I have a data set with 181 observations. I have 9 predictors and I have developed different regression models using ordinary linear regression and stepwise linear regression. Now I'm trying to decide which model to choose. Here's summary of the models that I want to choose from: enter image description here

RMSE% is RMSE divided by mean of actual data expressed as a percentage. and any column labeled CV means that I used 80% of my data to train the model and 20% to test and the last three columns with CV is obtained using the testing set. Those columns without CV uses all the data.

So I have two questions here:

  1. based on the fact that I am using linear regression and have only 181 observations, should I use training and testing set or should I just use R2 and RMSE?
  2. according to R2 and RMSE, model 2 is better. But is it a good model as the RMSE% is 14? isn't it too high? does it mean that I'm overfitting?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.