Lecturer: Markus Pauly
Exercises taught by: Burim Ramosaj

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General Information

Language	English
Lectures	2 h
Exercises Office Hours	1h by appointment

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Time and Venue

Lectures Fridays, from 10:00 to 12:00, Room 131, N24

Exercises Wednesdays, from 10:00 to 11:00, Room E.04, Heho 22

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Exam:

tba

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General Informations:

Prerequisites:	Suitable for Bachelor students in "Mathematische Biometrie", "Mathematik" or "Wirtschaftsmathematik" (each in their last studying year). Attending students must have passed the lectures on "Elementare Wahrscheinlichkeitsrechnung und Statistik" as well as "Stochastik 1".
Exam:	If 60 per cent of all exercise points are achieved and if the participant at least once presented her/his solution of an exercise, then the exam degree will be upgraded to the next best degree (e.g., 2.0 --> 1.7 or 3.7 --> 3.3 etc).

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Contents: In applied practice, it is often not sufficient to test only one null hypothesis. For instance, after rejection of ``two groups possess the same location parameter''
the statistician may be interested in the specific ordering of both. Another example is motivated by a 1-factorial analysis of variance (ANOVA). Here, a rejection of the null ``all groups possess the same expected value'' gives rise to testing hypotheses about more specific differences among those. Since testing several null hypotheses with the same data-sets usually leads to cumulated error probabilities,
a theory for the construction of adequate multiple hypothesis tests is mandatory. During this course, such a theory will be developed and motivated on the basis of practical examples. As quality criteria of particular interest the concepts of classical FWER as well as of modern FDR control will be covered.

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Exercise Sheets & other Files:

Will be available on Moodle. Enrollment keyword for Moodle will be announced in lecture.

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Literature:

• Blakesley, et al. (2009). Comparisons of methods for multiple hypothesis testing in neuropsychological research. Neuropsychology, 23(2), 255.

• Dmitrienko, A. et al. (2010). Multiple testing problems in pharmaceuticalstatistics. CRC Press.

• Hochberg, Y. and Tamhane, A. C. (1987). Multiple comparison procedures. John Wiley & Sons.

• Lehmann, E. L. and Romano, J. P. (2006). Testing statistical hypotheses. Springer.

• Pigeot, I. (2000). Basic concepts of multiple tests – a survey. Statistical Papers, 41(1), 3-36.

• Shaffer, J. P. (1995). Multiple hypothesis testing. Annual review of psychology, 46(1), 561-584.

• Westfall, P.H. and Young, S.S.(1993). Resampling-based multiple testing: Examples and methods for p-value adjustment (Vol. 279). John Wiley & Sons.

Semesterapparat:

Click here

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