Please pardon me if you find this question very silly but this doubt has been troubling me for some time now whenever I want to run a regression.
I am working on SAS. I have a dataset which has 24,000 observations, and there are about 50 independent variables. There are no missing values and/or outliers. Dummy coding for categorical variables is also done. So, data preparation is complete. Now, when I run a regression model on this dataset, there are a few variables (8 variables) for which p-value is > 0.05 i.e. these variables are insignificant.
My question is what next? Do we remove these variables from the final regression equation? So, instead of having 50 independent variables, we'll have 42 independent variables (42 Beta coefficients + 1 for constant). Or do we need to remove one of these insignificant variables and re-run the regression model to see if there's any previously insignificant variable becomes significant now?