I'm investigating how some weather variables (15) affect electricity demand in a specific area during the last 20 years. I was thinking to perform the following steps: 1. Perform Multiple Linear Regression on each subset of selected variables 2. Save t-statistics (p-values) for each run
Then, I would to show the statistics (median, min, max, quantiles) of the t-statistics for each variable in order to give an idea about which is the most influencing. Finally, I would also show the relationship between each variable and the mean square error obtained with regressions using it.
Do you think this approach makes sense?