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