This course serves as a foundational course for students who enter computer science department for graduate studies. Most of the engineering students, in their under graduation, do not get formal exposure to probability. This course is designed to fill this gap. This course also emphasizes rigorous reasoning which is essential for graduate studies in computer science.
Probability spaces, random variables and expectation, moment inequalities, multivariate random variables, sequence of random variables and different modes of convergence, law of large numbers, Markov chains, maximum likelihood estimators, statistical hypothesis testing, Neyman-Pearson lemma, exponential models.
- An Introduction to Probability and Statistics by Vijay K. Rohatgi, A. K. Md. Ehsanes Saleh, Wiley, 2nd
- An Intermediate course in Probability by Allen Gut, Springer, 2008.
- Introduction to Probability Models by Sheldon Ross, Academic Press, 10th Edition, 2010.
- Introduction to Probability by Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, 2nd Edition, 2008.