Research Design and Methods in Sociology and Political Science

Sciences Po, Undergraduate, Campus Reims,

With Emiliano Grossman

This course is meant to provide a first general approach to enunciating and solving problems in sociology and political science. It will discuss the way in which to frame a problem, ask a good research questions and how to look for answers. This will call for some elements of the theory of science, as well as understanding the importance of theory and causality. A second block will deal with the issue of measurement in responding to problems. It will demonstrate how to develop and how to interpret indicators. Thereby, we will pay attention to levels of measurement and provide examples from opinion surveys, questionnaires and textmining. The third and largest block will provide an introduction into the interpretation and analysis of data. It will introduce to descriptive statistics, graphs, correlation and simple and multiple regression.

There are no prerequisites required at this stage. There will be a tutorial in addition to the course working with the statistical software R.

The ultimate objective of the course is to elaborate a complete research project. To be handed in one week after the end of the course. The topic has to be agreed with the instructors. A separate assignment will be added for the tutorial.

1. Theory, hypotheses and causality

2. Comparison and simple forms of inference

3. Experiments in the social sciences
4. Building and reading indicators

5. Questionnaires, surveys and public opinion
6. The World Wide Web, big data and textmining

7. Qualitative approaches

8. Turning one or two variables into a figure. Mean, median, correlation, odds ratio...
9. How to deal with too many variables ? Geometrical data analysis
10. Do you want to take some risks? Statistical tests tell you how much

11. A step further with regression
12 Advanced Regression and Interaction Effects

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Research Design and Methods in Sociology and Political Science

1. Theory, hypotheses and causality

2. Comparison and simple forms of inference

3. Experiments in the social sciences

4. Building and reading indicators

5. Questionnaires, surveys and public opinion

6. The World Wide Web, big data and textmining

7. Qualitative approaches

8. Turning one or two variables into a figure. Mean, median, correlation, odds ratio...

9. How to deal with too many variables ? Geometrical data analysis

10. Do you want to take some risks? Statistical tests tell you how much

11. A step further with regression

12 Advanced Regression and Interaction Effects

LES COMMENTAIRES | COMMENTS