I have the following dependent and independent variables for my linear regression model. Since they are all in different scales (some of the are % others continuous variables), I was suggested to take the log and normalize my variables before running the regression.
Y X2 X3 (%) X1 (%) Mean 2.9 24.6 0.009517 230.992248 std 2.3 32.2 0.077092 230.992248 Min 0 1 0 0 Max 8 539 1 1
I have the following Qs:
Why should I take the log and then normalize them - rather than using just one of the two data transformations?
Should I log and normalize also my Y variable?
How would interpret my coefficient at the end of the exercise? and how can I make them humanly intelligible for a business audience?
Any easy doc reference is very appreciated!