I have the following datasets of several variables:
- hourly data of the year 1990
- hourly data of the year 2000
- hourly data of the year 2010
Now, I was planning to select and estimate a linear regression model based on the dataset of the year 1990 and then validate/check its accuracy by applying the model to the other two datasets and compare the dependent variable based on the regression model with the actual dependent variable of the dataset.
Is this approach correct? If so - am I supposed to completely ignore the two validation datasets? By that I mean not even looking at it and doing descriptive analysis?
Note: All the datasets contain the same variables.