Catalog Course Description

An introduction to probability, emphasizing the combined use of mathematics and programming. Discrete and continuous families of distributions. Bounds and approximations. Transforms and convergence. Markov chains and Markov Chain Monte Carlo. Dependence, conditioning, Bayesian methods. Maximum likelihood, least squares prediction, the multivariate normal, and multiple regression. Random permutations, symmetry, and order statistics. Use of numerical computation, graphics, simulation, and computer algebra.

Spring Term

3 hours of Instructor presentation of course materials per week and 7 to 8 hours of Outside Work Hours per week and 0 to 1 hours of Extra meetings for the review or elaboration of course materials per week and 2 hours of The exchange of opinions or questions on course material per week.

Fall Term

3 hours of Instructor presentation of course materials per week and 7 to 8 hours of Outside Work Hours per week and 0 to 1 hours of Extra meetings for the review or elaboration of course materials per week and 2 hours of The exchange of opinions or questions on course material per week.

Statistics 140