Nonparametric predictive inference for reproducibility of hypothesis tests

Seminário de Estatística e Gestão do Risco

by Frank Coolen, Department of Mathematical Sciences, Durham University, UK .  

Data | Hora: 10 Outubro de 2018 | 14H00

Local: Sala 1.9 - Edifício VII 

Abstract: Nonparametric predictive inference (NPI) is a frequentist statistics method based on few assumptions, with uncertainty quantified by imprecise probabilities. After a brief introduction to NPI we will apply it to investigate reproducibility of several basic statistical hypothesis tests, considering the question whether or not the final test result wrt rejection of the null hypothesis would be the same if the test were repeated. This is an important practical issue which has received relatively little attention, and about which there is a lot of confusion. We end the presentation with a brief discussion of related research challenges.

Financiado através do projeto UID/MAT/00297/2013.