BMGT 430
Data Modeling in Business
Explores the role of statistical models in business analytics to drive managerial decision-making and improve performance through the use of relevant data-motivated examples. Topics include regression models (both simple and multiple regression, as well as logistic regression for binary data), model validation, variable transformation, variable selection, discriminant analysis, and forecasting. These topics are modeled using state-of-the-art data analytics software.
Topics
- regression models (both simple and multiple regression
- as well as logistic regression for binary data)
- model validation
- variable transformation
- variable selection
- discriminant analysis
- and forecasting
Topics explicitly listed in official catalogue description
Prerequisites & course information
Prerequisite: BMGT231 or BMGT230 ; or permission of BMGT-Robert H. Smith School of Business.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Data Modeling in Business · 3 Credits