Applied Regression and Data Analysis

Course Code
TO 566
Hours
1.5 hours
Type
Elective
Offered
  • Winter 21 (A)
  • Winter 22 (A)
Prerequisites
Graduate Standing or (preceded or accompanied by TO 701 or 501)

Data Mining using Regression Analysis --- The course considers procedures for data collection, effective analysis, and interpretation for management control, planning, and forecasting. The course stresses the capabilities and limitation of statistical methods together with the considerations necessary for their effective application and correct interpretation. The course focuses primarily on multiple regression models, which includes weighted least squares, analysis of variance, and analysis of covariance. Readings, cases, examples and exercises are drawn from diverse areas of business, including finance, marketing research, accounting, economics and general management.

Taught By
Jun Li
  • Associate Professor of Technology and Operations
  • Michael R. and Mary Kay Hallman Fellow
I conduct research in empirical operations management and business analytics spanning areas across revenue management and pricing, healthcare...