TLBPRA2 Praksisperiode 2 Emneplan

After completing the course, student should have the following overall learning outcomes defined in terms of knowledge, skills, and general competence:

Knowledge

The student has

• advanced knowledge about different quantitative designs and data and variable formatting.
• advanced knowledge about the use of different regression models to analyse social science topics.
• broad knowledge about different quantitative analysis techniques and how to interpret their results.
• broad knowledge about the possibilities and limitations of various statistical procedures

Skills

The student is capable of

• understanding quantitative research articles and their methodological strengths and weaknesses.
• choosing appropriate analysis techniques given specific research questions and data.
• working independently with practical data preparation, analysis, and interpretation of quantitative data.
• using the statistical tool Stata for research purposes
• presenting statistical results in assignments and articles

General competence

The student is capable of

• applying skills in quantitative method in new areas to conduct job assignments and projects.
• critically assessing results from different research designs and from different types of statistical analyses
• Interpreting and communicating empirical results in an appropriate manner.

The course consists of lectures, seminars and group supervision on campus, and e-lectures. The main emphasis is on student active teaching in the form of workshops.

No coursework requirements or compulsory activities.

The exam in the course is an individually written report in article format. The article must have a scope of 10 pages (+/- 10 percent). Font and font size: Calibri 12 points. Line spacing:1,5.

Students awarded a fail grade are given one opportunity to submit an improved version of the article for assessment.

All aids are permitted, as long as the rules for source referencing are complied with.

Grade scale A - F.

The exam papers are assessed by one internal and one external examiner.

A random selection consisting of at least 25 % of the exam papers will be graded by both an internal and external examiner. This will inform the grading of the remaining exam papers.

Mats Lillehagen