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Applied Data Analysis - Angewandte Datenanalyse
Knowledge
Successful completion of the lecture course in statistics
Description
The course “Applied Statistics” builds on the skills that students acquired in previous semesters in courses on research design and data analysis and gives them opportunities to exercise and develop their skills in the application to topics from the social sciences. The course revolves around the analysis of political science research data sets using the free statistical software R. In addition to the core topic of data analysis the course also covers aspects of social science data management and the graphical representation of statistical results.
The course is accompanied by student tutorials.
Learning objectives
The course provides participants with practical experience in the application of data analytical techniques, using appropriate statistical software. This allows them to acquire, develop and expand skills that are immensely useful not only for their research activities in later stages of their studies, but which are also essential job skills in many fields of either academic or applied political science.
After successful completion of the course participants
have an understanding of the structure of social science research data sets
are able to select statistical techniques appropriate for research question of their own chosing,
are capable to put these techniques into practice using statistical software,
and to effectively present and communicate statistical results by way of tables and graphics.
E-learning
ILIAS: http://learning.zu.de
Preparation
Field, Andy, Jeremy Miles and Zoë Field. 2012. Discovering Statistics Using R. London, Thousand Oaks, New Delhi, Singapore: Sage Publications.
Mehmetoglu, Mehmet, and Matthias Mittner. 2021. Applied Statistics Using R: A Guide for the Social Sciences. London: Sage.
Next events
1/12 | Lecture | Tu, 04.02.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
2/12 | Lecture | Tu, 11.02.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
3/12 | Lecture | Tu, 18.02.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
4/12 | Lecture | Tu, 25.02.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
5/12 | Lecture | Tu, 04.03.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
6/12 | Lecture | Tu, 11.03.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
7/12 | Lecture | Tu, 18.03.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
8/12 | Lecture | Tu, 25.03.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
9/12 | Lecture | Tu, 01.04.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
10/12 | Lecture | Tu, 08.04.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
11/12 | Lecture | Tu, 29.04.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
12/12 | Lecture | Tu, 06.05.2025 | 13:30 Uhr | 16:00 Uhr | 2.11 | grün |
Course details
Offer code | 114161 | 113122 |
Version | 2 Umbenennung_FS 2023 |
Credits / ECTS | 6 |
WSH | 3 |
Frequence | Every term |