Why do we do the one-factor ANOVA instead of just doing a bunch of t tests? When doing many non-independent tests, our assumptions used to calculate p values fail. When doing many non-independent tests, our assumptions used to calculate alpha values f When doing many tests, the type II errors adds up and this allows us to keep this low. When doing many non-independent tests, our assumptions used to calculate t values fail. When doing many tests, the type I errors adds up and this allows us to keep this low.
Why do we do the one-factor ANOVA instead of just doing a bunch of t tests? When doing many non-independent tests, our assumptions used to calculate p values fail. When doing many non-independent tests, our assumptions used to calculate alpha values f When doing many tests, the type II errors adds up and this allows us to keep this low. When doing many non-independent tests, our assumptions used to calculate t values fail. When doing many tests, the type I errors adds up and this allows us to keep this low.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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