Syllabus
Unit I
Sample Space and Events, Interpretations and Axioms of Probability, Addition rules, Conditional Probability, Multiplication and Total Probability rules, Independence, Bayes theorem.
Random variables, Probability Distributions and Probability mass functions, Cumulative Distribution functions, mathematical expectation, variance, moments and moment generating function.
Unit II
Standard discrete distributions – Binomial, Poisson, Uniform, Geometric distributions, Negative binomial and Hypergeometric Distributions -Standard continuous distributions – Uniform, Exponential, Gamma, Beta and Normal distributions. Chebyshev’s theorem. Two dimensional random variables-Joint, marginal and conditional probability distributions for discrete and continuous cases, independence, expectation of two dimensional random variables – conditional mean, conditional variance, covariance and correlation.
Unit III
Tests of Hypotheses: Tests of Statistical Hypotheses, One-Sided and Two-Sided Hypotheses, P-Values in Hypothesis Tests, General Procedure for Hypothesis Tests, Tests on the Mean and Variance. F, t and Chi-square tests.