I have several data to work with in order to select models.
Some of the predictor variables vary from 0 to more than 2000 square meters(Area). And some goes from 200 to 800 meters(Altitude). Others from 0 to 30 degrees(Slope). All of them have non-parametric distributions.
My response variable goes around 50 units.
Does it make any sense using log for some variables and scale for others so I can get less skew for my predictor variables? Or should I use log only or scale only for the entire dataset?