- Assessing reliability and validity of empirical measurement in conventional (e.g., surveys) and new sources of social data (e.g., online process data)
- Learning different statistical techniques for scale, factor, regression and social network analysis
- Applying these techniques to social data from conventional and new sources to address substantial research questions
- Getting acquainted with different types of social data and learning to cope with statistical measurement and modelling issues
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The course focuses on the `Empirical research' , in the `Problems-Theory-Empirical research-Policy implications'-sequence that characterizes the various steps in analytical social science.
The course introduces some of the main methods of empirical measurement and statistical modeling that are used in quantitative sociological research. These are various methods to assess the validity and reliability of measurement, such as reliability analysis and factor analysis, as well as advanced methods of multiple regression analysis. These methods are used to address substantial research questions. For example: Do strong family ties inhibit trust? How does reputation affect online traders’ business success? How are network density and interethnic diversity related?
The first week will be a recap of multiple regression and measurement basics. The following six weeks cover measurement and statistical modeling issues related to trust, reputation and social networks by means of survey data (e.g., General Social Survey), online process data (e.g., transaction data from peer-to-peer online markets) and social network data (e.g., complete class networks).
There will be weekly assignments asking students to solve problems of measurement and statistical modeling that arise in the respective data sets. For example, students will be asked to replicate an analysis described in a research paper or extend the analysis addressing a novel research question. The assignments will also give students the opportunity to get acquainted with different kinds of social data.
In the last two weeks of the course, students write a research essay in which they address particular research questions, conduct an explanatory analysis and explicate the societal relevance of their results as well as the limitations of their analysis.
Students meet three times a week in lectures, tutorials and computer lab sessions. In the lectures, the methodological and statistical theories behind measurement and modeling issues in social data analysis are discussed. In the tutorials, the assignments are introduced and the results of previous week’s assignments are discussed. In the computer lab sessions, students apply the research skills and statistical theory to real life examples and prepare their assignments and research essay.
Assumed knowledge
Basic statistics (descriptive and inference), basic regression analysis (simple and multiple), and basic skills of SPSS or Stata including working with syntax. Sound knowledge of English (spoken and written).
The course is designed for third year sociology students. The language of the instruction and presentations is English.
Note: This course is also part of the dedicated minor Social Sciences and Economics.
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