1 / 45

Multiplicity in Hypothesis Testing: Theory and Applications

The discussion revolves around the challenges posed by testing multiple hypotheses simultaneously in the era of big data, citing the work of renowned statisticians like Fisher and Tukey. Various methods for controlling Type I errors in multiple testing scenarios are highlighted, including the concept of False Discovery Rate (FDR). The idea of ranking and selection in multiplicity testing is explored, emphasizing the importance of constructing a reliable "top table" for further investigation. The talk delves into theoretical approaches for determining the optimal number of hypotheses to follow up on in large-scale studies.

extramiana
Télécharger la présentation

Multiplicity in Hypothesis Testing: Theory and Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


More Related