES :

Subject Code

Title of the Course L T P C

MSI E101 Operations Research 3 0 0 3MSI E102 Actuarial Statistics 3 0 0 3MSI E103 Statistical Genetics 3 0 0 3MSI E104 Markov Chain and its Applications 3 0 0 3MSI E106 Statistical Methods for Epidemiology 3 0 0 3MSI E107 Stochastic Modeling 3 0 0 3MSI E108 Non parametric inference 3 0 0 3MSI E109 Data Mining Tools 3 0 0 3MSI E110 Bayesian Inference 3 0 0 3MSI S111 * Statistics for Social Sciences 3 0 0 3MSI S112 * Bio-Statistics 3 0 0 3

* TO OTHER DEPARTMENTS ONLY

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MSI C101 Real Analysis C 3 1 0 4 Guest FacultyPre-requisite : Undergraduate level Mathematics.

Unit I : Recap of elements of set theory; introduction to real numbers, introduction to n-dimensional Euclidian space; open and closed intervals (rectangles), compact sets, Bolzano – Weirstrass theorem, Heine – Borel theorem.

Unit II : Sequences and series; their convergence. Real valued functions, continuous functions; uniform continuity, sequences of functions, uniform convergence ; power series and radius of convergence.

Unit III : Differentiation, maxima – minima of functions; functions of several variables, constrained maxima – minima of functions.

Unit IV : Riemann integral & Riemann – Stieltjes integral with respect an increasing integrator – properties of R.S. integral –integrators of bounded variation.

Unit V : Multiple integrals and their evaluation by repeated integration, change of variables in multiple integration. Uniform convergence in improper integrals, differentiation under the sign of integral – Leibnitz rule.

REFERENCES :

Apostol, T.M. (1985) : Mathematical Analysis, Narosa, Indian Ed.Bartle,R.G., Sherbert, D.R.(1982) : introduction to Real analysis.Malik, S.C.(1985) : Mathematical analysis, Wiley Eastern Ltd.Royden, H.L.(1995) : Real analysis, 3ed., Prentice Hall of India.Rudin, Walter (1976) : Principles of Mathematical Analysis, McGraw Hill.Rangachari,M.S.(1996) : Real Analysis, Part 1, New Century Book House.

MSI C102 Linear Algebra C 3 1 0 4 Ms. M.R. SindhumolPre-requisite : Undergraduate level Mathematics. Unit 1 : Vector spaces, Linear dependence, linear independence, basis and diversion of vector space, inner product Gram Schmidt orthogonalization, linear transformations, projection operators, null space and nullity.

Unit II : Matrix algebra, rank and inverse of a matrix, determinants, characteristic roots, characteristic polynomial, Cayley Hamilton theorem, multiplicity of characteristic roots, idempotent matrix.

Unit III : Reduction of matrices, Echelon form, Hermite canonical form, diagonal reduction, rank factorization, triangular reduction Jordan form, pairs of symmetric matrices, singular value decomposition, spectral decomposition. Unit IV : Kronecker product of matrices matrix differentiation, generalized inverse, Moore-Penrose inverse and properties of g-inverse, Application of g-inverse.

Unit V : Quadratic forms, classification, definiteness, index and signature, extremum of quadratic forms, reduction of quadratic form, transformation, applications of quadratic forms.

REFERENCES :

Bellman, R. (1970) : Introduction to Matrix Analysis, 2nd ed. McGraw Hill.Biswas, S. (1984) : Topics in Algebra of Matrices, Academic Publications.David, A.Harville(1997) : Matrix algebra from a statistician’s perspective, Springer.Hadley, G. (1987) : Linear Algebra, Narosa Publishing House.Hoffman, K. and Kunze, R. (1971) : Linear Algebra, 2nd ed. Prentice Hall, Inc.Graybill, F.A. (1983) : Matrices with application in Statistics, 2nd ed. Wadsworth.Rao, C.R. & Bhimasankaran, P.(1992) : Linear algebra, Tata McGraw Hill Pub. Co. Ltd.Searle, S.R. (1982) : Matrix Algebra useful for Statistics, John Wiley and Sons, Inc.

MSI C103 Distribution Theory C 3 1 0 4 Guest FacultyPre-requisite : Undergraduate level Mathematics.

Unit I : Brief review of distribution theory, functions of random variables and their distributions using Jacobian of transformation, Laplace and Caushy distribution, lognormal distribution, gamma, logarithmic series.

Unit II : Bivariate normal, Bivariate exponential, Bivariate Poisson, Compound, truncated and mixture of distributions, concepts of convolution.

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Unit III : Sampling distributions, non-central chi-square distribution, t and F distributions and their properties, distributions of quadratic forms under normality and related distribution theory – Cochran’s and James theory.

Unit IV : Order statistics their distributions and properties, Joint and marginal distributions of order statistics, extreme value and their asymptotic distributions, approximating distributions of sample moment, delta method.

Unit V : Kolmogorov Smirnov distributions, life distributions, exponential, Weibull and extreme value distributions Mills ratio, distributions classified by hazard rate.

REFERENCES :

Gibbons(1971) : Non-parametric inference, Tata McGraw Hill.Rohatgi, V.K. and Md. Whsanes Saleh, A.K.(2002) : An introduction to probability & Statistics, John Wiley and Sons.Rao, C.R. (1973) : Linear statistical inference and its applications, 2ed, Wiley Eastern.Mood,A.M. & Graybill, F.A. and Boes, D.C. : Introduction to the theory of statistics, McGraw Hill.Johnson,S. & Kotz,(1972): Distributions in Statistics, Vol. I, II & III, Hougton & Miffin.Dudewicz, E.J., Mishra, S.N.(1988) : Modern mathematical statistics, John Wiley.Searle, S.R.(1971) : Linear models, John Wiley.

MSI C104 Measure Theory C 3 1 0 4 Dr. G.Gopal/Guest Faculty

Pre-requisite : Undergraduate level Mathematics.

Unit I : Sets and set functions, Algebra of sets, limits of sequence of sets, classes of sets : Ring, Field, Field and monotone classes, Generated classes.

Unit II : Measure functions, properties of measure functions, Outer measure, extension and completion of measures signed measures, Hahn Decomposion theorem.

Unit III : Lebesgue, Stieltjes measures, examples, measurable functions, approximation theorems.

Unit IV : Measure integration, properties of measure integrals, Monotone convergence theorem and dominated convergence theorem, Fatou’s lemma.

Unit V : Absolute continuity, Radon Nikodymn theorem, singularity, Lebesgue Decomposion theorem, Fubini’s theorem, convergence types for measurable functions (almost everywhere, in mean and their inter-relationships).

REFERENCES :

Munroe, M.E. (1971) : Measure and integration, 2nd ed. Addision Wesley.Ash, R.B. (1972) : Real analysis and probability, Academic press.Kingman, J.F.C. and Taylor, J. (1973) : Introduction to measure and probability, Cambridge University Press.Royden, H.L. (1968) : Real analysis, 2nd ed. Macmillan.Loeve, M. (1960) : Probability theory, Van Nostrand.Halmos, P.R. (1974) : Measure theory, East-West.De Barr, G. (1987) : Measure theory and integration, Wiley Eastern.

MSI C105 Probability Theory C 3 1 0 4 Dr.G.Gopal/ Guest Faculty

Pre-requisite : Measure Theory.

Unit I : Events, sample space, different approaches to probability, random variables and random vector, Distribution functions of random variables and random vector, Expectation and moments, basic, Markov, Chebyshev’s, Holder’s, Minkowski’s and Jensen’s inequalities.

Unit II : Independence of sequence of events and random variables, conditional probability, conditional expectation, smoothing properties, Tail-sigma field, 0-1 law of Borel and Kolmogorov, Hew itt-Savage 0-1 law. Unit III : Characteristic functions and their properties, inversion formula, convergence of random variables, convergence in probability, almost surely, in the r-th mean and in distribution, their relationships, convergence of moments, Helly-Bray theorem, continuity theorem and convolution of distributions.

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Unit IV : Convergence of series of random variables, three-series theorem, Khintchines weak law of large numbers, Kolmogorov inequality, strong law of large numbers.

Unit V : Central limit theorem, statement of CLT, Lindeberg, Levy and Liapounov forms with proof and Lindeberg Feller’s form examples.

REFERENCES :

Bhat, B.R. (1985) : Modern probability theory, 2nd ed. Wiley Eastern.Chow, Y.S. and Teicher, H. (1979) : Probability theory, Springer Verlag.Ash Robert, B. (1972) : Real analysis and probability, Academic Press. 3rd ed.Chung, K.L. et al : A course in probability theory, Academic press.V.K.Rohatgi etal(2002) : An introduction to probability and statistics, John Wiley.Parthasarthy, K.R. (1977) : Introduction to probability and measure, MacMillan Co., Breiman, L. (1968) : Probability, Addison Wesley.

MSI C106 Sampling theory C 3 1 0 4 Dr.M.R.SrinivasanPre-requisite : Undergraduate level Mathematics.

Unit I : Review of basic finite population sampling techniques SRS, Stratified, Systematic sampling, related results on estimation, allocation problem in stratification sampling, efficiency of systematic over stratified and SRS.

Unit II : Varying probabilities, PPS WR/WOR ordered and un-ordered estimator, selection of samples Horowitz Thompson, Desraj, Rao Hartley-Cochran estimators.

Unit III : Sampling with supplementary information, Ratio and regression estimators and related results.

Unit IV : Multi stage and multiphase sampling, two stage sampling with equal number of second stage under-double sampling cluster sampling.

Unit V : Non sampling errors, errors in surveys (Types of Errors), Observational errors (Measurement and related results, Incomplete samples (Non-response Politz and summary randomized response technique, Introduction to Jackknife and bootstrap techniques.

REFERENCES :

Cochran, W.G. (1977) : Sampling Techniques 3rd ed., Wiley.Des Raj and Chandak (1988) : Sampling Theory, Narosa.Murthy, M.N. (1977) : Sampling theory and methods. Statistical publishing society, Calcutta.Sukhatme & Sukhatme (1984) : Sampling theory of surveys with applications. ISAS.Singh, D. and Chaudhary, F.S. (1986) : Theory and Analysis of Sample Survey Designs, New Age International Publishers.

MSI C107 Statistical Estimation Theory C 3 1 0 4 Dr.G.GopalPre-requisite : Probability Theory.

Unit I : Sufficient statistics, Neyman, Fisher Factorisation theorem, the existence and construction of minimal sufficient statistics, Minimal sufficient statistics and exponential family, sufficiency and completeness, sufficiency and invariance.

Unit II : Unbiased estimation : Minimum variance unbiased estimation, locally minimum variance unbiased estimators, Rao Blackwell – theorem.Completeness- Lehmann Scheffe theorems, Necessary and sufficient condition for unbiased estimators Unit III : Cramer- Rao lower bound, Bhattacharya system of lower bounds in the 1-parameter regular case. Chapman -Robbins inequality.

Unit IV : Maximum likelihood estimation, computational routines, strong consistency of maximum likelihood estimators, Asymptotic Efficiency of maximum likelihood estimators, Best Asymptotically Normal estimators, Method of moments.

Unit V : Bayes’ and minimax estimation : The structure of Bayes’ rules, Bayes’ estimators for quadratic and convex loss functions, minimax estimation, interval estimation.

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REFERENCES :

V.K.Rohatgi etal(2002) : An introduction to probability and statistics, John Wiley.Lehmann, E.L. (1983) : Theory of point estimation, John Wiley.Zacks, S. (1971) : The theory of statistical inference, John Wiley.Rao, C.R. (1973) : Linear statistical inference and its applications, Wiley Eastern, 2nd ed.Ferguson, T.S. (1967) : Mathematical statistics, A decision theoretic approach, Academic press, New York and London.Lindley, D.V. (1965) : Introduction to probability and statistics, Part 2, Inference, Cambridge University Press.

MSI C108 Practical – I (Calculator Based) C 2 0 0 2 All Faculty

Practical Exercises based on MSI C102, MSI C103, MSI C106 and MSI C107

MSI C109 Multivariate Analysis C 3 1 0 4 Guest FacultyPre-requisite : Distribution theory.

Unit I : Random sampling from a multivariate normal distribution. Maximum likelihood estimators of parameters. Distribution of sample mean vector. Wishart matrix – its distribution and properties. Distribution of sample generalized variance.

Unit II : Null and non-null distribution of simple correlation coefficient. Null distribution of partial and multiple correlation coefficient. Distribution of sample regression coefficients. Application in testing and interval estimation. Distribution of sample intra – class correlation – coefficient in a random sample from a symmetric multivariate normal distribution. Application in testing and interval estimation.

Unit III : Null distribution of Hotelling’s T2 statistics. Application in tests on mean vector for one and more multivariate normal populations and also on equality of the components of a mean vector in a multivariate normal population.

Unit IV : Multivariate linear regression model – estimation of parameters, tests of linear hypotheses about regression coefficients. Likelihood ratio test criterion. Multivariate Analysis of variance (MANOVA) of one-and two-way classified data.

Unit V : Classification and discrimination procedures for discrimination between two multivariate normal populations – sample Discriminant function, tests associated with Discriminant functions, probabilities of misclassification and their estimation, classification into more than two multivariate normal populations.

Principal components, Dimension reduction, Canonical variables and canonical correlation – definition, use, estimation and computation.

REFERENCES :

Anderson, T.W. (1983) : An introduction to multivariate statistical analysis. 2nd ed.Wiley. (study)Giri, N.C. (1977) : Multivariate statistical inference, Academic press.Kshirsagar, A.M. (1972) : Multivariate analysis, Marcel Dekker.Morrison, D.F. (1976) : Multivariate statistical methods, 2nd ed. McGraw Hill.(study)Muirhead, R.J. (1982) : Aspects of multivariate statistical theory, Wiley.Rao, C.R. (1973) : Linear Statistical Inference and its applications, 2nd ed. Wiley.Seber, G.A. (1984) : Multivariate observations, Wiley.Sharma, S. (1996) : Applied multivariate techniques, Wiley.Srivastava, M.S. and Khatri, C.G. (1979) : An introduction to multivariate statistics. North Holland.Johnson,R.& Wichern(1992) : Applied multivariate statistical analysis, Prentice Hall, 3ed.(study).

MSI C110 Testing Statistical Hypotheses C 3 1 0 4 Dr.G.GopalPre-requisite : Probability Theory .

Unit I : Uniformly most powerful tests, the Neyman-Pearson fundamental Lemma, Distributions with monotone likelihood ratio.Problems

Unit II : Generalization of the fundamental lemma, two sided hypotheses, testing the mean and variance of a normal distribution.Unit III : Unbiased ness for hypotheses testing, similarly and completeness, UMP unbiased tests for multi parameter exponential families, comparing two Poisson or Binomial populations, testing the parameters of a normal distribution (unbiased tests), comparing the mean and variance of two normal distributions.

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Unit IV : Symmetry and invariance, maximal invariance, most powerful invariant tests.

Unit V : SPRT procedures, likelihood ratio tests, locally most powerful tests, the concept of confidence sets, non parametric tests.

REFERENCES :

V.K.Rohatgi etal(2002) : An introduction to probability and statistics, John Wiley.Lehmann, E.L. (1986) : Testing of statistical hypothesis, John Wiley.Ferguson, T.S. (1967) : Mathematical statistics, A decision theoretic approach, Academic press.Rao, C.R. (1973) : Linear statistical inference and its applications, Wiley Eastern, 2nd ed.Gibbons, J.D. (1971) : Non-parametric statistical inference, McGraw Hill.

MSI C111 Design and Analysis of Experiments

C 3 1 0 4 Dr.M.R.Srinivasan

Pre-requisite : Matrix algebra & Linear models.

Unit I : Linear models, classification, linear estimators, Gauss-Markov theorem, BLUE, test of general linear hypothesis, fixed, mixed and random effects models.

Unit II : Review of basic designs: CRD, RBD, LSD, Orthogonal latin squares, Hyper Graeco Latin squares – analysis of variance – analysis of covariance – multiple comparisons – multiple range tests - Missing plot technique – general theory and applications.

Unit III : General factorial experiments, factorial effects; best estimates and testing the significance of factorial effects ; study of 2 and 3 factorial experiments in randomized blocks; complete and partial confounding. Fractional replication for symmetric factorials. Sprip plot and split block experiments.

Unit IV : General block design and its information matrix (C), criteria for connectedness, balanced and orthogonality; intrablock analysis (estimability, best point estimates / interval estimates of estimable linear parametric functions and testing of linear hypotheses) : BIBD – recovery of interblock information; Youden design – intrablock analysis.

Unit V : Response surface methodology - first order and second order rotatable designs, applications: clinical trials.

REFERENCES :

Das, M.N. and Giri, N. (1979) : Design and analysis of experiments, Wiley Eastern.John, P.W.M. (1971) : Statistical design and analysis of experiments, Macmillan.Montgomery, C.D. (2001) : Design and analysis of experiments, John Wiley, New York.Friedman, L.M., Furberg, C.D., Demets, D.L.(1998) : Fundamentals of clinical trials, Springer.Robert, O., Kuelhl(2000) : Design of experiments. Statistical principles of research design and analysis, Duxbury.Federer, W.T.(1963) : Experimental design; Theory and application, Oxford & IBH publishing Co.Doshi, D.D. (1987) : Linear estimation and design of experiments, Wiley Eastern Ltd.

MSI C112 Statistical Quality Management C 3 1 0 4 Ms.M.R.SindhumolPre-requisite : Undergraduate level Statistics.

Unit I : Concept of quality – definition and standardization of quality – Functional elements of TQM, quality movements in India, quality circle, quality audit, Direct and indirect quality costs, measurement and analysis – Pareto and Ishikawa diagrams, ISO 9000 series.

Unit II : General theory and review of control charts for attribute and variable data; O.C. and A.R.L. of control charts; Moving average and exponentially weighted moving average charts; Cu-sum charts using V-masks and Economic design of X-bar chart.

Unit III : Acceptance sampling plans for attribute inspection ; single, double and sequential sampling plans and their properties. Plans for inspection by variables for one-sided and two-sided specifications; Mil-Std and IS plans.

Unit IV : continuous sampling plans for Dodge type and Wald-Wolfiwitz type and their properties, chain sampling plan..

Unit V : Capability indices Cp, Cpk and Cpm; estimation, confidence intervals and tests of hypotheses relating to capability indices for Normally distributed characteristics. Use of Design of Experiments in SPC, factorial experiments.

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REFERENCES :

Montgomery, D.C. (2001) : Introduction to Statistical Quality Control, John Wiley.Ott,E.R. (1975) : Process quality control, McGraw Hill.Grant, L. and Leavenworth, S. (1996) : Statistical quality control, McGraw Hill.Murthy, M.N. (1989) : Excellence through quality & reliability, Applied statistical centre.Thomas P.Ryan(2000) : Statistical methods for quality improvement 2ed., John Wiley.

MSI C113 Practical – II (Calculator Based) C 0 0 2 2 Ms. M.R. Sindhumol

Practical Exercises based on MSI C109, MSI C110, MSI C111, MSI C112 and MSI C113

MSI C114 Practical – III (Software Based) C 0 0 2 2 Dr. M.R. Srinivasan

Use Statistical packages like SPSS, MINITAB / S-PLUS for solving statistical problems in Core and Electives. Exercises will be prepared by the faculty in-charge.

MSI C115 Project Work / Dissertation C 0 6 0 6 All Faculty

MSI C116 Reliability and Survival Analysis C 3 1 0 4 Dr. G.GopalPre-requisite : Probability Theory.

Unit I : Introduction to Survival concepts, Survival functions and hazard rates, concepts of Type I, Type II, Random and other types of censoring, likelihood in these cases.

Unit II : Life distributions-exponential Weibull, Gamma, Lognormal, Pareto, Linear failure rate, estimation / testing under censoring setup.

Unit III : Life tables, failure rate, mean residual life and their elementary properties.

Unit IV : Estimation of survival functions-actuarial estimator, Product – limit (Kaplan-Meier) estimator, properties.

Unit V : Cox proportional hazards regression models with one and several covariates, exponential, Weibull, lognormal regression.

REFERENCES :

Miller,R.G.(1981) : Survival analysis, John Wiley.Collet, D.(1984) : Statistical analysis of life time data.Despande,J.V., Gore, A.P. and Shanbhogue, A.(1995) : Statistical analysis of non normal data, Wiley Eastern.Cox, D.R. and Oakes, D.(1984) : Analysis of survival data, Chapman & Hall, New York.Gross, A.J. and Clark, V.A.(1975) : Survival distribution: Reliability applications in the Biomedical sciences, John Wiley and Sons.Elandt-Johnson,R.E. Johnson, N.L. : Survival models and data analysis, John Wiley & sons.Kalbfleish, J.D. and Prentice R.L.(1980) : The statistical analysis of failure time data, John Wiley.

ELECTIVES

MSI E101 Operations Research 3 0 0 3 Guest Faculty

Pre-requisite : Open to all – Offered in the First Semester.

Unit I : Linear programming – Simplex and Revised simplex method. Duality in LPP – sensitivity Analysis – Bounded variable Techniques – parametric and integer programming problems – Game theory – different methods of solving game problems. Unit II : Application of LPP – Transportation problem – Assignment problem – characteristic of queuing model – M/M/1 and M/M/C queuing model.

Unit III : Network analysis- PERT and CPM-Simulation- Monte-Carlo Techniques.

REFERENCES :

Handy Taha (1992) : Operations Research, An Introduction, Prentice Hall.Hiller Lieberman (1995) : Introduction to Opearations Research, McGraw Hill.J.K.Sharma(1997) : Operations Research. Theory and Applications, Macmillan.

MSI E102 Actuarial Statistics 3 0 0 3 Guest Faculty

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Pre-requisite : Open to all – Offered in the Second Semester

Unit I : Mortality : Gompertz - Makeham laws of mortality - life tables.Annuities : Endowments, Annuities, Accumulations, Assurances, Family income benefits.

Unit II : Policy Values : Surrender values and paid up policies, industrial assurances, Joint life and last survivorship, premiums.

Unit III : Contingent Functions : Contingent probabilities, assurances. Decrement tables.Pension funds : Capital sums on retirement and death, widow’s pensions, benefits dependent on marriage.

REFERENCES :Study Material, 104-Survival Models, Actuarial Society of India.Hooker,P.F., Longley, L.H.-Cook (1957) : Life and other contingencies, Cambridge.Alistair Neill(1977) : Life contingencies, Heinemann professional publishing.Hosack,I.B., Pollard, J.H. and Zehnwirth, B.(1999) : introductory statistics with applications in general insurance, Cambridge University.

MSI E103 Statistical Genetics 3 0 0 3 Dr.M.R.Srinivasan

Unit I : Bio-assays - response relationship - Transformation - probit and logits - Feller's theorem. Symmetric and Asymmetric assays.

Unit II : Mating designs - random mating - Hardy and Weinberg equilibrium. Inbreeding - segregation and linkage analysis.

Unit III : Estimation of gene frequencies - inheritance - heritability- repeatability - selection index - diallel and triallel crosses.

REFERENCES :

Falconer, D.S.(1981) : Introduction to quantitative genetics, Longman.Bruce, S.Wein(1990) : Genetic data analysis, Sinauer associates.Keneth Lange(1997): Mathematical and statistical methods for genetic analysis, Springer.

MSI E104 Markov Chain and its Applications 3 0 0 3 Guest Faculty

Unit I : Markov Chains - classification of states, Determination of higher order transition probabilities,

stability of a Markov system, limiting behavior.

Unit II : Kolmogorov forward and backward differential equations. Poisson processes - birth and

death processes and applications.

Unit III : Branching process and its applications.

REFERENCES :

J.Medhi(1982) : Stochastic processes, Wiley Eastern.Cinlar, E.(1975) : Introduction to stochastic processes, Prentice Hall.Samuel Karlin and Howard M.Taylor(1975) : A first course in Stochastic processes Vol.I, Academic PressBhat,B.R.(2000) : Stochastic models : Analysis and Applications, New Age International.

MSI E106 Statistical Methods for Epidemiology 3 0 0 3 Dr.M.R.Srinivasan

Unit I : Measures of disease frequency : Mortality / morbidity rates, incidence rates, prevalence rates. Source of mortality / morbidity statistics – hospital records, vital statistics records. Measures of secrecy or validity : sensitivity index, specificity index. Measure of reliability.Epidemiologic concepts of diseases : Factors which determine the occurrence of diseases, models of transmission of infection, incubation period, disease spectrum and herd immunity.

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Unit II : Observational studies in Epidemiology : Retrospective (case control) & prospective (cohort or longitudinal) studies. Measures of association : Relative risk, attributable risk. Statistical techniques used in analysis : Cornfield and Garts method, Mantel – Haenszel method. Conditional and unconditional matching. Analysis of data from matched samples, logistic regression approach.

Experimental Epidemiology : Clinical and community trials Statistical techniques: Methods for comparison of two treatments. Crossover design with Garts and McNemars test. Randomization in a clinical trials, sequential methods in clinical trials, clinical life tables, assessment of survivability in clinical trials.

Unit III : Mathematical modeling in Epidemiology : (deterministic and stochastic) simple epidemic model, generalized epidemic model, Read-Frost and Green-wood models, models for carrier borne and host vector diseases. Estimation of latent and infectious periods, geographical spread of the disease, simulation of an epidemic.

REFERENCES :Kahn, H.A., Sempose, C.T.(1989) : Statistical methods in Epidemiology, Oxford University press.Daley, D.J., Gani, J.(1999) : Epidemic modeling an introduction, Cambridge.

MSI E107 Stochastic Modelling 3 0 0 3 Dr.G.Gopal

Unit I : Basic concepts of Stochastic Processes and their classifications - Markov chain and its applications - Markov processes and applications.

Unit II : Time Series models : Concepts, analysis and applications.Gauss Weiner processes - Levy processes. Brownian Motion.

Unit III : Monte Carlo simulations of stochastic processes.

REFERENCES :

J.Medhi(1982) : Stochastic processes, Wiley Eastern.Cinlar, E.(1975) : Introduction to stochastic processes, Prentice Hall.Samuel Karlin and Howard M.Taylor(1975) : A first course in Stochastic processes Vol.I, Academic PressBhat,B.R.(2000) : Stochastic models : Analysis and Applications, New Age International.

MSI E108 Non parametric Inference 3 0 0 3 Dr.M.R.Srinivasan

Unit I : Rank tests for comparing two treatments, Wilcoxon ranksum tests, Asymptotic null distribution of Wilcoxon statistics, Siegel-Tukey and Smirnov tests, power of Wilcoxon rank, sum tests, Asymptotic power, comparison with students t-test, estimating the treatment effect.

Unit II : Block comparison for two treatments, sign test for paired comparisons, Wilcoxon signed rank test, a balanced design for paired comparisons, power of sign and Wilcoxon signed rank tests and their comparisons. Comparison of more than two treatments, the Kruskal, Wallis test, 2 x t contingency table, comparing several treatments with a control, ranking several treatments.

Unit III : Randomised complete blocks, Friedman, Cochran, McNemar tests, Aligned ranks. Tests of randomness and independence, testing against, trend, testing for independence, zxt contingency tables.

REFERENCES :

Lehmann, E.L.(1975) : Non parameteric: Statistical methods based on Ranks, McGraw Hill.Gibbons, J.D.(1971) : Non parametric Statistical inference, McGraw Hill.Hajek, J. and Sidak, Z.(1967) : The theory of rank tests, Academic press.Hollandar, M. and Wolfe, D.A.(1973) : Non parametric statistical methods, John Wiley.Walsh, J.F.(1962) : Handbook of non parametric statistics, Van Nostrand.Puri,M.L.(Ed.) (Bloomington1969)n (1972) : First international symposium on non parametric inference, Cambridge University press.

MSI E109 Data Mining Tools 3 0 0 3 Ms.M.R.Sindhumol

Unit I : Classification and clustering methods, decision trees.

Unit II : Introduction to databases, data warehouse, online analytical processing.

Unit III : Association rules, neural networks, regression models and trees.

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REFERENCES :

Han,J and Kamber,M(2001) : Data mining: Concepts and techniques, Morgan Kautamann publishers.Brieman, L. Friedman, J.H.,Olshen, R.A. and Stone,C.J.(1984) : Classification and regression trees; Wardsworth and Brooks.Hestie, T.,Tibshirani,R. and Friedman,J.(2001) : The elements of statistical learning, Springer.Johnston,R.R. & Wichern (1992):Applied multivariate Statistical analysis, Prentice Hall.

MSI E110 Bayesian Inference 3 0 0 3 Guest Faculty

Unit I : Bayesian point estimation : as a prediction problem from posterior distribution. Bayes estimators for (i) absolute error loss (ii) squared error loss (iii) 0-1 loss. Generalization to convex loss functios. Evaluation of the estimate in terms of the posterior risk. theorem – prior and posterior distributions. Conjugate priors and Jeffrey’s priors, examples.

Unit II : Bayesian interval estimation : Credible intervals. Highest posterior density regions. Interpretation of the confidence coefficient of an interval and its comparison with the interpretation of the confidence coefficient for a classical confidence interval.

Unit III : Bayesian testing of hypotheses : Specification of the appropirate form of the prior distribution for a Bayesian testing of hypothesis problem. Prior odd,s Posterior odds, Bayes factor for various types of testing hypothesis problems depending upon whether the null hypothesis and the alternative hypothesis are simple or composite.

REFERENCES :

Berger,J.O. : Statistical decision theory and Bayesian analysis, Springler Verlag.Robert, C.P. and Casella, G.Monte Carlo : Statistical methods, Springer Verlag.Leonard, T. and Hsu, J.S.J. : Bayesian methods, Cambridge University press.Degroot, M.H. : Optimal statistical decisions, McGraw Hill.Bernando, J.M. and Smith, A.F.M. : Baysian theory, John Wiley and sons.Robert, C.P. : The Bayesian choice : A decision theoretic motivation, Springer.

MSI S111 Statistics for Social Sciences 3 0 0 3 Dr.G.Gopal / Guest Faculty

Unit I : Measures of central tendency and dispersion - coefficient of variation. Elements of probability theory - Bayes theorem. Random variables - standard distributions and their properties, Binomial, Poisson, Uniform, Normal Distributions.

Unit II : Elements of sampling theory - Simple and stratified and systematic sampling schemes. Multiple correlation and Regression, Partial linear and Regression, Correlation and regression - Rank Correlation.

Unit III : Tests of significance based on Normal t, Chi square and F distributions. ANOVA - one-way and two-way classifications.

REFERENCES :

John E.Freund(1999) : Mathematical statistics, Pearson education.Rohatgi, V.K. (2001) : An introduction to probability and statistics, John Wiley.Bhat,B.R. Srivenkataraman,T. and Rao Madheva K.S.(1997) : Statistics:A beginner’s text, Vol.II, New age international Pvt. LTd.

MSI S112 Bio-Statistics 3 0 0 3 Dr.M.R.Srinivasan/Ms.M.R.Sindhumol

Unit I : Frequency distribution - Diagrammatic representation - Measures of Central tendency - Dispersion - Probability - Probability distribution - Binomial, Poisson & Normal Distribution.

Unit II : Elements of sampling theory – Simple, stratified and systematic sampling schemes. Applications in Biology Correlation and Regression, Rank Correlation. Multiple correlation and Regression, Partial correlation.

Unit III : Large Sample test - Small sample test - Student ‘t’, ‘F’ tests - Chi-Square test for independence and Goodness of fit - Analysis of Variance. Non parametric Tests - Sign test, Run test, Median test, Two Sample Rank test.

REFERENCES :

Wayne,W.David(1987) : A foundation for analysis in Health Sciences 4th ed., John Wiley and Sons.

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Jerrold H.Zar ( 1984) : Bio statistical analysis, Prentice hall 2nd ed.Susan Milton, J.(1992) : Statistical methods in the biological and health sciences, McGraw Hill.Jain,J.R.(1982) : Statistical techniques in quantitative genetics, Tata McGraw Hill.

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