Course Code and Name: MAT5019- Stochastic Models and Applications
(July-December, 2024-25)
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Classes: Thursday, 3:00-4:30 pm; Friday, 9:30-11am, Tutorial: 1:45-2:45 pm
Instructor: Manikandan Rangaswamy
Prerequisites: Basic Probability
Syllabus:
Probability spaces, conditional probability, independence, random variables, distribution functions, multiple random variables and joint distributions, functions of random variables, moments, characteristic functions and moment generating functions, conditional expectation, sequence of random variables and convergence concepts, laws of large numbers, central limit theorem, stochastic processes, Markov chains, Poisson process.
Textbooks:
1. Ross S. M, Introduction to Probability Models, 10th Edition, Academic Press, 2012.
References:
1. P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, 1971. 2. P. G. Hoel.
S. C. Port and C. J. Stone, Introduction to Stochastic Processes, 1972
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