Course Description
An applied course in regression providing the necessary theory, rigor, and applications useful in practice. Application areas include forecasting, driver modeling, and analysis of variance for experiments. Students work with real-world data sets and relevant software.
Athena Title
Regression Models for Mark Dec
Pre or Corequisite
Permission of department
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
• Understand the structure and assumptions of regression and ANOVA models. • Develop the ability to assess the appropriateness of models for different applications and apply remedial measures where needed. • Understand the benefits provided by regression models in marketing applications and how to properly interpret, utilize, and communicate results. • Develop hands-on model building and application skills utilizing relevant software.
Topical Outline
• Simple Linear Regression Model o Parameter Inference o Prediction • Multiple Linear Regression Model o Parameter Inference o Prediction • Regression Diagnostics • Remedial Measures • Qualitative Predictor Variables • Multicollinearity • Model Building and Validation • Analysis of Variance and Experimental Design
Syllabus