3.0

credits

Average Course Rating

This course introduces students to multiple regression as a tool for inferential statistics in the social science, with a focus on applications to education research. Students will begin with a review of basic statistical concepts, then move on the basics of linear regression including model assumptions, estimation, and statistical inference. Emphasis will be placed on interpreting coefficients, assessing model fit, and critiquing empirical studies. We will review methods for specific types of data in the linear model, including categorical variables, interactions, data transformations and limited dependent variables. Finally, students will consider the limitations of regression and diagnostics for challenges including missing data and outliers. This course is designed for students who have had at least a one-semester introduction to statistics. Students should have existing knowledge of probability theory, properties of distribution and random sampling, and basic statistical tests.