Multiple Regression Analysis
Techniques and assumptions of regression models, data management, and analysis. Topics include ordinary least squares, binary, ordinal, and multiple logistic regression, and models for count variables.
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesMFHD 513; or MFHD 691
Course Outcomes: 

Statistical Understanding

STudents will understand and utilize univariate, bivariate, and multivariate statistics commonly used in the social and behavioral sciences. Students will gain familiarity with Stata (a statistical programming package), how to organize and pursue a research project, and how to present results.

Quantitative Analysis

Students will conduct sophisticated analyses of quantitative data, including cleaning the data and checking the assumptions of each model. The course also focuses on the integrity of the research process to ensure the analysis meaningfully represents the data.