Thanks for an excellent introductory presentation to linear regression. Your mnemonic for the assumptions is helpful, but perhaps it could be extended to include additional assumptions that complete the term LINEAR: Linear relationship between predictor and response variables Independent residuals (no autocorrelation) Normally distributed residuals Equal variance of residuals (homoscedasticity) Absence of external-variable predictor correlation (tertium quid) Removed multicollinearity issues Chuck
@@marinstatlectures Hi there, thank you for your video. I am on the website but I do not have any idea which one it is. FEV stands for what? First time on the channel.
@@marinstatlectures Opened one by one, the file with the same columns aren't there? What would be a shame, because you did a very good video explaining but without the practice exercise it is like only 50% of the job done.
Thanks for an excellent introductory presentation to linear regression. Your mnemonic for the assumptions is helpful, but perhaps it could be extended to include additional assumptions that complete the term LINEAR:
Linear
relationship between predictor and response variables
Independent residuals (no autocorrelation)
Normally distributed residuals
Equal variance of residuals (homoscedasticity)
Absence of external-variable predictor correlation (tertium quid)
Removed multicollinearity issues
Chuck
yeah, thats a good way to add a few more important conditions to the list :)
Hi...Thanks for all your magnificent work!!... Could you put a link with the "fev" data set?... All the best...
you can find it on our website: www.statslectures.com
@@marinstatlectures Hi there, thank you for your video. I am on the website but I do not have any idea which one it is. FEV stands for what? First time on the channel.
@@marinstatlectures Opened one by one, the file with the same columns aren't there? What would be a shame, because you did a very good video explaining but without the practice exercise it is like only 50% of the job done.
@@marinstatlectures Hey, I can't find that dataset called fev