160122 PR Data Analysis Sandbox (2022W)
Prüfungsimmanente Lehrveranstaltung
Labels
VOR-ORT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Sa 03.09.2022 08:00 bis Di 27.09.2022 23:59
- Abmeldung bis Mo 31.10.2022 23:59
Details
max. 40 Teilnehmer*innen
Sprache: Deutsch, Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
teilweise geblockt, Termine werden in der Vorbesprechung fixiert
- Donnerstag 20.10. 15:00 - 16:30 Seminarraum 3 Sensengasse 3a 1.OG (Vorbesprechung)
- Donnerstag 01.12. 09:00 - 11:00 Seminarraum 8 Sensengasse 3a 5.OG
- Donnerstag 15.12. 09:00 - 11:00 Seminarraum 8 Sensengasse 3a 5.OG
- Donnerstag 12.01. 09:00 - 11:00 Seminarraum 8 Sensengasse 3a 5.OG
- Donnerstag 19.01. 09:00 - 11:00 Seminarraum 8 Sensengasse 3a 5.OG
- Donnerstag 26.01. 09:00 - 11:00 Seminarraum 8 Sensengasse 3a 5.OG
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
You will be asked to apply the skills acquired throughout the seminar in a small practical data analysis assignment, for which you will supply both results and your analysis code.
Mindestanforderungen und Beurteilungsmaßstab
Attendance is mandatory (2 unexcused absences max.). Active participation in class in encouraged and will be valued positively. The final grade is 100% based on performance on the final assignment.
Prüfungsstoff
Relevant books chapters and papers will be supplied on Moodle over the course of the seminar.
Literatur
Zuordnung im Vorlesungsverzeichnis
BA-APM10b
Letzte Änderung: Mo 24.10.2022 08:49
You will learn to identify relevant variables of interest in typical experimental paradigms, to descriptively analyze and plot the resulting data, and to choose and apply appropriate tests for statistical inference.
The aim of this seminar is firstly to enable you to better understand quantitative results as reported in published psycho- and neurolinguistics papers; and secondly to provide you with the knowledge and tools necessary for your own quantitative analyses, e.g. in case you aim to collect experimental data in your thesis.In class, we will be using the open-source software R and a number of R packages. If possible, please bring a laptop and download and install R (https://cran.r-project.org/) before the first session.Please note that this seminar will likely not be held weekly, but in blocks. We will agree upon the specific dates and times of the remaining sessions in the first session and I will do my best to accommodate all attendees.The seminar will be held in English.