ST102 - Introduction to Probability Theory
Counting Techniques: Combinations, Permutations, Set partitions, Elements of Probability: Experiments, Events, Sample space, Laws of Probability, Bayes' Theorem, Independence of events. Random variables: Discrete and continuous r.v.'s, Probability mass function, Probability density function, Cumulative distribution function, Functions of a random variable, Expectation, Moments, Mean and variance, Moment Generating function.
Probability inequalities: Chebyshev's and Markov's etc.
Distributions: Discrete: Uniform, Bernoulli & Binomial, Poisson, Geometric, Negative Binomial, Hypergeometic, Multinomial, Continuous: Uniform, Normal, Gamma, Exponential, Properties and applications of distributions, Probability Generating functions.
Approximation to Binomial using Poisson, Binomial using Normal, and Poisson using Normal.
- Applied Probability and Statistical Methods, G.C.Canovos
- A Basic Course in Statistics, G.M.Clarke and D. Cooke
- A Course in Probability & Statistics , C.J. Stone