MA 261: Probability Models

Credits: 3:0


Sample spaces, events, probability, discrete and continuous random variables, Conditioning and independence, Bayes’  formula, moments and moment generating function, characteristic function, laws of large numbers, central limit theorem, theory of estimation, testing of hypotheses, linear models.  


Suggested books and references:

  1. Ross, S.M. , Introduction to Probability Models, Academic Press 1993.
  2. Taylor, H.M., and Karlin, S., An Introduction to Stochastic Modelling, Academic Press, 1994.

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Contact: +91 (80) 2293 2711, +91 (80) 2293 2265 ;     E-mail: chair.math[at]iisc[dot]ac[dot]in
Last updated: 11 Dec 2023