Most scientists think that t-tests, ANOVAs, linear regression etc rely on your data being normally distributed. Is that really true? And given that no data is perfectly normal, how normal does your data have to be? Can I see what effect non-normality will have on my hypothesis testing? I’m going to use some simply tricks that us to see how bad our distribution is.
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