Pre-requisites : NIL
Combinatorial analysis, axioms of probability, conditional probability and stochastic independence, the binomial, Poisson and normal distributions, random variables, expectation, laws of large numbers, limit theorems, random walks, Markov chains. Linear equations, vector spaces, linear transformations, inner products, determinants, eigenvalues.
1. W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd Ed., Wiley, 1968.
2. K. Hoffman and R. Kunz, Linear Algebra, 2nd Edition, PHI, 1971.
1. S. Ross, A First Course in Probability, 6th Ed., Pearson Education India, 2002.
2. C. M. Grinstead and J. L. Snell, Introduction to Probability, 2nd Ed., Universities Press India, 2009.
3. D. S. Watkins, Fundamentals of Matrix Computations, 2nd Edition, Wiley, 2005.
4. Gilbert Strang, Introduction to Linear Algebra, Wellesley-Cambridge Press, 2009.