MA 2110 - Introduction to Probability

Syllabus

  • Basics : Sample space and events, definitions of probability, properties of probability, conditional and Bayesian probabilities.
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  • Random variables : Distribution functions, Discrete and continuous random variables, moments of random variables, Chebyshev and Markov inequality, functions of random variables.
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  • Special Distributions: Bernoulli, Binomial, Geometric, Poisson, Exponential, Uniform, Normal distributions.
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Reference Text

  • Oliver C Ibe, Fundamentals of Applied Probability and Random Processes (2nd Edition), Academic Press, (2014).
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  • P L Meyer, Introductory Probability Theory and Statistical Applications (2nd Edition), Oxford & IBH Publishing Co (1970).
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  • Sheldon Ross, A First Course in Probability (9th Edition) Pearson (2012).
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  • Athanasios Papoulis, S. Unnikrishna Pillai, Probability, Random Variables and Stochastic Processes, (4th Edition), Tata McGraw Hill (2002).
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  • Geoffrey Grimmett and David Stirzaker, Probability and Random Processes (3rd Edition) , Oxford Press (2001).
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Assignments