Regression analysis: multiple linear regression, diagnostics, and variable selection. Forecasting: exponential smoothing techniques and autoregressive moving average models. 

Small groups of students undertake an industry-sponsored project under faculty guidance.

Topics include conditional probability, density and distribution functions from engineering, expectation, conditional expectation, laws of large numbers, central limit theorem, and introduction to Poisson Processes.

Practical analytics project experience applying ideas from the classroom to a significant project of interest to a business, government agency, or other organization.

Courses in special topics of timely interest to the profession, conducted by resident or visiting faculty.