Universität Wien

210021 UE BAK 4 Quantitative Methoden der empirischen Sozialforschung (2022W)

6.00 ECTS (2.00 SWS), SPL 21 - Politikwissenschaft
Prüfungsimmanente Lehrveranstaltung
VOR-ORT

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Details

max. 35 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Donnerstag 06.10. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 13.10. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 20.10. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 27.10. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 03.11. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 10.11. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 17.11. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 24.11. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 01.12. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 15.12. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 12.01. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 19.01. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Donnerstag 26.01. 15:00 - 16:30 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course is complementary to the theoretical course “VO BAK 4 Quantitative methods in the empirical social sciences (2022W)” taught by Professor Markus Wagner. The aim of the course is to equip students with the basic applied skills for easy data projects. The content of the course includes descriptive univariate (scale levels, position and dispersion measures, frequency tables) and bivariate (cross tables, correlation measures for different scale levels) analysis methods, as well as the graphic representation of results and the basics of inferential regression statistics. The core focus of this course will be hands-on and practical. The lecture component will cover more abstract ideas. Students are strongly encouraged to attend the lecture as well.
Students will learn the basic “tools” to conduct quantitative data analysis, using the statistical software Stata. Theoretical concepts of descriptive and inferential statistics will be briefly discussed in class, in combination with their practical application using existing databases typical of those in the field of political science. By the end of the course, you should be able to describe a dataset and conduct basic inferential analyses using the main commands implemented in Stata.
At the end of the course, students should know and understand the basic methods and simple statistical procedures in the social sciences, as well as be able to interpret and evaluate the results of quantitative social research in research and the media. You should also be able to develop questions yourself and answer them using quantitative methods and be able to present the results of quantitative research appropriately.
Please note that the course will be instructed in English. This requires that class discussions, weekly assignments, written tests and the term paper are completed in English.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The final assessment will be based on the following components:
- Attendance/Participation (10% of final grade): regular attendance in class (maximum 2 classes can be missed)
- 3 short homework assignments (25% of final grade) based on materials in the course texts. Students are encouraged to form study groups but assignments must be completed individually. The Turnitin program will ensure that no plagiarism occurs.
- 1 short test (25% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata output. Duration: max 45 minutes.
- Final assignment (40% of final grade). At the end of the course, you will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. The Turnitin program will ensure that no plagiarism occurs.
Deadline for handing in the final assignment: 28 February 2023.
Final grades will be a summation of these:
- 100-87 Points Excellent (1)
- 86-75 Points Good (2)
- 74-63 Points Satisfactory (3)
- 62-50 Points Sufficient (4)
- 49-0 Points Insufficient (5)

Mindestanforderungen und Beurteilungsmaßstab

Please note that all four components are essential for the final grade, i.e. regularly attend classes, hand in 3 homework assignments, complete the short test, and submit the final assignment. In cases of suspected plagiarism, you may be called upon to reasonably demonstrate that any work they you have submitted is your own (the anti-plagiarism software Turnitin will be used via Moodle to detect plagiarism). A passing grade on each component is not required for a passing grade in the course.

Prüfungsstoff

The examination will focus on different topics covered in class and will include basic data analysis using the Stata commands learnt in class. Detailed instructions about the homework, the test and the final assignment will be shared on Moodle in due time.

Literatur

Recommended Texts:
- Philip H Pollock III and Barry C. Edwards. (2018). A Stata® companion to political analysis. CQ Press/SAGE Publications
- Kyle C. Longest. (2019). Using Stata for quantitative analysis. SAGE Publications.
- Paul M. Kellstedt, and Guy D. Whitten. (2018) (3rd edition). The fundamentals of political science research. Cambridge: Cambridge University Press
- Paul M Kellstedt and Guy D. Whitten. (2019). A Stata Companion for the Third Edition of The Fundamentals of Political Science Research. Cambridge University Press

Supplementary materials:
- Alan C. Acock. (2014). A Gentle Introduction to Stata (6th edition). College Station, Texas: Stata Press
- Alan Agresti. (2018). Statistical methods for the social sciences (5th edition). New Jersey: Pearson Education International
- Donald J. Treiman. (2009). Quantitative Data Analysis. Doing Social Research to Test Ideas. San Francisco: Jossey-Bass.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 26.09.2022 12:29