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Course Contents

Probability: Sample space, events and probability; Conditional probability and independence; Random variable (RV); Expectation, variance and higher moments; Some standard probability distributions; Functions of RVs; Jointly distributed RVs; Some multivariate distributions; Sum of RVs; Limit theorems. Statistics: Population and sample; Sampling distributions; Properties of point estimators; Maximum likelihood method; Interval estimation; Hypothesis testing; Some standard hypothesis tests; Analysis of variance; Simple linear regression; Multiple linear regression; Goodness of fit tests. Textbooks 1) H. J. Larson, Introduction to Probability Theory and Statistical Inference, John Wiley & Sons. 2) R. V. Hogg, A. T. Craig, and J. W. McKean, Introduction to Mathematical Statistics, Pearson Education. 

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