245  Fundamentals of Engineering Statistics. Fall, Spring  QR 
A study of fundamentals of statistical methods and their applications in engineering. Basic concepts of probability, discrete and continuous distributions, sampling and quality control, statistical inference, empirical models, and least squares. Three lectures. Open to freshmen. R. A. Carmona, E. H. Vanmarcke.
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309  Probability and Stochastic Systems 
(also Mathematics 309 and Electrical Engineering 380). Fall 
An introduction to probability and its applications. Random variables, expectation, and independence. Poisson processes, Markov chains, Markov processes, and Brownian motion. Stochastic models of queues, communication systems, random signals, and reliability. Prerequisite: Mathematics 201, 203, 217, or instructor's permission. E. Cinlar. 
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405 Regression and Applied Time Series. Fall 
Robust and nonparametric techniques for time series encountered frequently in engineering and industrial applications. Regression analysis for de-noising or smoothing. Includes a final project in the form of a realistic forecasting game involving portfolio management and economic time series data. Prerequisite: 245 and Mathematics 202. R. A. Carmona. 
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406  Statistical Design of Experiments. Spring 
Major methodologies of statistics as applied to the engineering and physical sciences. The central theme is the construction of empirical models, the design of experiments for elucidating models, and the applications of models for forecasting and decision making under uncertainty. Three lectures. Prerequisite: 245 or equivalent. C. A. Peters. 

Mathematics