StatisticsSTAT 203 Introduction to Probability Theory

Introduces probability theory and its applications. Requires a multivariate calculus background, but has no measure theoretic content. Topics include: combinatorial analysis; axioms of probability; random variables (discrete and continuous); joint probability distributions; expectation and higher moments; central limit theorem; law of large numbers; and Markov chains. Students cannot receive credit for this course and course 131 or Computer Engineering 107. (Formerly AMS 203.)

Requirements

Enrollment is restricted to graduate students, or by permission of the instructor.

Credits

5

Quarter offered

Fall

Instructor

The Staff, Raquel Prado, Athanasios Kottas, Bruno Sanso, Ju Hee Lee