Universität Wien

230136 UE Specific Multivariate Methods of Analysis in the Social Sciences (2023S)

4.00 ECTS (2.00 SWS), SPL 23 - Soziologie
Continuous assessment of course work
Moodle

Registration/Deregistration

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

Details

max. 20 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 02.03. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Thursday 09.03. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Thursday 16.03. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Thursday 23.03. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Thursday 30.03. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Thursday 20.04. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 25.04. 13:15 - 16:15 PC-Raum 1 Schenkenstraße 8-10, 1.UG
  • Thursday 04.05. 13:15 - 16:15 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33

Information

Aims, contents and method of the course

Focusing on the practice of empirical research in the social sciences, this course is intended to provide the basic in multivariate data analyses. The aim of the course is to provide students with fundamental skills to interpret quantitative information, to comprehend statistical analyses, and to analyze data by means of a statistical software.
Main topics of the course:
- Multiple regression and correlation
- Model building with multiple regression
- Logistic regression
The following free software will be used: R and RStudio. The language of the course is English.

Assessment and permitted materials

Students have to deliver individual assignments and perform a research paper presentation, showing the quantitative skills acquired (e.g., proper use of statistical concepts, use of data, analyze data correctly and interpret the results accordingly). The final grade is based on all the following tasks:
- Active participation (20%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (20%)

Important Grading Information:
If not explicitly noted otherwise, all requirements mentioned in the grading scheme must be met.
If a required task is not fulfilled, this will be considered as a discontinuation of the course. In that case, the course will be graded as ‘fail’ (5), unless there is a major and unpredictable reason for not being able to fulfill the task on the student's side (e.g. a longer illness).
In such a case, the student may be de-registered from the course without grading.
Whether this exception applies is decided by the lecturer.

If any requirement of the course has been fulfilled by fraudulent means, be it for example by cheating at an exam, plagiarizing parts of a written assignment or by faking signatures on an attendance sheet, the student's participation in the course will be discontinued, the entire course will be graded as ‘not assessed’ and will be entered into the electronic exam record as ‘fraudulently obtained’.

The plagiarism-detection service (Turnitin in Moodle) can be used in course of the grading.

Minimum requirements and assessment criteria

Task are graded with a scale from 1 (excellent) to 5 (fail). Students have to respect the deadlines agreed for each task. If the student does not perform in one of the tasks according to the deadline, the course is considered failed. To have an overall positive evaluation, students need a grade of at least 4 for each task. Attendance at the sessions is expected, if a student misses more than one session, the course is considered failed.

Examination topics

Reading list

Statistical Methods for the Social Sciences (5th Edition), Alan Agresti
Other material will be indicated during the course.

Association in the course directory

in 905: Ausschließlich für das Pflichtmodul MA M Methoden

Last modified: Th 14.11.2024 00:16