Three hours of lecture and one and one-half hours of lab per week. Introduction to Probability. See Mathematics 425. 426. Introduction to Mathematical Statistics. This course covers the basic ideas of statistical inference, including sampling distributions, estimation, confidence intervals, hypothesis testing, regression, analysis of variance, nonparametric testing, and Bayesian inference.
Weekly problem sets, two hourly exams, and one final exam.
Discrete State Stochastic Processes. An introduction to Brownian motion, stationary processes, or martingales. Statistical Analysis of Time Series. Special topics might include vector autoregression, cross-spectral analysis, causality testing or other issues of current interest. Statistics 511 or Economics 775 is the standard prerequisite.