2. As George Box famously noted: “…the statistician knows…that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive results which match, to a useful approximation, those found in the real world.” (JASA, 1976, Vol. 71, 791-799) Therefore, the normality assumption will never be exactly true when one is working with real data.
Is linear regression valid when the outcome (dependant variable) not normally distributed?. Available from: https://www.researchgate.net/post/Is_linear_regression_valid_when_the_outcome_dependant_variable_not_normally_distributed [accessed May 17, 2015].