Quantitative Methods in the Social Sciences 2
The course deals with advanced applications of linear regression (such as interactions, transformations, marginal effects, testing hypothesis, decomposition methods, measurement errors), linear regression extensions (multilevel and panel data models), as well as models for discrete outcomes (binary, ordered and multinomial logit).
In the course, emphasis is placed on the craft, i.e., to implement, understand and interpret analyzes with the aforementioned methods rather than statistical theory, although some statistical theory is included as part of the deeper understanding required by the course. In addition, the course provides an overview of research traditions in quantitative social sciences (such as experiments, quasi experiments, observation data models) as well as the problems of causality. The course focuses on computer exercises where the course participants themselves work with analyzing a data material.
Course PM - all you need to know
Teaching is given in the form of lectures, practical exercises in a computer room, as well as seminars.
The course is examined through assignments, most of which are based individual computer exercises, but also on interpretations of existing analyzes. The assignments are conducted in groups and individually.
Professor of Sociology Martin Hällsten
ScheduleThe schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.