course title
Statistical methods

instructor
Shravan Vasishth

tutor
Sabrina Gerth

dates and location
Mondays and Wednesdays 1015-1145, Golm campus, Haus 24, room 1.78/79 (Computer pool)

what this course is about
This is a 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 studies, eyetracking data, and EEG data.

prerequisites
I 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. The EMCL group has a different grading scheme; if there are any EMCL students in the class I will adjust the grades to match their Studienordnung.
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.


conduct in the classroom
  • Please do not engage in private conversations during class.
  • All cell phones must be switched off (except by permission from me).
  • Please do not surf the web or read email while the class is on.
  • Please do not walk into class after it starts, unless you have a really good reason to be late (example: Deutsche Bahn screwed up yet again). 10:15 is the deadline to be ready for class.
  • Questions to the instructor are actively encouraged.


    • textbooks
    We will consult the following online books:
  • R for beginners by Emmanuel Paradis
  • The foundations of statistics: A simulation-based approach by Shravan Vasishth and Michael Broe
  • Gelman and Hill 2007 I recommend you buy this book.
  • Baayen 2008 (buy if you can, but not necessary to do so)

    rough schedule
    Please sign up on moodle to get the reading material, slides, assignments, etc. Sign up here.

    topic dates slides, readings, in-class exercises homework
    Part 1: Intro to R April 19-May 12 (8 lectures) to be provided on moodle Shravan
    Part 2: Statistical foundations May 17-June 9 (8 lectures) to be provided on moodle Shravan
    Part 3: Applications and advanced topics June 14- Shravan