- 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
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.|
NOTE THAT THIS VERSION OF THE COURSE (5 ECTS) ENDS AFTER THE FIRST PART AND IS ONLY OPEN FOR EXCHANGE STUDENTS WHO CANNOT CONTINUE WITH THE COURSE AFTER THE CHRISTMAS BREAK.
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 rest of the course is divided in two parts, each lasting four weeks. In the first part, students will study measurement and statistical modeling issues related to trust and reputation by means of survey (e.g., General Social Survey) and online process data (e.g., transaction data from peer-to-peer online markets). In the second part, students will study measurement and statistical modeling issues related to social networks by means of survey and social network data (e.g., complete class networks).
In the first three weeks of each part, 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 fourth week of each part, students write a research essay in which they address particular research questions, conduct an explanatory analysis and explicate the social 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 results of the assignments and research essays 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 essays.
Basic statistics (descriptive and inference), basic regression analysis (simple and multiple), and basic skills of SPSS 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.
Access by Erasmus students is subject to approval by the coordinator.
|The following course module must be completed:|
|Basic statistics (descriptive and inference), basic regression analysis (simple and multiple), and basic skills of SPSS including working with syntax. Sound knowledge of English (spoken and written).|
Those who did not complete the course Practicum Data-analyse are offered a self-assessment test to help them decide whether they meet the requirements with respect to knowledge and skills.
|Collier, J., Using SPSS Syntax, A Beginner’s Guide. Los Angeles: Sage, 2010. ISBN is 978-1483333434 or similar SPSS manual.|Instructional formats
|Computer lab sessions|
General remarksIn the computer lab sessions, students apply the research skills and statistical theory to real life examples and prepare for assignments and research essays.
Class session preparationStudents are expected to familiarize themselves with the data used in the computer lab session.
Contribution to group workStudents participate actively to prepare the assignments.
General remarksIn the lectures, the methodological and statistical theories behind measurement and modeling issues in social data analysis are discussed.
Class session preparationStudents read the required literature in advance to obtain understanding of the topic of the lecture.
General remarksIn the tutorials, the results of the assignments and research essays are discussed and the new assignments are introduced.
Class session preparationStudents prepare reports on the assignments and research essays, and actively participate in the discussion during the tutorials.
AssessmentEssays (40%), min. grade 5.0 and assignments (60%), min. grade 5.0. See course manual.
Knowledge of different statistical techniques for scale, factor, regression and social network analysis and their application to social data from conventional and new sources to cope with statistical measurement and modelling issues.