Regression 1: Linear Regression

About

This course is offered as part of the Radboud Summer School in Social Research Methods, in collaboration with MethodsNET (a global network that offers excellent training in social research methods).

A course on the theory and application of one the most widely applied methods in the social sciences: linear regression analysis. Learn about what it is, how it works, when it’s (not) useful.

Course leader

Alex Lehr Assistant professor Department of Political Science Radboud University

Target group

-Master
-PhD
-Post-doc
-Professional

This PhD level course is open to all researchers aiming at bringing their research to the next level. It is particularly designed for those in need of a(n) introduction or refresher on linear regression, including those in need of building a solid basis before taking more advanced follow-up courses.

Course aim

After this course you are able to:

-Better understand the role and theory of regression analysis in the context of theory-testing social science research;
-Interpret (simple and multiple) linear regression models when they include continuous and categorical predictor variables, when they include non-linear effects (through the inclusion of polynomial, exponential and logarithmic functions), and when the include interaction terms (moderation analysis);
-Better understand the benefits and limitations of regression analysis for making inferential statements, including statements about causality;
-Better understand how these limitations are related to uncertainty in (frequentist) inferential statistics in general, and the assumptions associated with the linear regression model in particular.

Fee info