MA 361: Probability Theory

Credits: 3:0


Prerequisite courses: MA 222

Probability measures and randown variables, pi and lambda systems, expectation, the moment generating function, the characteristic function, laws  of large numbers, limit theorems, conditional contribution and expectation, martingales, infinitely  divisible laws and stable laws.


Suggested books and references:

  1. Durrett, R., Probability: Theory and Examples (4th Ed.) ,Cambridge University Press, 2010.
  2. Billingsley, P., Probability and Measure (3rd Ed.) ,Wiley India, 2008.
  3. Kallenberg, O., Foundations of Modern Probability (2nd Ed.) ,Springer-Verlag, 2002.
  4. Walsh, J., Knowing the Odds: An Introduction to Probability ,AMS, 2012.

All Courses


Contact: +91 (80) 2293 2711, +91 (80) 2293 2265
E-mail: chairman.math[at]iisc[dot]ac[dot]in