CASUS Hands-on Software Seminar, Dr. Lennart Schüler, CASUS

Bayesian statistics are conceptually easy to understand, but very difficult to apply correctly. Probabilistic programming arose from this contrast and its aim is to make statistical inference as easy as “pressing the inference button”. The inference steps are thus clearly separated from the model creation, which makes it possible for the user to concentrate on modelling, evaluation, and interpretation. In this seminar, you will learn the basics of probabilistic programming using PyMC3, which is based on Python and has an easy to read syntax.

Due to a CASUS-related time conflict, the seminar had to be re-scheduled from 4 November. Our apologies to all participants and especially to the speaker.