Nijmegen, Netherlands

Regression 1: Linear Regression

when 20 June 2022 - 24 June 2022
language English
duration 1 week
credits 2 EC
fee EUR 575

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


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.

Credits info

2 EC
2 ECTS credits, with the possibility of an extra 1-3 ECTS credits depending on additional course work and assignments handed in during or after the summer school (for a possible total of up to 5 ECTS).

Fee info

EUR 575: The fee includes the registration fees, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.


We offer several reduced fees:
€ 518 early bird discount- deadline 1 April 2022 (10%)
€ 489 partner + RU discount (15%)
€ 431 early bird + partner + RU discount (25%)

Register for this course
on course website