class xii chapter wise concept map

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RELATIONS & FUNCTIONS CONCEPTS:- 1. RELATION 2. TYPES OF RELATIONS a) Empty Relation b) Universal Relation c) Reflexive Relation d) Symmetric Relation e) Transitive Relation 3. EQUIVALENCE RELATION A Relation which is Reflexive, Symmetric and Transitive 4. FUNCTION To recall - identity , constant, linear, polynomial, rational, Signum, modulus, greatest integer functions 5. TYPES OF FUNCTIONS a) One – One ( Injective mapping) b) Onto ( Surjective mapping) c) One – One and Onto ( Bijective mapping) 6. COMPOSITION OF FUNCTIONS To recall algebra of functions and to introduce composition of functions. 7. INVERSE OF A FUNCTION Problems based on linear, quadratic and rational functions 8. BINARY OPERATIONS Operation Table 9. PROPERTIES OF BINARY OPERATIONS a) Commutative b) Associative c) Existence of Identity element d) Existence of Inverse element e) To check properties of binary operation using operation table INVERSE TRIGONOMETRIC FUNCTIONS 1. RECALL ALL THE TRIGONOMETRIC IDENTITIES

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  • RELATIONS & FUNCTIONS

    CONCEPTS:-

    1. RELATION 2. TYPES OF RELATIONS

    a) Empty Relation b) Universal Relation c) Reflexive Relation d) Symmetric Relation e) Transitive Relation

    3. EQUIVALENCE RELATION A Relation which is Reflexive, Symmetric and Transitive

    4. FUNCTION To recall - identity , constant, linear, polynomial, rational, Signum, modulus, greatest integer functions

    5. TYPES OF FUNCTIONS a) One One ( Injective mapping) b) Onto ( Surjective mapping) c) One One and Onto ( Bijective mapping)

    6. COMPOSITION OF FUNCTIONS To recall algebra of functions and to introduce composition of functions.

    7. INVERSE OF A FUNCTION Problems based on linear, quadratic and rational functions

    8. BINARY OPERATIONS Operation Table

    9. PROPERTIES OF BINARY OPERATIONS a) Commutative b) Associative c) Existence of Identity element d) Existence of Inverse element e) To check properties of binary operation using operation table

    INVERSE TRIGONOMETRIC FUNCTIONS

    1. RECALL ALL THE TRIGONOMETRIC IDENTITIES

  • 2. DOMAIN AND PRINCIPAL VALUE BRANCH OF ALL INVERSE TRIG. FUNCTION The following table gives the inverse trigonometric function (principal branches) along with their domains and ranges

    sin-1 : [-1, 1]

    2,

    2

    cos-1 : [-1, 1] [0, ]

    cosec-1 : R (-1, 1)

    2,

    2

    - {0}

    sec-1 : R (-1, 1) [0, ] {2

    }

    tan-1 : R

    2,

    2

    cot-1 : R (0, )

    3. PROPERTIES OF INVERSE TRIG. FUNCTIONS 4. APPLICATION PROBLEMS

    a) Evaluate the Inverse Trig. Functions b) Evaluating the Problems by using Trig. Identities

    i) a2 + x2 Put x = a tan or x = a cot ii) a2 - x2 Put x = a sin or x = a cos iii) x2 a2 Put x = a sec or x = a cosec

    c) To reduce into simplest form d) To solve :- for the unknown variable x or

    e) Problems involving cos -sin >0 if

    4,0

    &

    sin -cos >0 if

    2,

    4

    &

    MATRICES

    1.Definition 2.Order of a Matrix

    3.Construction of a Matrix of given order &identifying entries(example :Find 23,22,11 aaa etc)

    (Construct a matrix of order 2

    232

    jiaasdefinedareesWhoseentri ij

    )

    4.Types of matrices i)column matrix, ii)row matrix,iii)square matrix, iv)diagonal matrix, v) scalar matrix vi)identity matrix, vii)zero ornull matrix 5.Equality of matrices-Finding the unknown values x,y if given two matrices are equal 6.Matrix operations, i) addition , ii)subtraction , iii)scalar multiplication-(multiply all the entries of the matrix with the scalar k.) , iv)multiplication of matrices-a)Matrix multiplication need not be commutative b)Matrix multiplication is associative c)Product of two non zero matrices can be a zero matrix. 7.Transpose ofa matrix&its properties

    i) AA //

  • ii) TTT ABAB iii)(kA)T=kAT

    TTT BABAiv ) 8.Symmetric&skew symmetric matrices I)AT=A (Symmetric) ii)AT=-A( skew symmetric) 9.Writing a given square matrix as a sum of a symmetric & a skew symmetric matrices.-

    symmetricskewisAA

    symmetricisAA

    /

    /

    //2

    1

    2

    1.10 AAAAA

    11.Elementary row and column transformations. a).If row transformation is used i)Use A=IA Ii)Use only the following three transformations

    ji RR

    ii kRR

    numberrealnonzeroanyiskwherekRRR jii ,

    b).If column transformation is used i)Use A=AI Ii)Use only the following three transformations

    ji CC

    ii kCC

    numberrealnonzeroanyiskwherekCCC jii ,

    12.Finding the inverse of a square matrix using elementary row or column transformations

    13.

    IAAAA

    ABAB

    11

    111

    14.Invertible matrix( Let A and B be two square matrices, if AB=BA =Ithen B is called the inverse of the matrix Aand A is called an invertible matrix. Inverse of A is denoted by A-1)

    CHAPTER DETERMINANTS.

    1. Explain the difference between a matrix and a determinant. Determinant is a number or a function we associate with a matrix.

    2. Determinant of a matrix of order 1 and order 2. 3. Determinant of a matrix of order 3. It can be done by expanding about any row or

    any column. 4. Properties of determinants.

    i) The value of the determinant remains unchanged if its rows and columns are interchanged.

  • ii) If any two rows (or columns) of a determinant are interchanged, then sign of determinant changes.

    iii) If any tworows(or columns) of a determinant are identical then the value of the determinant is zero.

    iv) If each element of a row(or a column of a determinant is multiplied by constant k, then its value gets multiplied by k.

    v) If some or all elements of a row or column of a determinant are expressed as sum oftwo(or more) terms, then the determinant can be expressed a s sum of two (or more) determinants.

    vi) If to each element of any row or column of a determinant, the equimultiples of corresponding elements of other row(or column) are adds, the value of determinant

    remains the same. Ie.RiRi+kRj orCiCi + kCj then value of determinant remains the same.

    5. Solving problems using properties of determinants ie.problems involving proving LHS = RHS using properties.

    6. Finding the area of a triangle using determinants. 7. Finding minors and co-factors.

    8. Aij=(-1)i+jMij

    9. = a11A11+ a12A12 + a13A13.whereAij are cofactors of aij . 10. If elements of a row (or column) are multiplied with cofactors of any other row (or column). Then their sum is zero.

    11. Finding the adjoint and inverse of a matrix. 12. A is singular matrix implies || = 0. 13. || = | || |. But if IAI =IkBIwhere k is a constant then || =kn|| where n is the

    order of Matrix A.

    14. | | = ||n-1 . where n is the order of the square matrix A 15. (1 )T = (AT)-1 16. adj(AT) = (adjA)T 17. |()| = ||(n-1)2

    18. If = [11 1221 22

    ] then adj A =[22 12

    21 11] (Note: to find adjA interchange main

    leading diagonal and change the sign of other diagonal. ) 19. If A is a square matrix of order n then IkAI= knIAI

    20. A-1 = 1

    ||adj A.

    21. (A-1)T=(AT)-1

    22.Working rule for solving of linear equations in 3 variables. Step 1: Express the system of linear equation as AX = B find|| Step 2: If || 0, then the system of equation is consistent and has a unique solution given by X = A-1 B.

    Step 3: If || = 0 and (adjA)B 0, then the system is inconsistent. Step 4: If || = 0 and (adjA)B = 0, then the system may or may not be consistent. In case it is consistent the system has infinite number of solutions.

  • Step 5: In order to find the solutions when system has infinitely many solution, take any one variable equate it to t or k. Find the values of other variables in terms of t or k.

    Topic: Continuity and Differentiability

    Limits

    1. 0

    lim

    = 1

    2. 0

    lim

    = 1

    3. 0

    lim

    = 1

    4. ax

    lim

    = 1

    5. 0

    limx

    1

    = 1

    6. ax

    limlog (1+)

    = 1

    7. Algebra of Limits: ax

    lim()

    ()=

    axlim ()

    axlim ()

    (i) If ax

    lim ()=0 and ax

    lim () 0 limit does not exist

    (ii) If ax

    lim ()=0 and ax

    lim () 0 limit of the

    function is zero

    (iii) If ax

    lim ()=0 and ax

    lim ()=0 then f(x) , g(x) can be factorized or

    rationalized or simplified using trigonometric identities

    Continuity

    Definition -1 A real function f(x) on a subset of real numbers and let a be a point in the domain of f then f

    is continuous at a if )()(lim afxfax

    Example: Find if 0

    limx

    ( 5)

    Deinition-2

    A real function f(x) is said to be continuous at a if )()(lim)(lim afxfxfaxax

    Example: Verify that the following function f(x) is continuous at x = 2

    () = {2 + 3, 22 3, > 2

    Theorem

  • Suppose f and g are real valued function such that fog is defined at c. If g is continuous at c and if f is continuous at g(c) then fog is continuous at c Differentiability

    Y=f(x)

    = ()

    C (constant) 0

    n1 Sinx Cosx

    Cosx -sinx

    Tanx Sec2x

    Secx secxtanx

    Cosecx -cosecxcotx

    Cotx -cosec2x

    ex ex

    Logx 1/x

    sin1 1

    1 2

    cos1 1

    1 2

    tan1 1

    1 + 2

    cot1 1

    1 + 2

    sec1 1

    2 1

    cosec1 1

    2 1

    (u+v) u+v

    u-v u-v

    Uv uv+vu

    2

    1

    2

    1

    1

    2

    loga Result: Every differentiable function is continuous but the converse need not be true Chain Rule

    Let y=vou, t = u(x) and if both

    ,

    exist then

    =

    .

    Derivatives of Implicit and explicit functions Example: = + 2x (Explicit function) + = 0 (implicit function) Differentiation of one function with respect to another function Differentiate sin2x with respect to cosx

  • Take u = sin2x and v=cosx then

    =

    Rules of logarithmic function log = log + log log / = log log log

    =nlog

    Change of base rule log = log

    log

    loge = 1, log1 = 0, log() = ()

    Example: If = + , find

    Solution: y= u+v then

    =

    +

    where = and =

    Parametric Form

    If x=f(t), y = g(t) then

    =

    Second Order Derivatives

    Let y=f(x) ,

    = () = y1 then

    2

    2 = f(x) = y2

    If x=f(t), y = g(t) then 2

    2=

    (

    )

    Rolles Theorem If a real-valued function is continuous on a closed interval [a, b], differentiable on the open interval (a, b), and(a) = (b), then there exists a c in the open interval

    (a, b) such that

    Mean Value Theorem Let be differentiable on the open interval and continuous on the closed interval . Then there is at least one point in such that

    CONCEPT MAPPING INTEGRATION

    1.Integration- as an inverse process of differentiation

  • (sinx) = cosx,

    (3

    3) = 2,

    () =

    We observe that the function cosx is the derivative function of sinx.we say that sinx is

    an antiderivative ( or an integral)of cosx.similarly3

    3 and are the antiderivatives (or

    integrals) of 2and .we note that for any real number c,treated as constant

    function,its derivative is0and hence we can write

    (sinx +c) = cosx,

    (3

    3+ ) =

    2,

    ( + ) =

    Thus antiderivative or integrals of the above functions are not unique.Actually there exists infinitely many antiderivatives of each of these functions which can be obtained by choosing C arbitrarily from the set of real numbers( also called constant of integration).for this reason C is customarily referred to as arbitrary constant.

    More generally

    (F(x) +c)= f(x),x belongs to I

    2.Symbol

    () -- Meaning 3.Comparison between differentiation and integration a. Both are operations on function b. All functions are not differentiable c.All functions are not integrable d .Derivative of a function when it exists it is unique function but the integral of of a function is not so. However they are unique upto an additive constant ie.any two integrals of a function differ by a constant. e. When a polynomial function P(x) is differentiated the result is a polynomial whose degree is one less than the degree of p(x)

    eg.

    (2) = 2x

    When a polynomial function is integrated the result is a polynomial whose Degree is one more than that of p(x)

    Eg.3dx =4

    4 + c

    f. The derivative of a function has a geometrical meaning- the slope of the tangent to the corresponding curve at a point g.Integration- family of curves placed parallel to each other having parallel tangents at the point of intersection of the curves of the family ,with the lines perpendicular to the axis representing the variable of integration. 4.Methods of integration

    Methods of integration 1. Integration by direct method

    Integration by Integration using Integration by Substitution Partial fraction parts Application of Function Partial fraction =uv-

    Trigonometric function+

    ()() -

    () +

    ()

  • In integrals(+)

    () -

    ()+

    ()

    ++

    ()()() -

    () +

    () +

    ()

    Integration of some++

    ()() -

    () +

    () +

    ()

    Particular function++

    ()(++ -

    () +

    +

    ++

    ,

    ,

    ++

    ++ ,

    (+)

    ++,

    (+)

    ++

    SOME SPECIAL INTEGRALS

    1. dx

    2. dx

    3. + + dx

    4.( + ) + + dx

    Definite Integrals

    ()

    - Area of the region bounded by the curve y=f(x) and the ordinates

    x=a,x=b and x-axis

    Calculating ()

    Find the indefinite integral () .Let this be F(x), ()

    = F(b) F(a)

    Definite integrals

    Definite integrals based on Definite integrals Properties of integration types of indefinite integrals as a limit of sum definite integral of modulus fn Some important results.

    1. = +

    + +c

    2. = x+c 3. = -cosx +c 4. = sinx +c 5. x dx = tanx + c 6. x dx = -cotx +c 7. = secx + c 8. = - cosecx + c

    9.

    dx = - +c OR +c

    10.

    +dx = +c OR - +c

    11.

    = +c OR - +c

    12.dx = + c

  • 13.

    dx =log x +c

    14.dx =

    + c

    15.( f(x) +f (x) ) dx = f(x) +c Some Properties of Definite Integrals

    : ()

    = ()

    : ()

    = ()

    : ()

    = ()

    + ()

    : ()

    = ( + )

    ()

    = ( )

    : ()

    = ()

    + ( )

    : () = ()

    ,If f(2a-x)=f(x) =0 if f(2a-x)=-f(x)

    :() ()= (),

    If f is an even function

    (ii) () =

    Limit as a sum

    3. ()

    dx = ( f(a) + f(a+h)+f (a+2h)++f(a+(n-1)h)

    = + + + + = n (n+1)/2 = + + + + + = n (n+1) (2n+1)/6 = + + + + + = [ ( + )/]

    + + + + + = a( )/( ) r 1 INTEGRATION(TIPS TO REMEMBER THE POINTS) 1.Read thoroughly the formulae 2.Prepare a pocket formula dictionary (Writing all the formulae in a note book). 3.Insist the children daily to bring in the class and whenever they get time they should memories the formulae. 4.They have to put those formulae in practice. 5.Daily formula test to be conducted. 6.Students should be practiced so that they can identify the method of integration.

    APPLICATIONS OF INTEGRATION Review

    1. Standard equations of straight lines 2. Equation of circles with Centre at the origin, andcenter at (h,k) 3. Equation of parabolas 4. Equation of ellipse

  • 5. First fundamental theorem of integral calculus 6. Second fundamental theorem of integral calculus

    1.Area under the curve y=f(x)and the x-axis and the ordinates at x=a and

    at x=b is

    .

    2.Area under the curve x=f(y)and the x-axis and the ordinates at y=c and

    at y= d is

    3.The area bounded by the curve y=f(x) and x-axis and the ordinates x=a and x=b is given by A1 +A2=A 4.Area under two curves If y=f(x) , y= g(x) where f(x) g(x) in the [a,b] such that the point of intersection of these two curves are given by x=a and x=b obtained by taking common values of y from given equation of two

    curves then the area between the curves is given by A= [()

    ()] 5.If f(x) g(x) [a,c] and f(x) g(x) in [c,b] where a < c

  • Example: 1 (

    )2= (

    2

    2)

    1

    3

    Degree of a differential equation The degree of a differential equation is the degree of the highest order derivative

    occurring in the equation, when the differential coefficients are made free from radicals if each term involving derivatives of differential equation is polynomial(can be expressed as a polynomial).

    Example: (

    )2+

    = 0

    Verifying the given function as a solution of the given differential equation. General solution and particular solution(Finding values of the constants by using the

    given condition) Formation of differential equation Steps involved

    Write down the given equation of family of curves

    Differentiate the given equation as many times as the number of arbitrary constants.

    Eliminate the arbitrary constants from the given equation and the equation obtained by differentiation. Solving a differential equation:

    Variable separable

    Type-1:

    =

    ()

    (),

    ()

    ()then separate the variables and integrate.

    Type-2:(). () + (). () = , then divide by (). () and integrate.

    Type-3:

    = ( + + ), + + = .

    Homogeneous : If the question is asked to prove homogeneous find (, ) = (, )then f is homogeneous of degree n.

    Step 1: put y= vx and

    = + .

    where v is a function of x alone.

    Step 2: The equation reduce to variable separable and solve.

    Some homogeneous equation can be solved by substituting = .

    Linear Differential equation of type :

    + = , where P and Q are functions of

    x alone or constants.

    Step 1: Identify P and Q.

    Step 2: Find and find (Note: If = (()), then =()).

    Step 3: Solution . = . + .

    Linear Differential equation of type :

    + = , where P and Q are functions of

    y alone or constants.

    Step 1: Identify P and Q.

    Step 2: Find and find (Note: If = (()), then =()).

    Step 3: Solution . = . + .

  • =

    ()+()

    () ""

    =

    ()

    ()+() "".

    =

    ()+()

    () ""

    The equation representing the parabola having vertex at the origin and axis along the positive direction of X-axis- 2 = 4.

    The family of circles touching y-axis at the orgin-( )2 + 2 = 2. The family of circles touching the x-axis: 2 + ( )2 = 2

    VECTOR ALGEBRA

    CONCEPT MAPPING DEFINITION OF Vectors Definition of Scalars Position Vector Dcs and Drs Types of vectors

    Zero Vector Unit Vector

    Unit vector in the direction of + or + + Collinear Vectors Equal Vectors Negative of a Vector Addition of Vectors Multiplication of a Vector by a Scalar Unit Vectors along the coordinate axes. Vector joining two points Section formula

    Dot product of vectors Projection of vectors on a line Perpendicular vectors Finding the angle between the two vectors

    Finding I + I, I + + I, I - I Squaring of a vector Angle between two vectors. Expressing dot product in rectangular coordinates. Cross product of vectors Cross product of unit vectors. Expressing cross product in rectangular coordinates. Unit vector perpendicular to two given vectors. Angle between two vectors. Area of parallelogram when adjacent sides are given. Area of parallelogram when diagonals are given. Area of a triangle Area of a rectangle when position vectors of A,B,C,D are given. Scalar Triple product of vectors.

  • Expressing the STP in rectangular coordinates. Geometrical meaning of STP. Vector Triple Product. Properties of dot, cross and STP

    Dot product Cross product Scalar triple product

    . = | |. | | = | |. | | where is perpendicular to both , .

    Notation is [ , , ]

    If . = If parallel = If coplanar [ , , ] =

    . = | |

    ( . )

    = ( ) + ( )

    + .

    = [ , , ] = if any two vectors are equal.

    If = + +

    = + + Then

    . = + +

    If = + +

    = + +

    Then = |

    |

    If = + +

    = + + = + +

    Then [ , , ] =

    |

    |

    Geometrical meaning

    projection of = .

    | |

    Geometrical meaning

    =

    , Adjacent sides

    Geometrical meaning Volume of a parallelepiped

    with , , as adjacent sides.

    Concept Mapping Topic: 3-Dimensional Geometry.

    1. Direction Cosines and Direction Ratios of a Line.(

    =

    =

    =k )

    2. Relation between the direction cosines of a line. ( +. + = ) 3. Direction Cosines of a line passing through two points P(x1,y1,z1) and Q(x2,y2,z2) 4. Equation of a line in a space

    5. Equation of a line through a given point and parallel to a given Vector 6. Derivation of Cartesian form from vector form. 7. Equation of a line passing through two given points. 8. Derivation of Cartesian form from Vector form. 9. Whenever the Equation of a line or a plane is given it is to see that whether the Equation is in standard form. 10. Angle between Two Lines. 11. Shortest Distance between Two Lines 12. Distance between two skew Lines. 13. Distance between two parallel lines 14. Equation of a plane in normal form& Cartesian form.

    15. Equation of a plane perpendicular to a given vector and passing through agiven point

    16. Equation of a plane passing through three non collinear points. 17. Intercept form of the equation of a plane.

  • 18.Plane passing through the intersection of two given planes. 19.Coplanarity of Two Lines. 20.Angle between Two Planes. 21. Distance of a Point from a Plane. 22.Angle between a Line and a Plane 23. Image of a point w.r.t line and plane. 24. Geometrical interpretation to be given wherever possible. 25. condition for perpendicularity an d parallality of two lines and two planes.

    Summary of the chapter:

    .

  • Probability

    CONCEPT MAPPING:

    Introduction Concepts in probability

    CONDITIONAL PROBABILITY PROPERTIES OF CONDITIONAL PROBABILITY

    MULLTIPLICATION THEOREM ON PROBABILITY Probability

    Enumerating outcomes

    INDEPENDENT EVENTS PARTITION OF SAMPLE SPACE

    THEOREM OF TOTAL PROBABILITY

    BAYES THEOREM and ITS APPLICATIONS

    RANDOM VARIABLE AND ITS PROBABILITY DISTRIBUTION

    MEAN OF A RANDOM VARIABLE FORMULA TO FIND THE VARIANCE OF A RANDOM VARIABLE

    BINOMIAL DISTRIBUTION (BERNOULLI TRIALS)

    PROBLEM SOLVING BASED ON BAYES THEOREM& BERNOULLI TRIALS

    Formatted: Font: 12 pt, Complex Script Font:12 pt

  • PROBABILITY Experiments Sample Space(S) Events(A,B,C,E,F,G,.) Conditional Probability If E and F are two events associated with the same sample space of a

    random experiment, the conditional probability of the event E given that F has occurred, i.e. P (E|F) is given by P(E|F) =P(E F)/P(F) provided P(F) 0

    Properties of conditional probability: Let E and F be events of a sample space S of an experiment, then we have

    Property 1:P(S|F) = P(F|F) = 1 Property 2: If A and B are any two events of a sample space S and F is an event of S such that P(F) 0, then

    P((A B)|F) = P(A|F) + P(B|F) P((A B)|F) Property 3:P(E|F) = 1 P(E|F) Multiplication Theorem on Probability P(E F) = P(E) P(F|E) = P(F) P(E|F), provided P(E) 0 and P(F) 0 Multiplication rule of probability for more than two events:If E, F and G are

    three events of sample space, we have P(E F G) = P(E) P(F|E) P(G|(E F)) = P(E) P(F|E) P(G|EF)

    Independent Events:

    Two events E and F are said to be independent, ifP(F|E) = P (F) provided P (E) 0 and P (E|F) = P (E) provided P (F) 0 Let E and F be two events associated with the same random experiment, then E and F are said to be independent ifP(E F) = P(E) . P (F)

    Partition of a sample space Let {E1, E2,...,En} be a partition of the sample space S, and suppose that each of the events E1, E2,..., En has nonzero probability of occurrence. Let A be any event associated with S, then P(A) = P(E1) P(A|E1) + P(E2) P(A|E2) + ... + P(En) P(A|En)

    Theorem of total probability P(A) = P(E1) P(A|E1) + P(E2) P(A|E2) + ... + P(En) P(A|En)

    Bayes Theorem If E1, E2 ,..., En are n non empty events which constitute a partition of sample space S, i.e. E1, E2 ,..., En are pairwise disjoint and E1 E2 ... En = S andA is any event of nonzero probability, then

    P(/) = ( ) (| )

    ( ) (| )=for any j =1,2,3,..,n

  • Random Variables and its Probability Distributions

    o Probability distribution of a random variable

    The probability distribution of a random variable X is the system of numbers

    X :x1 x2 .. . xn P(X) :p1 p2 . .. pn

    where,x1,x2, .xnare the possible values of the random variable X and pi (i = 1,2,..., n) is the probability of the random variable X taking the value xi

    pi = 1, i = 1, 2,..., n i.e. P(X = xi) = pi

    A random variable X has the following probability distribution:

    X 0 1 2 3 4 5 6 7

    P(X) 0 K 2K 2K 3K 7k2 +k

    o Mean of a random variableE (x)= = =1 pi

    o Variance of a random variableE (x2)= 2

    =1

    Bernoulli Trials and Binomial Distribution o Bernoulli trials

    Trials of a random experiment are called Bernoulli trials, if they satisfy the following conditions : (i) There should be a finite number of trials. (ii) The trials should be independent. (iii) Each trial has exactly two outcomes : success or failure. (iv) The probability of success remains the same in each trial.

    o Binomial distribution The probability of r successes P(X = r) is denoted by P(x) and is given by P(X =r) =nCrqnrpr,r = 0, 1,..., n. (q = 1 p) This P(x) is called the probability function of the binomial distribution. A binomial distribution with n-Bernoulli trials and probability of success in each trial as p, is denoted by B(n, p).

    P(at least r successes),

    P(at most r successes),

    P(exactly r successes)

    P(r>3), P(r