Universität Wien

210016 UE BAK 4 Quantitative Methoden der empirischen Sozialforschung (2022W)

(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 12.10. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 19.10. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 09.11. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 16.11. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 23.11. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 30.11. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 07.12. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 14.12. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 11.01. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 18.01. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02
  • Mittwoch 25.01. 11:30 - 13:00 Seminarraum 17, Kolingasse 14-16, OG02

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course is complementary to the theoretical course “210014 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 basic descriptive and inferential statistics, as well as the graphic representation of results. The core focus of this course will be hands-on and practical. Students are expected to attend the 210014 VO lecture component, which will cover theoretical concepts and more abstract ideas.

Students will learn the basic “tools” to conduct quantitative data analysis using the programming language R. By the end of the course, students should be able to describe and manipulate a dataset and conduct basic inferential analysis R.

PLEASE NOTE: In order to participate in the course YOU WILL NEED A PERSONAL LAPTOP (not an iPad) WHICH CAN RUN R.

Teaching will be in-person in a regular classroom, not a computer lab, so you will need to bring your laptop every week.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The final assessment will be based on the following components:
(1) Participation (10% of final grade) Regular attendance in class (maximum 2 classes can be missed)
(2) Four 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.
(3) A mid-term exam before Christmas (25% of final grade). The test will concern theoretical questions and/or interpretation of R output. 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 paper of 2000-2500 words, focusing mostly on methods with applications in R. Joint work is NOT allowed for the final assignment.

Mindestanforderungen und Beurteilungsmaßstab

Students are required to bring a personal laptop to class.

In order to complete the course with a positive grade students have to attempt all seminar parts.
Students are allowed to miss two classes.
The software turnitin will be used to check plagiarism
90-100 = 1. Excellent
80-89 = 2. Good
70-79 = 3. Satisfactory
60-69 = 4. Sufficient
< 60 = 5. Fail

Prüfungsstoff

The examination will focus on different statistical concepts covered in class and will include basic data analysis using the programming language R. Detailed instructions about the homework assignments and the final assignment will be posted on Moodle in due time.

The final paper is due on February 15th 2023

Literatur

The following readings are required - please consider buying:
- Alan Agresti (2018). Statistical methods for the social sciences (5th edition). New Jersey: Pearson Education International

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 28.09.2022 12:28