13.7 Regression tables
- each column represents a different regression
- parentheses: usually standard errors (sometimes t-statistics)
- significance stars –> p-values (author isn’t a fan)
- below: descriptions of analysis/measures of model quality
- adjusted \(R^2\) consideres number of variables
- \(F\)-statistic: null: all the coefficients in the model are all zero
- RMSE: estimate of the standard deviation of the error term
What can we do with all of these model-quality measures? Take a quick look, but in general don’t be too concerned about these.
If you don’t care about most of the causes of your dependent variable and are pretty sure you’ve included the variables in your model necessary to identify your treatment, then \(R^2\) is of little importance.