Course content

This course covers applied statistical data analysis with continuous and categorical variables. The emphasis will be on regular OLS analysis and how this can be used to examine various relationships between dependent variables (Y) and a set of continuous explanatory variables (X). The students are also introduced to logit regression and other techniques applied when Y is a categorical variable. Emphasis is placed on methods to test whether the model assumptions are credible.

Learning outcome

Knowledge - the student shall:

• be able to read academic literature in the social sciences where regression models are used and with critical insights in the context of modeling assumptions and analysis results

Skills - the student shall demonstrate the ability to:

• carry out analyses with the help of the analytical models in which they received instruction

Learning methods and activities

Teaching methods and activities: Lectures, seminars and PC-labs equivalent to 6 hours pr week. Supervision of term paper. The paper is to be an independent discussion of a topic taught in lectures, and is to consist of 20 pages. If 6 or fewer students sign up for a planned course during the first 2 teaching weeks, the course will be offered as an instructed reading course.

Recommended previous knowledge

SOS1002.

Required previous knowledge

15 credits quantitative research methods in the social sciences.

Course materials

To be decided at the start of the course.

Credit reductions