| Course title | Introduction to Data Analysis in Social Science |
|---|---|
| Course code | KPE/BIDS |
| Organizational form of instruction | Lecture + Seminary |
| Level of course | unspecified |
| Year of study | not specified |
| Semester | Summer |
| Number of ECTS credits | 5 |
| Language of instruction | English |
| Status of course | unspecified |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Course availability | The course is available to visiting students |
| Lecturer(s) |
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| Course content |
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unspecified
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| Learning activities and teaching methods |
| unspecified |
| Learning outcomes |
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Data science is becoming more and more crucial in social sciences. Quantitative methods have become a workhorse of research in political science, education and sociology. Furthermore, a data analytics specialist is essential in any business. There is a growing need for employees across all areas to know how to read, interpret, and present data in a way that can be understood across all functions and inform decision-making. The aim of the course is to provide students with basic skills how to conduct their own research project or data analysis. We start with getting the data, importing data into a statistical software R, reshaping and recoding data. The second part of the course will aim at data analysis. The basics principles in statistics will be introduced. We will focus on correlational and regression analysis. The third part of the course will aim at data visualization skills such as how to produce interactive online plots (use in data journalism, business, or marketing), online maps for targeting etc.
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| Prerequisites |
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unspecified
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| Assessment methods and criteria |
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unspecified
Own research project presentation. |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
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