thanks homie

@mayito3334

6 жыл бұрын

lol

I wish I had a teacher like you lol 😅 why is KZread the best teacher

Thank you, straight and to the point. Great lesson.

Aw my God, I trailed through article after article after article of stuffy old lecturers basically debating whether it was good to use the correlation of determination or not and I found this video and within two minutes I learned how to report it the way I wanted to. THANK YOU!

I read untold articles including my text book and you explained in within 2 minutes and 47 seconds.

@rvcmathprof

4 жыл бұрын

Thank you for your feedback! Glad it helped.

Such a helpful video. Thank you for explaining in a very simple manner that is easy to understand!

Thank you for this very simple explanation! With a now online statistics course, your video was extremely helpful.

@rvcmathprof

4 жыл бұрын

So glad it helped!

Thank you! Someone finally made sense of this!

Wonderfully and simply explained, Thank You so much

simple and precise... Thanks a lot for the lesson ❤️

Thank you for explaining the interpretation so well :)

simple and great explanation. Helpful.

So, they both tell us how strong the relationship is between two variables?!

Amazing explanation. All your videos are very helpful. Thank you so much.

You are a very good teacher, madam. A lot of Respect here

Can I find the other to calculate. The longer one. As the regression equation we have calculated and from there we calculate the coefficient of determination..

Thank you for the explanation..... It is straight forward and It helped me a lot

omg, I love you. Thank you for this video. It helped me answer a question from my HW and my professor was impressed. LOL

Perfectly done,.11yrs now.Still using her knowledge 😊🎉

Straight to the point. Awesome video

Perfect explanation; thank you!

Great video ! But how do you calculate r if you don't have it ?

Is Analysis of covariance (ANCOVA) used in the context of linear regression to drive R^2.

Thanks. I was looking for a video on the interpretation of the wording of coefficient of determination. Variation of Y is explained by X. Got it.

please madam i have one question....when i work my research paper on multiple regression my adjusted R square is become only 0.032 meaning only 3 percent of the variance in dependent variable is explained by my independent variables right??..so is it possible only 3 percent variance?..if not how can increase Adjusted R square??

A big thank you from South Africa!

Thanks this helped a lot to study for my final! :D

teacher is it the value of R-sequared is same as the value of coefficient of determination?

Wow crystal clear explanation

hi very helpful but what would happen if my r is a negative? will I still do the same process

Very good explanation.

@rvcmathprof

4 жыл бұрын

Thank you, glad you found it helpful.

You are AMAZING!!!!!! Thank you!!!

THANK YOU SO MUCH, YOU HELP ME ALOT FOR MY PRESENTATION.

so does rxy = r squared?

Thankyou soo much it was really helpful...

@rvcmathprof

4 жыл бұрын

Thank you for the positive feedback!

Thank you, this is a great explanation.

Thank you very much! I find this really helpful.

Wow! That certainly cleared it up for me! THANK YOU! So subscribing to your channel.

Wow am in love with your simple calculation

This is so helpful thank you so much!

Thank you soo much!! You really helped me.

Is this the same? 90% of the variations in the number of sick days incurred (y) is attributed to the variations in age (x). Thank you.

@rvcmathprof

4 жыл бұрын

Yes, yours is an application of the concept

How could I find the least squares regression line of the coefficient of determination !?!? This makes me so frustrated

If it’s not significant, do we do the coefficient of determination?

Thank you for this explanation

Thank you. I'm in a data analytics class and the teacher used Data Analysis tool to get R and R^2 but did not go into the meaning of the two variables. But why do we have R and R^2 , what does R mean on its own?

@42luke93

Жыл бұрын

In Excel

very clear and simple i wish you are my teacher

Thank you for this more simple explanation.

Great video!

in the end is r once squared =0.94^2, and then once again =(0.94^2)^2? so we get (r^2)^2?

@NemShrestha

8 жыл бұрын

+OlgaCS olgaolga Nah !!! Just multiplying by 100 to get in percentage

wow learned so much in 3 mins.

Great explanation

But what do you mean by "explained" and unexplained"?

how do you work out r. not very good

@jayaseto

6 жыл бұрын

Curious George Thanks a lot

Great lesson! Thank you.

@rvcmathprof

3 жыл бұрын

My pleasure!

Thanks for helping me mdm..

thanks for sharing ....helpful

where is the video where you find r?

why is coefficient of determination a square of correlation coefficient?

Okay but how do you get r????!!!!!! It's not in your last video like you said

Thanks, nice video

Thank you so much!

gawd damn that handwritting neat af

Thanks you soo much!!

thanks so much for this.

does Having a higher percentage mean the model is a good fit?

@rvcmathprof

5 жыл бұрын

yes, the closer r^2 is to 1 (or 100%) the better the fit

fantastic explanation!

@rvcmathprof

Жыл бұрын

Thank you so much!

Your sound is awesome

Very helpful thanks

@rvcmathprof

4 жыл бұрын

So glad it helped

great video

thank you. you explained it well..

@rvcmathprof

2 жыл бұрын

Glad it was helpful!

thank you easy and fast

Thank you very much maam.

Thanks for this

THANK YOU!!!

thanks this helped alot!

@rvcmathprof

2 жыл бұрын

Thank you for the positive feedback! Glad it helped!

thank you so much!!!!

You are good👍

@rvcmathprof

Жыл бұрын

Thanks 😁

very helpful

Best lady

ok but how do u find r 😭😭

thanks a lot

thanks very much!

@rvcmathprof

3 жыл бұрын

I appreciate your feedback!

Here's my attempt to explain the point that I think is missing (namely why the coefficient of determination is a percentage of the variation, why that is "explained by X", and why anyone bothers to square r). Without losing anything, you can assume X and Y have a mean of zero. Then the variation of Y can be thought of as the square of the length of a vector pointing in the direction of Y, which in turn is the hypotenuse of a right triangle formed by two vectors: one pointing in the direction of X, and and one orthogonal to it. (Direction and magnitude are with respect to the inner product induced by the probability measure.) The correlation is extracting the cosine of the "angle" between X and Y. The cosine, in turn, is equal to the length of the leg pointing in the direction of X divided by the length of the hypotenuse, which is the standard deviation of Y. The square of the standard deviation is the variation, which is equal to the sum of the squares of the length of the legs. Dividing these two squares of the lengths of the legs by the square of the length of the hypotenuse (the variation) shows you what proportion each contributes to the variation: one contribution from a vector pointing in the direction of x, and one from the remainder. A percentage makes sense with this understanding.

Thank you!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

awesome!

Thank you!

@rvcmathprof

Жыл бұрын

Welcome!

thank you

Thank you ma'am.💟

@rvcmathprof

3 жыл бұрын

I am so glad it helped

@chamitharathnayake4865

3 жыл бұрын

@@rvcmathprof Obviuosly that helped so much.

thank you mdm

Thanks

شكرا يا جده

i will stay determine :^}

Thanku mam

Why do we say that it(coeff of determination) is a measure of how much of the variation in y is predicted by the variation in x? The two variables are just correlated. By saying this, we are imposing a causal relationship between the two. AHHHH...This is so vexing. Can you or anyone please clarify this doubt?? Thanks...

@rvcmathprof

3 жыл бұрын

The coefficient of determination is just saying how strong the correlation between the explanatory and response variable is, not that one causes the other. The variation in y can be predicted by the variation in x without x causing y..

@anshumanbiswal2225

3 жыл бұрын

@@rvcmathprof Thanks Diane...I am more clear about it now.

Why is there an ad on this lol

thanks

Thnx mam

The sensation of watching this video fills you with *DETERMINATION* *file saved

@rvcmathprof

Жыл бұрын

Love the pun!!

Literally I'm watching videos of people making graphs means of y minus means of x and all this nonsense I can't understand where all you had to do was square r for the answer.. thank you..

@rvcmathprof

4 жыл бұрын

Glad the video was helpful