A question on approaching regression analysis when all Y - X correlation is low; almost all |correlation| < 0.1
To give an outline of data I have:
- Y (Store sales by month); n>2000
- Xi (Macro-economic data, Store type (binary variable for each type), Marketing score(eg. numeric data such as brand awareness); about 15-ish in total
I tried running regression, checking multicollinearity (VIF), clustering (K-means), feature selection (forward/backward selection) but nothing is giving me a tangible result.
My management wants to see an analysis so 'insufficient data' is not a viable conclusion at the moment (they want to see "something") so would really love to know what options I have left in this case.
Any help would be appreciated and thank you in advance!