Universität Wien

220043 SE SE Advanced Data Analysis 1 (2024S)

5.00 ECTS (2.00 SWS), SPL 22 - Publizistik- und Kommunikationswissenschaft
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. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 13.03. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG
  • Wednesday 10.04. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG
  • Wednesday 24.04. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG
  • Wednesday 15.05. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG
  • Wednesday 29.05. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG
  • Wednesday 12.06. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG
  • Wednesday 26.06. 09:45 - 12:45 Seminarraum 4, Währinger Straße 29 1.UG

Information

Aims, contents and method of the course

This data analysis seminar focuses on advanced data analysis with R. Following a recapitulation of the basics of regression analysis, the seminar will address 1) Structural Equation Modeling including CFA and Path Analyses, 2) Multi-Group Analysis and Measurement Invariance, 3) Moderation and Mediation Analysis, as well as 4) Multi-Level Modeling. Students will also learn how to analyze cross-sectional and longitudinal data.

By the end of this course, participants will be able to:
• Understand the theoretical background of linear regression, moderation, mediation, as well as complex statistical analyses like structural equation and multi-level models
• Know how to use R to run the respective analyses
• Know how to visualize, report and interpret the obtained results

Assessment and permitted materials

Course grading is based on the presentation and written report of a group project. In this project students apply the learnt techniques of analysis on a provided dataset (secondary data analysis). Further details will be provided in class.

Minimum requirements and assessment criteria

Ongoing in-class participation and additional readings are basic requirements.

For successfully passing the course, participants have to achieve at least 50% of the total points. Full details on the grading system will be given in class and on Moodle.

Examination topics

All lectures and tutorials taught in class as well as related readings and materials on Moodle.

Reading list

Association in the course directory

Last modified: Fr 01.03.2024 12:06