I have data with an explanatory variable $X$ (I think I can treat this as continuous, as scores 1-100 on a certain test) and a response variable $Y$ (continuous variable, never lower than 0). Both are NOT normally distributed ($X$ is close to, $Y$ is not at all).
I wanted to do a regression, using
glm() in R. However, I cannot decide what family/link function to use.
I found that it does not really matter that my $X$ is not normally distributed. However, it does that my $Y$ is not. There are many 0 observations, i.e. skewed right. Doing a log transformation of this variable makes it more difficult to interpret the results, so I found that using
family = Gamma would be appropriate. However, I do not know / understand how to choose a link function. Should it be inverse, log or identity? How can I choose?