Universität Wien

200100 SE Anwendungsseminar: Geist und Gehirn (2024S)

Programming, Data Workflow and Data Visualization with R

4.00 ECTS (2.00 SWS), SPL 20 - Psychologie
Prüfungsimmanente Lehrveranstaltung

Anwendungsseminare können nur für das Pflichtmodul B verwendet werden! Eine Verwendung für das Modul A4 Freie Fächer ist nicht möglich.
Moodle
Mi 08.05. 09:45-11:15 Hörsaal H Psychologie KG Liebiggasse 5

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 20 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

This seminar aims to develop a basic understanding of programming with R, and also addresses the organization of research data and the creation of professional plots.
In order to take part in the seminar and to do the homework, you need to install R (https://cran.r-project.org ) and RStudio (RStudio Desktop; https://www.rstudio.com ) on your own computer or laptop. The R package Tidyverse (https://www.tidyverse.org ) is also required.
In the first session on March 6th, the topics will be presented and (if necessary) support will be provided for the installation of R/RStudio. Admission to the seminar will be also decided on March 6th.

Mittwoch 06.03. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 13.03. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 20.03. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 10.04. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 17.04. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 24.04. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 15.05. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 22.05. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 29.05. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 05.06. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 12.06. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 19.06. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5
Mittwoch 26.06. 09:45 - 11:15 Hörsaal H Psychologie KG Liebiggasse 5

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course consists of classes with compulsory attendance as well as independent preparation and follow-up assignments at home (= small homework exercises).

R is a statistical programming language that is often used in psychology to process and analyze data.
In this course students will
- acquire basic programming knowledge in R (the goal is not to become a professional programmer, but rather to be able to write small scripts and functions),
- learn to prepare, examine and communicate data in a clean and reproducible way (avoid data chaos using "tidy" data and R notebooks),
- learn how to create illustrations and plots that can be used in publications and theses,
- carry out basic data analyzes in R (e.g., t-tests, ANOVAs, correlations),
- get a good understanding of R, which will be helpful for more advanced topics and courses (e.g. Bayesian statistics, hierarchical models, etc.).

Art der Leistungskontrolle und erlaubte Hilfsmittel

- regular attendance
- active participation in the classes (and in the online forum: asking and answering questions)
- regular homeworks (small programming tasks as preparation and follow-ups to the classes)
- Final assignment: Preparation and analysis of a real data set

Mindestanforderungen und Beurteilungsmaßstab

- Regular attendance is a requirement; a maximum of 2 classes may be missed without excuse
- Active participation: 20%
- Homework: 40%
- Final assignment: 40%

1 (sehr gut) 100% - 88%
2 (gut) 87% - 75%
3 (befriedigend) 74% - 62%
4 (genügend) 61% - 50%
5 (nicht genügend) 49% - 0%

Prüfungsstoff

There will be no final exam

Literatur

Venables, W. N., Smith, D. M., & R Core Team. (2023). An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics. https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1–23. https://doi.org/10.18637/jss.v059.i10
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., … Yutani, H. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Wickham, H. & Grolemund, G. (2017). R for Data Science. O’Reilly. https://r4ds.had.co.nz/
Ross, Z., Wickham, H., & Robinson, D. (2017). Declutter your R workflow with tidy tools. PeerJ Preprints, 5(e3180v1), 1–20. https://doi.org/10.7287/peerj.preprints.3180v1

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 04.03.2024 11:26