Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

230089 SE From Description to Inference: Basic Tools to Learn from Data (2021S)

4.00 ECTS (2.00 SWS), SPL 23 - Soziologie
Continuous assessment of course work
REMOTE
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. 35 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 04.03. 09:00 - 10:30 Digital
  • Thursday 11.03. 09:00 - 10:30 Digital
  • Thursday 18.03. 09:00 - 10:30 Digital
  • Thursday 25.03. 09:00 - 10:30 Digital
  • Thursday 15.04. 09:00 - 10:30 Digital
  • Thursday 22.04. 09:00 - 10:30 Digital
  • Thursday 29.04. 09:00 - 10:30 Digital
  • Thursday 06.05. 09:00 - 10:30 Digital
  • Thursday 20.05. 09:00 - 10:30 Digital
  • Thursday 27.05. 09:00 - 10:30 Digital
  • Thursday 10.06. 09:00 - 10:30 Digital
  • Thursday 17.06. 09:00 - 10:30 Digital
  • Thursday 24.06. 09:00 - 10:30 Digital

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 foundations in descriptive and inferential statistics. The aim of the course is to provide students with fundamental skills to interpret quantitative information, to comprehend statistical reports, and to analyze data by means of a statistical software.
Main topics of the course:
- Statistical Concepts and Descriptive Statistics,
- Probability,
- Inferential Statistics,
- Analyzing association between variables.
The course will be both theoretical and practical. For the applied sessions, the following software will be used: R and RStudio.
The course will be held digitally, the Moodle platform will also be used. The language of the course is English.

Assessment and permitted materials

In the course of the semester, students have to deliver an individual assignment at the end of each - main - topic, for a total of four assignments. In each assignment, the student has to show the quantitative skills acquired (e.g., proper use of statistical concepts, use of data, analyze data correctly and interpret the results accordingly). For the final grade: the first assignment weights 20%, the second and third assignments weight 25%, the fourth assignment weights 30%.

Minimum requirements and assessment criteria

Each assignment is graded with a scale from 1 (excellent) to 5 (fail). Students have to deliver each assignment in due time, according to the agreed deadlines, which will be announced during the course. For each 12 hours of delay in submitting the assignment, half a point will be subtracted from the grade. If the student does not deliver all the assignments, the course is considered failed. Attendance is compulsory, up to three absences without notice will be excused. Students need an overall grade of 4 or less to pass the course.

Examination topics

Reading list

Statistical Methods for the Social Sciences (4th Edition), Agresti & Finlay.
Statistical Methods for the Social Sciences (5th Edition), Agresti
When necessary, other material will be indicated during the course.

Association in the course directory

Last modified: Fr 12.05.2023 00:20