Advanced Quantitative Methods

Course content

The course introduces students to advanced regression analysis and its application in sociological research with a special focus on causal analysis. The student acquires knowledge of

 

· Multiple linear regression,

 

· Interaction effects,

 

· Selection of control variables for regression models,

 

· OLS Assumptions,

 

· Regression analysis of experimental studies,

 

· Regression analysis of natural experiments using instrument variables and regression discontinuity designs.

 

The student must be able to explain these topics. The student must be able to further explain the logic behind the use of regression analysis for the estimation of causal effects. Finally, the student must be able to reflect on the possibilities and limitations of the use of regression analysis in sociological research.

Education

Compulsery course on the 3rd semester BSc in Sociology.

Credit and exchange students must be at bachelor level. 

Learning outcome

KNOWLEDGE:

The course introduces the student to regression analysis and its application in sociological research. The student acquires knowledge of
 

- Multiple linear regression,

- Interaction effects,

- Statistical tests and their use in regression analysis,

- OLS assumptions behind regression analysis,

- Selection of control variables,

- Regression analysis of experimental studies,

- Regression analysis of natural experiments using

 

SKILLS:

The course gives the student the opportunity for practical mastery of regression analysis in R. Students will be able to:
 

- Perform multiple regression analysis,

- Interpret regression coefficients,

- Use statistical tests to test hypotheses,

- Select relevant control variables,

- Specify interaction effects,

- Apply instrument variable regression,

- Apply regression discontinuity designs,

- Perform model checks,

- Present and communicate results based on regression analysis in relation to a given problem,

- Critically evaluate its empirical results.

 

KOMPETENCE:

After completing the teaching, the student must be able to:

- Acquire further advanced quantitative methods such as factor analysis, multilevel models or panel data analysis.

- Translate his knowledge and skills into advanced quantitative analyses for research and consulting.

- Be able to plan and carry out reports or reports involving regression analysis.

Lecture, tutorial, and regular statistics tasks using R.

De Veaux, Richard, Paul F. Velleman, and David E. Bock. 2016. Stats. Data and Models. Boston: Pearson & Addison Wesley.

Angrist, Joshua D., and Jörn-Steffen Pischke. 2014. Mastering ’Metrics: The Path from Cause to Effect. Princeton University Press.

Students must have mastered “Basic Statistics”.

Requirement: Own laptop with running and updated versions of RStudio and R.

Peer feedback (Students give each other feedback)

We will make use of tutorials and regular Peer feedback.

ECTS
7,5 ECTS
Type of assessment
Written examination
Type of assessment details
Written assignment. Individual/group.
The exam is intergrated with the course Welfare, inequality and social mobility. A written take-home essay is defined as an assignment that addresses one or more questions. The exam is based on the course syllabus, i.e. the literature set by the teacher. The written take-home essay must be no longer than 15 pages. For group assignments, an extra 5 pages is added per additional student.
Further details for this exam form can be found in the Curriculum and in the General Guide to Examinations at KUnet.
Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assessment

Please see the learning outcome.

  • Category
  • Hours
  • Lectures
  • 42
  • Preparation
  • 104
  • Exam Preparation
  • 60
  • English
  • 206

Kursusinformation

Language
English
Course number
ASOB16111U
ECTS
7,5 ECTS
Programme level
Bachelor
Duration

1 semester

Placement
Autumn
Schedulegroup
See timetable
Capacity
Vejl. 110
Studyboard
Department of Sociology, Study Council
Contracting department
  • Department of Sociology
Contracting faculty
  • Faculty of Social Sciences
Course Coordinator
  • Merlin Schaeffer   (4-756d7b6b487b776b36737d366c73)
Teacher

Merlin Schaeffer

Saved on the 12-05-2022

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