Covariance and correlation

[cgabt]

Good content lasts forever. This has been useful for me, old engineer dog in his mid 50's, relearning statistics. I couldn't get my head around the differences between these two measures - your video did the trick!

[SpartacanUsuals]

Hi, thanks for your comment. Good question. Essentially what it means is that the maximum covariance between two random variables, X and Y, is given by when the two variables are the same. In this case the sqrt(var(x).var(x))=var(x). The proof of this depends on the Cauchy-Schwarz inequality, and was a little too involved for me to post here. However, I have added it to my list of videos to do in the future. Best, Ben

[meshreporting]

These videos have been nothing but helpful. Thank you so much! 

[harunsuaidi]

Ah, so that's where it comes from. I'm an Art graduate learning Statistics for my master degree in Instructional Technology. I never quite got how one could figure out the mathematical expression of the relationship between two sets of data. Now that you explained it, it becomes much clearer. Damn, mathematicians are smart.

[talkohavy]

Well done!
I'm taking a course called Linear Regression
and I learned a lot from your video.
Thank you for the lesson.

[darynaivaskevych]

Thank you for the brilliant explanation!
I finally understand why these formulas are like this.

[h-s]

this video was just a piece of art ! thank you so much! well explained and really clear and smooth !

[gabrielasantana]

This guy just has a video for every question, thank you

[tjfirhfjejUTH]

good video very clear. if anyone is having trouble make sure you really understand joint pdfs, and expected values.

[batuhantekmen]

Very intuitive and can be watched along with a formal explanation or numerical calculations! Thank you.

[emilylawrence]

What kind of people disliked this video? this video is amazing! Thank you Ben!

[antibioticsOfWorld]

thank you !! i am doing masters in data science and it helped me to understand the basics properly

[edentrainor]

This is such a damn clear ad well explained explanation it hurts.

[COSMOPOLITANWORLD]

You made it easy to understand! Thanks a lot!!

[myvoice]

Hello Sir, You are such a good instructor.Great May God Bless you and your loved ones..

[kejeros]

Thank you so much. I am actually getting excited for this final now. haha!

[tymothylim]

Thank you very much for this video, Ben. It really helped me understand the intuition behind the formulae, as well as the relation between Cov and Corr! The visuals helped a lot with explaining, too!

[Jdonovanford]

I've read that the formula for betas is beta=cov(x, y)/var(x). However, the formula given in many places for betas does not divide by n (or n-2): IN this formula, neither the numerator or denominator are divided by N or n-1… to be called covariance and variance.

[shashikalaraju]

Perfect. You are amazing teacher. You inspire me. Thank you

[katiegraham]

This is an awesome explanation. It would be even better if there was an example to accompany it