Universität Wien

200099 SE Anwendungsseminar: Geist und Gehirn (2022S)

Experimentalpsychologische Daten analysieren mit R

4.00 ECTS (2.00 SWS), SPL 20 - Psychologie
Continuous assessment of course work
REMOTE

Anwendungsseminare können nur für das Pflichtmodul B verwendet werden! Eine Verwendung für das Modul A4 Freie Fächer ist nicht möglich.

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: German

Lecturers

Classes (iCal) - next class is marked with N

The seminar takes place exclusively online (live sessions in Moodle at the indicated times). Therefore a computer with internet access is required. During the sessions, online attendance is obligatory. Those who are not online during the first session will be deregistered from the seminar. In addition to the sessions, there will be voluntary sessions where questions will be answered and assistance provided in direct exchange.

Tuesday 01.03. 13:30 - 15:00 Digital
Tuesday 08.03. 13:30 - 15:00 Digital
Tuesday 15.03. 13:30 - 15:00 Digital
Tuesday 22.03. 13:30 - 15:00 Digital
Tuesday 29.03. 13:30 - 15:00 Digital
Tuesday 05.04. 13:30 - 15:00 Digital
Tuesday 26.04. 13:30 - 15:00 Digital
Tuesday 03.05. 13:30 - 15:00 Digital
Tuesday 10.05. 13:30 - 15:00 Digital
Tuesday 17.05. 13:30 - 15:00 Digital
Tuesday 24.05. 13:30 - 15:00 Digital
Tuesday 31.05. 13:30 - 15:00 Digital
Tuesday 14.06. 13:30 - 15:00 Digital
Tuesday 21.06. 13:30 - 15:00 Digital
Tuesday 28.06. 13:30 - 15:00 Digital

Information

Aims, contents and method of the course

Targets: In this course, students learn how to analyze experimental cognitive psychology data, create diagrams, and report the results in a suitable way for publication. Knowledge in R is obtained, and statistical and methodological expertise is deepened. Knowledge in R is not a prerequisite.
Contents: In this course, four topics are covered. 1. Handling of data (import, calculating new variables, filtering, etc.); 2. Descriptive statistics diagrams; 3. Simple inferential statistics (t-test etc.) and advanced inferential statistics (linear mixed effect models, etc.); 4. Simulations for power analysis. The last block shows the strengths of R and illustrates which aspects influence the power of experiments.
Methods: Mainly problem-solving oriented teaching. After an introduction to the topic of each session, students work independently on problems. The solutions are then discussed together. After each session, similar tasks are to be worked on as homework.
Note: Please install R (https://www.r-project.org) and R-Studio (https://www.rstudio.com/products/rstudio/download/#download) on your computer before the first session. Any problems that may arise with the installation will be solved in the first unit.

Assessment and permitted materials

Participation in the sessions, homework for the session, and final assignment. All kinds of aids are allowed as long as the tasks are worked on and solved independently.

Minimum requirements and assessment criteria

Minimum requirements: Obligatory online attendance (maximum two absences).
Assessment criteria: participation (20%), homeworks (60%), final assignment (20%).
For a positive assessment, 50% is necessary (from 62.5% Satisfactory; from 75% Good, from 87.5% Very Good).

Examination topics

The topics of the sessions are the basis for the assessment.

Reading list

Will be announced in the seminar.

Association in the course directory

Last modified: Th 11.05.2023 11:27