234012 VO Statistics for Social Scientists 1 (Lecture) (2023W)
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Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Details
max. 30 participants
Language: English
Examination dates
- Wednesday 07.02.2024 15:00 - 18:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Friday 22.03.2024 08:00 - 12:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Wednesday 10.04.2024 08:00 - 12:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 27.06.2024 09:45 - 12:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 09.10.2024 08:00 - 12:00 Seminarraum 19, Kolingasse 14-16, OG02
Lecturers
Classes (iCal) - next class is marked with N
- Wednesday 06.12. 15:00 - 18:15 PC-Seminarraum 3, Kolingasse 14-16, OG02
- Tuesday 12.12. 15:00 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 16.01. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 23.01. 15:00 - 18:15 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
- Friday 26.01. 09:45 - 13:00 PC-Seminarraum 3, Kolingasse 14-16, OG02
Information
Aims, contents and method of the course
This course is intended to provide the foundations of statistical techniques commonly implemented in social sciences. In addition, the refresher course aims at achieving a common standard in statistical methods among students, and help prepare for more advanced quantitative courses. The course will start by introducing students with basic concepts, notations, and techniques of summarizing and presenting data in a meaningful way. The second part will focus probability and probability distributions. The third part of the course will deal with the basic problem of statistical analysis-how we make general statements about the `phenomenon itself' from observed data. It will include likelihood functions, hypothesis testing, confidence intervals and ordinary linear regressionanalysis. METHODS: The teaching method mainly involves classroom lectures where the instructor will explain intuitions and concepts with worked examples.
Assessment and permitted materials
Successful completion of this lecture-based course will be evaluated by ONE written exams about the topics discussed in the lecture- a final exam to take place during the final session of the course (100 %).
Minimum requirements and assessment criteria
The examination for the lecture will be graded on a basis of 100 points in total:[87%-100%]: Excellent (1)[75%-86%]: Good (2)[63%-74%]: Satisfactory (3)[50%-62%]: Sufficient (4)<50%: Unsatisfactory (5)
Examination topics
• Content of the lectures and suggested take-home exercises• Assigned reading materials and book chapters
Reading list
Lindsey J.K. (2004). Introduction to Applied Statistics. A Modelling Approach. Oxford University Press, Second EditionStatistical Methods for the Social Sciences (5th Edition), AgrestiIntroductory Econometrics: A Modern Approach (5th ed.), JM WooldridgeWhen necessary, other material will be indicated during the course.
Association in the course directory
Last modified: Mo 16.09.2024 14:06