Course content

The content of the course varies. It may be given as an overview course, covering several statistical techniques and methods - such as multilevel analysis, panel data analysis or structural equation models - or it may be concentrated on one technique. The course may also link the analytical techniques to advanced rules and aspects of conducting social research, including research designs and data collection/evaluation techniques. Please consult the course coordinator to receive more information about the exact course content of this year.

Learning outcome

Knowledge - the student shall:

• achieve insight and understanding into one or more techniques in applied statistical data analysis.

Skills - the student shall demonstrate the ability to:

• be able to apply the learned techniques in a practical manner (using Stata and/or R)
• demonstrate the ability to use one of the analytical techniques addressed during the course in an independent manner through written work

Learning methods and activities

Intensive lectures/seminars (full days), normally during one week in the beginning of the semester (often the very first week). The sessions consist of a mix of theory and practice, that is, the presented topics and techniques will be subsequently applied in a practical manner (using Stata and/or R).If less than 6 students plan to attend the course, the course may be given as an individual study course with supervision. Students will be informed if this will be the case.

Compulsory assignments

• Participation on lectures and seminars

Recommended previous knowledge

See required previous knowledge.

Required previous knowledge

SOS3003 or SOS3005 or the equivalent. The requirement must be fulfilled to be admitted to the course.

Course materials

To be announced at the beginning of the semester.

Credit reductions