1Have basic understanding of the General Linear Model, the data requirements for ordinary least squares regression analyses, and the computational details of simple, multiple, and hierarchical regression analyses.

2Use multiple regression analysis as a general approach to research design and data analysis for studies with multiple predictors, sets, mediators, moderators, and within-subjects factors;

3Interpret and critique results of correlation and multiple regression analyses appearing in the literature;

4Apply multiple regression analyses to data of their own;

5Write-up the results of multiple regression analyses;

6Prepared to take additional advanced statistics courses that build on multiple regression, including logistic regression, multi-level modeling, and structural equation modeling.