I am trying to use linear regression to predict the earnings of the employed people (i.e. no zeros in my data set), however, no matter what I try, I can't get my residuals to be normally distributed.
I have tried things like
- log((earnings-median(earnings)/(max(earnings)-min(earnings)) +1)
- variety of different combinations of min, max, sd for the denominator
But nothing seems to work. qq-plot looked the best after square root transformation, however, the shapiro-wilk test rejected the normality.
Plus a bonus question. In a multiple regression, do I need to get normality of errors for all the dependent~ independent relationship pairs or only for the overall model (i.e dependent~ independendent1+ independent2...)?