Data AnalysisSpotlights - I

M.Elkharashy

Introduction

● Variables Types● Analysis Types● Random Samlping Vs Assignment● Exploring Numerical Variables

o Mesures of Centero Robust Statistics

● Exploring Categorical Variables

Variables Types

Quantitive/Numberical● Continuous ● Discreate

Qualitative/Categorical

● Regural● Ordinal

Notes:It can be represented by numbers, but without any arthimatic operations.Ordinal: variables that have ordered levels.

Variables Types

Dependent/Associated● +ve association ● -ve association

Independant

Analysis Types

Observational Study● Merely “Observe”● Retrospective/Prespective

use data (from past/ throughout the study)

● Can only establish an association between the explooanatory and response variables.

Experiment

● Randomly assign subjects to various treatments.

● Can establish causal connections between the explanatory and response variables.

Random Sampling

Random Assignment

ideal experiment

most experiments

most opeservational studies

bad observational studies

Exploring Numerical Variables

Dot PlotUseful when individual values are of

interest

Histogram

Box Plot

Useful for highlighting outliers, median, and the interquartile range.

Intensity MapUseful for highlighting the spacial distribution

Mesures of Center

Mesures of Center

Sample Statistics/Point Estimates● mean: arithmetic average ● median: midpoint of the distn. (50th

percentile)● mode: most frequent observation

Mesures of Center

Skewness Vs Mesures of Center

Robust Statistics

Robust Statistics

As a mesure on which extreme observation have little effect

Robust Statistics

As a mesure on which extreme observation have little effect

Exploring Categorical Variables

Exploring Categorical Variables

● Exploring single categorical variable.● Exploring the relationship between two

categorical variables● Exploring the relationship between a

numberical variable and categorical variable

1- Single Categorical VariableFrequency Table & Bar Plot

1- Single Categorical VariablePie Chart

Contingency Table

2- Relationship between 2 categorical variables

Segmented Bar Plot

2- Relationship between 2 categorical variables

Relative Freq. Segmented Bar Plot

2- Relationship between 2 categorical variables

Mosaicplot

2- Relationship between 2 categorical variables

Side-by-Side Box Plots

3- Rel. bet. numberical & categorical variables

● Disjoint events Vs independent process● Conditional probability & probability

trees● Normal distribution ● Binomial distribution● Centeral Limit Theorem (CLT)● Confidence Interval● Introductoin to Inference

In Next Session

● Another introduction to inference● Hypothesis testing(for mean)

o p-valueo test statistics (Z & T)o ANOVA

● Hypothesis testing(for proportion)o Chi-Square (GOF & Independence Test)

● Frequentist Vs Bayesian Inference● Linear Regression

In 3rd Session

Questions?