160122 PR Data Analysis Sandbox (2022W)
Continuous assessment of course work
Labels
ON-SITE
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).
- Registration is open from Sa 03.09.2022 08:00 to Tu 27.09.2022 23:59
- Deregistration possible until Mo 31.10.2022 23:59
Details
max. 40 participants
Language: German, English
Lecturers
Classes (iCal) - next class is marked with N
dates and times of the following sessions will be agreed upon in the first session
Thursday
20.10.
15:00 - 16:30
Seminarraum 3 Sensengasse 3a 1.OG
(Kickoff Class)
Thursday
01.12.
09:00 - 11:00
Seminarraum 8 Sensengasse 3a 5.OG
Thursday
15.12.
09:00 - 11:00
Seminarraum 8 Sensengasse 3a 5.OG
Thursday
12.01.
09:00 - 11:00
Seminarraum 8 Sensengasse 3a 5.OG
Thursday
19.01.
09:00 - 11:00
Seminarraum 8 Sensengasse 3a 5.OG
Thursday
26.01.
09:00 - 11:00
Seminarraum 8 Sensengasse 3a 5.OG
Information
Aims, contents and method of the course
Assessment and permitted materials
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.
Minimum requirements and assessment criteria
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.
Examination topics
Relevant books chapters and papers will be supplied on Moodle over the course of the seminar.
Reading list
Association in the course directory
BA-APM10b
Last modified: 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.