In statistics, in the analysis of two-way randomized block designs where the response variable can take only two possible outcomes (coded as 0 and 1), Cochran's Q test is a non-parametric statistical test to verify if k treatments have identical effects. It is named for William Gemmell Cochran. Cochran's Q test should not be confused with Cochran's C test, which is a variance outlier test.
Read more about Cochran's Q Test: Background, Description, Critical Region, Assumptions, Related Tests
Famous quotes containing the word test:
“We do not quite say that the new is more valuable because it fits in; but its fitting in is a test of its value—a test, it is true, which can only be slowly and cautiously applied, for we are none of us infallible judges of conformity.”
—T.S. (Thomas Stearns)