Box-Cox Transformation + R Demo

Overview of Box-Cox Transformations and an R demo using MASS package.

Thanks for watching!! ❤️

Tip Jar 👉🏻👈🏻

♫ Eric Skiff - Chibi Ninja

[khalilmomo]

Great, your voice is normally distributed

[aninditanalli]

I cannot begin to explain how much this helped!

[tetricattack]

Woah, this was great. Keep them coming!

[sanarovaz]

This is just great. Well paced stats videos with high resolution, good audio and implementations in code. Can't thank you enough.

[lucasketels]

We thank so much for saving our assignment with this video

[petemurphy]

That's a very well done video on Box-Cox transformations, I particularly liked the r demonstration and the diagnostic plots. It really bought the message home. Well done!

[thomasmartinlange]

Thank you for this amazing tutorial! You explain something complicated in a way that it's understandable. I hope for more tutorials from you!

[TheExodeth]

This was really great! Thanks for explaining it at a high concept level. Cleared up alot of confusion for me from the text. Also, the little trivia fact was very interesting! I don't think any of my professors even knew that. Kudos!

[FelipeSantos-swkk]

I've seen this video already twice and will many times more.

[skiffwhiffed]

Your the goat, thank you for this great content

[erod]

Thank you. Your walk through on this topic is excellent.

[fengyuwen]

Really clear and easy to understand, helped me a lot. And the funny story at the beginning is really interesting :)

[jasoncraggs]

Nicely done. Thanks for the practical demo!

[punksnotdead]

Great video. Really helped as trying to understand Box-Cox transformation right now

[francescorambaldi]

Thank you for your great explanation. Looking forward to more videos!

[pablo_brianese]

Just seeing the y^l = X b + e formula written down calmed down a lot of anxieties for me. I still don't understand why using this transformation would be a good idea.

Thank you very much for this video!

[websurfer]

To the point and very clear explanation

[adamo]

This is great. Main takeaway I learned is that if the best lambda is equal to zero then you want to log the dependent variable y. Otherwise, you don't need to log y. In this example, best lambda equals -1.42 so you would use a linear model specification (as opposed to log-linear or log-log). Hope this sounds correct.

[suginong]

Thanks, this is awesome help for R newcomers! :)

[nicolasfromcolombian]

Very good video! Greetings from Colombia!