Winter 2010:

course title

MM6 Methods and Statistics

instructors

Shravan Vasishth and Reinhold Kliegl

dates and location

First and second week: 19.10.2010, 21.10.2010 in Haus 4 room 4.15/16
Tuesdays and Thursdays 1415-1545 Golm campus, Haus 14, Room 4.15/16 until further notice.

important information on course

This is a four-hour course; students will be expected to attend both classes every week. It's 12LP.

what this course is about

This is a 4-hour graduate level course on the use of statistical methods for data analysis, with a focus on the analysis of psycholinguistic data, specifically self-paced reading, reaction time, eye-tracking, and EEG data. We will begin with an overview of foundational ideas in statistical hypothesis testing, along with an introducing to the freely available programming language R, which is used widely in statistical data analysis.
The second part of the course will cover issues related to specification of linear models (e.g., contrasts), advanced topics such as (generalized) linear mixed models, (generalized) additive mixed models, and possibly also structural equation models. The course aims to attract not only students of psycholinguistics and experimental psychology, but also students working in biology, geology, etc., with an interest in these statistical models. The course will attempt to accommodate and to foster interdisciplinary exchange, using advanced data analyses as a common platform.

prerequisites

We presuppose no background in anything but high school (pre-calculus) mathematics. Programming background will help but is not necessary.

grading

Grading will be based on the grades of homework assignments and in-class quizzes.
Final scores will be based on the following mapping described in the Studienordnung: 95-100%=1,0 (A);90-94=1,3 (A-);85-89=1,7 (B+);80-84=2,0 (B);75-79=2,3 (B-);70-74=2,7 (C+);65-69=3,0 (C);60-64=3,3 (C-);55-59=3,7 (D+);50-54=4,0 (D);45-49=5,0 (F). If a student's score falls between the cracks, it will be treated as falling in the higher bin.
Students are expected to attend class regularly. If a class is missed, the student is responsible for finding out what the assignment was, what readings were assigned, and what material was covered.