234012 VO Statistics for Social Scientists 1 (Lecture) (2023W)
Labels
VOR-ORT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Prüfungstermine
- Mittwoch 07.02.2024 15:00 - 18:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Freitag 22.03.2024 08:00 - 12:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Mittwoch 10.04.2024 08:00 - 12:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 27.06.2024 09:45 - 12:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Mittwoch 09.10.2024 08:00 - 12:00 Seminarraum 19, Kolingasse 14-16, OG02
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Mittwoch 06.12. 15:00 - 18:15 PC-Seminarraum 3, Kolingasse 14-16, OG02
- Dienstag 12.12. 15:00 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Dienstag 16.01. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Dienstag 23.01. 15:00 - 18:15 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
- Freitag 26.01. 09:45 - 13:00 PC-Seminarraum 3, Kolingasse 14-16, OG02
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
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.
Art der Leistungskontrolle und erlaubte Hilfsmittel
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 %).
Mindestanforderungen und Beurteilungsmaßstab
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)
Prüfungsstoff
• Content of the lectures and suggested take-home exercises• Assigned reading materials and book chapters
Literatur
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.
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 16.09.2024 14:06