R Squared or Coefficient of Determination | Statistics Tutorial | MarinStatsLectures

[@marinstatlectures]

In this video Mike answers these questions and more while writing backwards working through an example! What is R squared or coefficient of determination or R2 and how to interpret it in regression analysis? Is R squared the same as correlation coefficient? How do you calculate R squared? What are the limitations of R squared? What is adjusted R squared?

[@anuragmukherjee1878]

Finished the whole series for the second time. Hopefully, visit again to brush up! Thanks! "Stay cool out till then" Copying the same comment I had from last year. I love Mike Marin.!

[@manishjandu7333]

Last video in the data science playlist, loved your way of explaining at last it is helping me to connect all the dots in ML. And also I watched every video to the last just to listen your sons voice. "Stay cool out guys coz we got lots more" Really your education is changing many lives. Stay blessed and keep educating. Thank you really.

[@anuragmukherjee1878]

Finished the whole series for the second time. Hopefully, visit again to brush up! Thanks! "Stay cool out till then"

[@sudhakarmadakaful]

What is commendable is your resolution to not sway off the topic covering all the basics conceptually. Gratitude to you, your team, and the ones with a big heart to allow uploading on youtube.

[@davehunt0000]

Thank you Mike. That was a really clear explanation and really helped me.

Excellent series, keep it coming!

[@samantadm8269]

You are amazing (: Thank you so much! all your videos have such clear explanations

[@user-bz7fj1fk2m]

So nice and valuable explanation. Thank U.

[@flamboyantperson5936]

Great Tutorial. Keep the good work going. Thanks a lot.

[@lukcho901]

We usually define R^2 as a number taking values from -Inf to 1, where negative values indicate that the model gives a worse estimation than the mean.

[@marinstatlectures]

this may be something else you are thinking of. in the case of no relationship between X and Y you will end up with a line with a slope of 0, and in this case your predicted value for everyone is the same...it will be the mean of Y. you may be thinking of some slightly different measure of model fit.

[@munsirali1896]

Great sir thank you very much for sharing your's knowledge with us. Looking forward to watch more and more videos in this series. Once again thanks for your precious time.

[@sanjanakhedekar7651]

beautiful explanation !

[@bezahunasrat1335]

Excellent!

[@quantumudit]

Please upload more videos on linear regression, validation, cross validation, logistic regression

[@marinstatlectures]

we will be creating videos for some of those topics in the coming summer. in the short term, we are working on some videos for using R...namely, making plots with "ggplot2" and some other videos around topics with the "tidyverse"

[@Jishijet]

Great series of video lectures, thanks. Can you recommend the best stats book in your opinion that gives a broad overview of most things. Thanks

[@marinstatlectures]

That’s hard to say, as it really depends on the subject area, etc...but I’d probably recommend the following...and it’s free! r4ds.had.co.nz

[@qudsif]

Hey, thank you for your videos. Is this the last video of the series or will you upload more?

[@marinstatlectures]

we will continuously upload more, although it will take a bit more time before we are able to record and edit new videos. we are planing on creating a series for using ggplot2, and dplyr, and a few other packages from the tidyverse as our next content

[@ldpy33]

Here's the question: IS THE ANSWER E? Which of the following tells us how strong the relationship is between two variables? a) the slope of a line b) the intercept of a line c) the coefficient of determination d) the coefficient of correlation e) both C and D are correct

[@aination7302]

Since correlation takes values between -1 & 1, R2 will take values between 0 & 1. Hmmm..

[@marinstatlectures]

Yup, the multiple R square is Pearson’s correlation squared, in the case of simple linear regression

[@willywilly9919]

Can you please answer this: "The computational expression for coefficient of determination in simple linear regression through origin" Thank you

[@nwgverified]

Epic