I recently reread some statistics books and noted something weird: They all discuss the assumptions of linear regression and mention the need for a normal distributed dependent variable. In the next step, there is always a discussion of variables which are non-normal and potential "cures" like sqrt, log, inverse etc.
But the books are never going to discuss how to interpret the transformed variable - which strikes me as odd, since a sqrt function changes the interpretation from "the GDP of a state increases by 1 when the social-freedom index increases by 1" to "the square root of GDP of a state increases by 1 when the social-freedom index increases by 1", which is quite a difference.
Can somebody point me to some good explanation about this?