Teaching

Course: Statistics (WS22/23)

Lectures: Mondays and Wednesdays, 12:00 - 12:30, Hörsaal (MI)
Exercises: Fridays, 10:00 - 11:30, Hörsaal II (Physik - Züplicher Str. 77)

In this course we will study selected chapters from the broad field of statistics, starting with some theoretical foundations, such as unbiased estimation and confidence regions. We will then proceed to the general theory of normal distributions and conclude with linear regression and ANOVA. Applications of the theory using R (or some other preferred programming language) will be covered during the exercises.

Understanding of concepts from the course “Introductions to Stochastics“ is a requirement.

Further information and news about the course can be found on ILIAS. Lecture notes and problem sheets will be made available on ILIAS.

Literature
  • R. M. Dudley. Real Analysis and Probability. Cambridge Studies in Advanced Mathematics. Cambridge UniversityPress, second edition, 2002.
  • B. Efron and T. Hastie. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Cambridge University Press, USA, first edition, 2016.
  • H.-O. Georgii. Stochastics. Walter de Gruyter GmbH, Berlin, second edition, 2013.
  • R. W. Keener. Theoretical Statistics: Topics for a Core Course. Springer Texts in Statistics. Springer New York, 2010.
  • J. Shao. Mathematical Statistics. Springer-Verlag New York Inc, 2nd edition, 2003.

Old courses and seminars

Research

Submitted papers/Preprints

Published/Accepted papers

Some conferences/workshops where I have given a talk

Mini CV

Since this is supposed to be a sort of CV website, I should probably list a couple of things that define me. In no specific order, here's a few things I have done.