Quantitative Methods in the Social Sciences I, 7.5 credits

The objective of the course is to provide a comprehensive introduction to regression analysis and its uses and limitations. The focus of the course is on linear regression analysis of continuous dependent variables, but it also introduces to logistic regression analysis. The course covers both bivariate regression and multivariate regression analysis. Within these topics, we discuss confounding and indirect effects, interaction effects, variable transformations, outliers, heteroscedasticity, and multicollinearity. Specific attention will be paid to considerations of which research questions the different methods can answer as well as the presentation and interpretation of the results, including their limitations.

The course requires prior knowledge on quantitative data analysis. Previous experience of the statistics software Stata is recommended. The course is also suitable for those who want to refresh their regression analysis skills. The course prepares for advanced courses in quantitative research methods, such as Quantitative Methods in the Social Sciences 2, SO7033.