NIFK14019U  Empirical Methods in Social Science

Volume 2014/2015
Content

This is an introductory course that centers on social science data collection methods - both qualitative tools (e.g. personal interviewing, focus groups) and quantitative tools (typically questionnaires) are covered.  Focus is on how, to construct such tools, and how to evaluate their validity. A number of techniques to analyse qualitative data and develop quantitative latent variables will also be presented.

The course does not address a specific study direction or empirical field. Literature, data and practical exercises from different fields of inquiry are used.

 

The course consists of two parts: a theoretical / methodological part and a practical part.

The theoretical / methodological part of the course gives an overview of available qualitative and quantitative social science methods and outlines their strengths and weaknesses. Also mixed methods approaches, where qualitative and quantitative data are combined, are introduced. It is discussed when it is more or less appropriate and relevant to employ a specific method. Different types of generalization principles and evaluations of validity are also presented.

The practical part of the course centers, firstly, on data tool construction: how to develop an interview guide for individual interviews, how to develop a questionnaire and appropriate survey questions and response options, and how to design stated preference questions. There will be exercises where the students will obtain practical experience with developing the data tools. Secondly, analytical strategies for examination of qualitative and quantitative data are presented. With respect to qualitative analysis different kinds of coding principles are outlined and the variable- versus case-oriented technique is presented. With respect to questionnaire data analytical principles and techniques to develop latent variables (scales or clusters) are discussed. Principles to assess the validity of latent variables and stated preference designs are also illustrated. The covered analysis and validity techniques are illustrated by use of existing interview guides and questionnaires and data analysis of these, and there will be practical exercises.

Learning Outcome

The overall objective of the course is to introduce students to social scientific data collection tools and give them practical experience with development and evaluation of the quality of such tools. After completion of the course it is expected that the student:

                                                                       

Knowledge:

- Can identify different types of quantitative and qualitative methods used in the social sciences and describe their features.

- Has a theoretical understanding of pertinent decision criteria when choosing methodological approach and specific tool(s).

- Can demonstrate an overview of a selection of techniques that can be used for qualitative data analysis and latent variable modeling.

- Has overview of and ability to reflect over ways to assess the validity of data collection tools.

 

Skills:

- Has the ability to compare the suitability of specific methods when confronted with research questions and argue for / explain choice of methods. 

- Has practical experience with developing qualitative and quantitative data collection tools.

- Can point out relevant analytical techniques (both qualitative and quantitative) for specific research questions.   

- Can determine the validity of a data collection tool and data.

                            

Competences:

- Discuss and evaluate the limitations and relevance of specific data tools and methods.

- Is able to develop research designs and data collection tools.

- Can discuss and critically assess the quality of a research design.

- Will have generalizable tools to assess appropriate social scientific research designs.

 - Can engage in discussion with other analysts (including social scientist candidates such as sociologists and anthropologists) about choice of method and validity criteria.

 

a course in statistics
Teaching is organized as lectures and exercises introducing and training the core elements of the course. Students are expected to participate actively in group work.
Credit
7,5 ECTS
Type of assessment
Written examination, 4 timer under invigilation
...
Exam registration requirements
During the course students will get three assignments that must be completed in order to take the final exam. The assignments can be carried in groups or individually.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
one internal examiner
Re-exam
If 10 or fewer register for the reexamination the examination form will be oral.
Criteria for exam assesment

see learning outcome

  • Category
  • Hours
  • Lectures
  • 28
  • Theory exercises
  • 24
  • Practical exercises
  • 54
  • Preparation
  • 96
  • Exam
  • 4
  • Total
  • 206