Institution: German Institute of Global and Area Studies (GIGA)
Lecturer: Dr. Steffen Mohrenberg, Zürich
Place: GIGA, Neuer Jungfernstieg 21, 20534 Hamburg, Germany
Registration: Online via the GIGA website
Day 1: Intro to linear and logistic regression
This first day of the seminar is meant as an introduction to regression analysis for social scientists with no previous background in statistics and regression. We cover the basics of linear regression and logistic regression, and focus on using regression techniques for data description. We do not go into detail on statistical inference and causal inference with regression.
Day 2: Presenting and commenting on regression results the smart way
During the second day of the seminar, we discuss multiple ways how identical regression results can be presented. We assume that the goal of such a presentation is not a thorough and complete coverage of all mathematical and technical details. Instead, such a presentation is intended to enable an audience with diverse scientific backgrounds to understand the most important aspects of the results and to give comments that may help the author to improve her/his research. While the first day of the seminar was mostly lectures and short exercises, this second day will have a workshop character. Given interest and time, individual participants may give short presentations of their own work. This is not meant as a platform for substantive feedback about participants’ PhD theses but rather as a possibility to acquire specific presentation skills for future colloquia. Participants who are interested in giving such a presentation are kindly asked to submit a short outline together with their course registration.
About the lecturer
Dr. Steffen Mohrenberg is a postdoctoral researcher at the Department of Humanities, Social and Political Sciences at ETH Zurich. In the past, Steffen worked as an academic staff member (wissenschaftlicher Mitarbeiter) at the University of Hamburg, where he taught political science research methods, data analysis and visualization using R, and courses on social network analysis.