I am researching the effect of parameters on energy consumption. To determine the effect of parameters, I want to use the R Studio's F-test. In this way I want to investigate if the model with the parameter (dummy categories) is significantly better than a model without the parameter. Here I run into a problem. My dataset has a very high skewness and kurtosis, resulting in fact that the linear regression assumptions are violated. I tried to solve this with a transformation (10log) of the dependent variable. The skewness is now lower (less than 1), but the kurtosis is still high (around 4, which was 30 without transformation). The assumptions now seem to be a bit better, but there are still fat tails in the qqplot. I was wondering if the test is reliable after the transformation? Or is the F test not affected by violated assumptions and is it possible to make the F-test reliable without transformation? And if the F-test isn't relaible with and without transformations, which other way can I use to test the significance of a parameter.
Thanks in advance:)
These are the regression outputs of the regression on the dependent variable (energy consumption) without transformations