Wednesday

11 Nov/20

15:00 -16:00 (Europe/Zurich)

PHYSTAT seminar: Testing Goodness-of-Fit

Almost all statistical analyses begin with the words: If the data comes from an XYZ distribution, then …, so an obvious question is: how can we be sure that a certain data set has been generated by a given probability distribution?
In this talk I will discuss some of the many tests that have been developed for this question, starting with the grandfather of all goodness-of fit tests, Pearson’s chi square. Other tests include Kolmogorov-Smirnov, Anderson-Darling, Zhang’s likelihood tests, Neyman’s smooth tests etc. I will also talk about gof testing in higher dimensions and issue of the curse of dimensionality. I will discuss a number of power studies that show a simple truth about goodness-of-fit testing: one size does not fit all!

The seminar will be done remote only.

Password: 152560