Course No:           Act 414

Course Name:      Probability Theory - 2

Course Description:      

a)    Conditional Probabilities. Theorems on conditional probability for two and more events, and its applications In sampling without replacement, Polya’s urn model, Ehrenhest Model of heat exchange, theorems on Independence for 3 and more events etc

b) Random Variables, Univariate and Bivariate probabilities and its applications in random placement problems, Bivariate Poisson, Mathematical expectations, variance and correlation coefficient. Chebyshev's inequality laws of large numbers.

c) Generating Functions, Recurrent events Renewal theory. Markov Chains with examples & applications. `Transition Matrices, Chapman Kolmogrove identity, classification of states, higher transition probabilities.

Course Review:      

This course aims on the conditional probabilities, random variables, univariate and bivariate probabilities in random placement problems, bivariate Poisson distributions, mathematical expectations, variance and correlation coefficient, Chebychev’s inequality and law of large numbers, recurrent events and renewal theory, generating functions, Markov chains with examples and applications, Chapman-Kolmogrov identity, classification states and higher transition probabilities.