Universität Wien FIND

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210025 UE BAK4.2: Quantitative Methods of Empirical Social Research (2020W)

(engl.)

6.00 ECTS (2.00 SWS), SPL 21 - Politikwissenschaft
Continuous assessment of course work

Die Lehrformate für das WS (digital, hybrid, vor Ort) befinden sich in Entwicklung. Die Lehrenden werden die geplante Organisationsform und Lehrmethodik auf ufind und Moodle bekannt geben. Aufgrund von Covid19 muss mit kurzfristigen Änderungen in Richtung digitaler Lehre gerechnet werden.

Nicht-prüfungsimmanente (n-pi) Lehrveranstaltung. Eine Anmeldung über u:space ist erforderlich. Mit der Anmeldung werden Sie automatisch für die entsprechende Moodle-Plattform freigeschaltet. Vorlesungen unterliegen keinen Zugangsbeschränkungen.

VO-Prüfungstermine erfordern eine gesonderte Anmeldung.
Mit der Teilnahme an der Lehrveranstaltung verpflichten Sie sich zur Einhaltung der Standards guter wissenschaftlicher Praxis. Schummelversuche und erschlichene Prüfungsleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis).

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first serve).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Tuesday 06.10. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 13.10. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 20.10. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 27.10. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 03.11. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 10.11. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 17.11. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 24.11. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 01.12. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 15.12. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 12.01. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 19.01. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital
Tuesday 26.01. 15:00 - 16:30 Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Digital

Information

Aims, contents and method of the course

If COVID restrictions are lifted, we may have 3-4 on-site presence days that will focus as reviews and allow for personalized assistance with STATA. If there are more than 10 students registered, students will be divided into groups and the session will be divided into 2 or 3 to ensure compliance with COVID-related university policies.
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 analysis 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.

Aims of the course
This course is complementary to the theoretical course “210014 VO BAK 4 Quantitative methods in the empirical social sciences (2020W)” 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 is course will be hands-on and practical. The 210014 VO lecture component will cover more abstract ideas (digital short lectures every Wednesday, tutorial Tuesday 5 pm with exercises). 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 analysis 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.

Method of Instruction
The primary method of the course will be digital/online using Moodle and BigBlueButton. This will allow for the maximum number of students to attend synchronously. There will also be 3-4 on-site presence days (if conditions allow it) that will focus as reviews and allow for personalized assistance with STATA. If there are more than 10 students registered, students will be divided into groups and the session will be divided into 2 or 3 to ensure compliance with COVID-related university policies.

Assessment and permitted materials

The final assessment will be based on the following components:
(1) 3 short homework assignments (30% 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.
(2) 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. This exam may occur on Moodle. Duration: max 45 minutes.
(3) Two-Page Final Research Assignment Proposal (5% of final grade): 28 February 2021
(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 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: 31 March 2021.

Final grades will be a summation of these:
100-90 Points Excellent (1)
89-80 Points Good (2)
79-70 Points Satisfactory (3)
69-60 Points Sufficient (4)
59-0 Points Insufficient (5)

Minimum requirements and assessment criteria

Please note that all four components are essential for the final grade, i.e. hand in 3 homework assignments, complete the short test, submit the two-page final research assignment proposal, and hand in 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 (TurnItIn via Moodle will be used to detect plagiarism). A passing grade on each component is not required for a passing grade in the course.

Examination topics

The short 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 final assignment will be posted on Moodle and circulated in class before the end of the course.

Reading list

All reading materials are available from the Political Science and Sociology Library (Rooseveltplatz) reference. The first text listed will be the primary text. You are encouraged to use their copies or purchase your own. Limited readings from other texts will be provided on Moodle. Supplemental texts are also available at the library.

Required 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

Supplemental Texts:
- Alan C. Acock. 2014. A Gentle Introduction to Stata (6th edition). College Station, Texas: Stata Press
- Alan Agresti and Barbara Finaly. 2009. Statistical methods for the social sciences (4th edi-tion). New Jersey: Pearson Education International
- Donald J. Treiman. 2009. Quantitative Data Analysis. Doing Social Research to Test Ideas. San Francisco: Jossey-Bass.

Association in the course directory

Last modified: Mo 05.10.2020 10:10