Universität Wien

210024 UE BAK 4 Quantitative Methoden der empirischen Sozialforschung (2023W)

(engl)

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

  • Mittwoch 04.10. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 11.10. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 18.10. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 25.10. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 08.11. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 15.11. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 22.11. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 29.11. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 06.12. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 13.12. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 10.01. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 17.01. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 24.01. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Mittwoch 31.01. 08:00 - 09:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course is complementary to the theoretical course VO BAK4 "Quantitative methods in the empirical social sciences" taught by Assoz. Prof. Christopher Wratil (2023W).

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. Students are encouraged to attend the lecture component, which will cover theoretical concepts and more abstract ideas.

During the course, students will learn the basic “tools” to conduct quantitative data analysis, using the statistical software Stata. By 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. To do so, students should be able to describe a dataset and conduct basic inferential analyses using the main commands implemented in Stata. Students should also be able to develop their own questions and answer them using quantitative methods and be able to present the results of quantitative research appropriately.

Theoretical concepts of descriptive and inferential statistics will be briefly discussed in class, in combination with their practical application using existing databases in the field of political science.

Please note that the course will be instructed in English. This requires that class discussions, assignments, written tests and final assignment take place in English.

Teaching will be in-person in a computer lab, so students do not need to bring a laptop every week. However, students can work with their own computers if this is easier for them or more accessible. To use their own computers, students will need to purchase the statistical software Stata (15€ per year). A discounted version for students is available at the following link: https://academic.softwareone.com/#/UniWien_Studierende/products?query=Stata

Art der Leistungskontrolle und erlaubte Hilfsmittel

The final assessment will be based on the following components:
(1) Attendance/Participation (10% of final grade): regular attendance in class (maximum 2 classes can be missed).
(2) Homework assignments (25% of final grade) based on materials in the course. Students are encouraged to form study groups but assignments must be completed individually. These tasks will be available on the course’s moodle page.
(3) One short exam (25% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata outputs. Duration: max 45 minutes.
(4) Final assignment (40% of final grade). At the end of the course, you will be required to write a final exam of 2000-2500 words focusing on methods (rather than theory) 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, which should be handed in by the end of February.

Deadline for handing in the final assignment: 29 February 2024.

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 homework assignments, complete the short test, and submit the final assignment. In cases of suspected plagiarism, students may be called upon to reasonably demonstrate that any work they have submitted is their 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 and during the class in due time.

Literatur

Recommended Texts:
- 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: Mi 13.11.2024 12:06