Timeline for Normality requirements across tests

4 events

when toggle format	what		by	license	comment
Dec 19, 2014 at 3:22	comment	added	SmallChess		It all depends on assumption. The most common statistical tests assume normal distribution in some sorts because it's simple and common for most applications. But there is no such thing that normal distribution is a must. We're simply trying to build a model that fits most cases nicely without complicating a model too much.
Dec 19, 2014 at 2:37	answer	added	Glen_b		timeline score: 2
Dec 19, 2014 at 0:27	comment	added	Silverfish		Re 'normality is required for regression' - there is no requirement that residuals be normally distributed. Sometimes residuals are modelled as having another distribution, such as skew-normal. Estimates of coefficients are still BLUE because the Gauss-Markov theorem doesn't assume normality. However, if you want to use the t distribution to do inference or construct confidence intervals for those parameter estimates, or use an F test on the regression as whole, the normality assumption (and the extent to which the CLT can overcome deviations from normality in large samples) becomes relevant.
Dec 18, 2014 at 23:49	history	asked	Gwen	CC BY-SA 3.0