This is an intermediate applied statistics course designed for students who have already taken one course in elementary concepts (e.g., sampling and statistical inference). The course covers the use, interpretation, and presentation of bivariate and multivariate linear regression models, curvilinear regression functions, dummy and categorical variables, and interactions; as well as model selection, assumptions, and diagnostics. Examples and assignments will draw from commonly-used large-scale educational datasets. Students are encouraged to use Stata; the course will also serve as an introduction to this software package (students may instead choose to use SPSS or other software they are familiar with). The objective of the course is to equip students with the skills to use, interpret and write about regression models in their own research.