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Thank you!

You have to look at the R Squared value and the significance of the coefficients (using the p-value). Generally a higher R Squared value will mean a better model and a lower p value of the coefficients will mean a better model.

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If you don't care then why did you watch it?

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Thank you! I would love to travel to Japan one day.

Thanks! Please subscribe to my channel and like the video. I intend to make more helpful videos.

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Good question. There are three methods. First you can look at the Adjusted R-Squared (not the R-Squared). Whichever model has the highest Adjusted R-Squared that is likely the best model. Another method is to look at the T-scores of the B1, B2, and B3 variables. If all T-scores are significant, then it means we have evidence to not reject those variables. Lastly we can run an F-test on the three variables: B1, B2, and B3. If the F-test is significant, then we can keep the additional variables. You can watch this video to see how an F-test is conducted, called "The F statistic - an introduction" by Ben Lambert: th-cam.com/video/ie-MYQp1Nic/w-d-xo.html

No problem - let me know if you need help with anything else.

I'm planning on making another video on how to do this in Excel.

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