Is it possible to do a regression on average values of categories?
I have categories of function type, building year and surface (dummy variables of categories) and average values of energy consumption calculated with a total dataset (which I do not own, so I can not use the whole dataset). I want to show that the dummy variables need to be included in the model to predict the energy consumption. The regression on the averages gives a very high R squared.
Is it right to conclude that the explanatory variables can help predict the average energy consumption (which says nothing about the total variation)?
And can I conclude with this that the parameters are important for predicting the energy consumption of a building or is that not a right conclusion? This is the dataset I am using: https://www.cbs.nl/nl-nl/cijfers/detail/83376NED