Freedman's paradox
id:
freedman-s-paradox-277-6057286
title:
Freedman's paradox
text:
In statistical analysis, Freedman's paradox, named after David Freedman, is a problem in model selection whereby predictor variables with no relationship to the dependent variable can pass tests of significance – both individually via a t-test, and jointly via an F-test for the significance of the regression. Freedman demonstrated that this is a common occurrence when the number of variables is similar to the number of data points. Specifically, if the dependent variable and k regressors are ind
brand slug:
wiki
category slug:
encyclopedia
description:
Statistical paradox
original url:
https://en.wikipedia.org/wiki/Freedman%27s_paradox
date created:
date modified:
2023-10-09T16:21:51Z
main entity:
{"identifier":"Q5500406","url":"https://www.wikidata.org/entity/Q5500406"}
image:
fields total:
13
integrity:
14