Covariance vs Correlation with simple data | Covariance vs Correlation Coefficient

[@saikiranreddymekala1346]

In the formula of cov(x,y) the denominator is N-1 . Can you please correct this sir!

[@UnfoldDataScience]

I will pin this on top of the video.

[@pkavenger9990]

actually if you are applying this formula on sample then its N-1 otherwise if you are applying on population then its N.

[@vaibhavpandey7398]

@@pkavenger9990 thanks

[@ShivUpadhyay-s6q]

i have bought classes but my teacher explanation was not so good , after watching many different videos i find this THE BEST. Thankyou for making this video

[@SomnathGupta-gu2rm]

You are a Genius Sir. Thank You So Much for making these Concepts Simple and Lucid. May God Bless You 🙏🙏💐💐

[@jigyasasoni1812]

with in a 1:30 sec.... i can say, you are the best teacher.

[@UnfoldDataScience]

Thank you Jigyasa. Your comments mean a lot to me

[@sathwiksharma4133]

beautfil explanation sir , every one teaches formula and complete explanation but you have explained why this formula dn explained it in very detailed manner thankyou sir

[@best_movies3736]

You are simply the best! The MasterBlaster in Data Science

[@UnfoldDataScience]

Thanks alot Thurab. Continue watching

[@rishabhsheoran6959]

Kaafi achhcha samjhaya bhai! Good work!

[@UnfoldDataScience]

Thanks Rishabh, thoda share kar dijie apne groups me :)

[@kavyanagesh8304]

You are the best teacher! Got goosebumps while listening to your lecture. Thank you so much!

[@UnfoldDataScience]

Thanks Kavya. Pls share with friends as well. Keep learning

[@ayushagarwal7284]

Awesome video sir...Keep shining😀

[@Nannyhere]

Just watched it before exam and in one go ,i understood the concept ❤keep making such videos sir 🥰🥰

[@launchdome3219]

very helpful...good job

[@UnfoldDataScience]

Thanks a lot.

[@gaytriray7019]

You are amazing at what you do! Your passion and dedication is beyond words! Thankyou so much sir.

[@UnfoldDataScience]

Thanks Gayatri for motivating me through your comment.

[@ajaykumarsahoo1404]

Hey I have a doubt. When you change the value of a y variable from 32 to 48 .. Will it mean remain same that means mean will not change? If change then how can you subtract the previous mean from the new value of y?

[@UnfoldDataScience]

Let me check once.

[@simplicityandchaos976]

Changing the value of Y variable from 32 to 48 changes overall mean of Y and hence it cannot be subtracted from the previous.

[@soheilaahmadi4807]

Was amazing. Happy to find your tutorials on RUclips.

[@UnfoldDataScience]

Thanks Soheila.

[@udayteja6595]

sir, when you have changed 32 as 48 then the mean also should change . So, it will effect all the variances in numerator , not only the last one.

[@tanmaypadhiar3529]

yes same doubt

[@balajinatarajan1051]

Excellent video

[@UnfoldDataScience]

Thanks Bala.

[@niii5715]

how calm u r while talking man ,excellent explaination! Hats off 🙇‍♂

[@leilyb5224]

Perfect 👍👍👍👍

[@UnfoldDataScience]

Thank you

[@BajiShaik-z4f]

Very well explained

[@prasadgpa6813]

You nail it in every your videos . You sell the simplified knowledge . Keep it up and may God bless you.. Can't wait for more such videos :)

[@UnfoldDataScience]

Thanks Prasad for motivation.

[@pokejishnu]

Amazing explanation Aman bhai ... Made it sound so simple. Thanks this helps.

[@UnfoldDataScience]

Thanks Jishnu da.

[@kiranpol1601]

wow... What a explanation

[@UnfoldDataScience]

Thanks Kiran.

[@sudhakarvasa2688]

When Yi value is changed from 32 to 48 mean of y will also change

[@Nandini-Maharaj]

Amazing video! Such simple explanation, you earned a loyal subscriber today :)

[@deepseaoflove3683]

Sir.. Divide by N Or (n-1) for finding convariance? In some lectures it is showing as by ( n-1)

[@UnfoldDataScience]

Does not matter if your sample size is large.
See these answers:
math.stackexchange.com/questions/2936143/do-i-use-n-or-n-1-as-the-denominator-for-covariance

[@johnsubhash]

@@UnfoldDataScience then, will it matter if it’s the case of small data set..?
What should we take then.??

[@karthikaanilkumar]

IT'S REALLY AN EASY CLASS AND THE WAY OF YOUR PRESENTATION IS GREAT.

[@shrutiathoi]

Sir, one question..
If we change the value the y from 34 to 48 than also the mean will be changed again?
Its an confusion pis clarify

[@sexycurse]

Amazing explanation brother..Good Job..👍👍👍

[@bayz4918]

it is good keep it up

[@tusharbedse9523]

Nicely explained again Aman!

[@UnfoldDataScience]

Glad you liked it Tushar.

[@k.vvishwanathan7341]

Pls clear my doubt.covariance is the way two variables move. Whether positive or negative but what is correlation of those Variables. How much have they moved ? Like if covariance is nearby to -1 then the two variables move in the opposite direction?

[@sameerpandey5561]

Beautifully explained!!...Thanks for such content

[@UnfoldDataScience]

Thanks Sameer.

[@RAGESS4]

Thank you sir. You're a great teacher.

[@UnfoldDataScience]

Welcome.

[@vcalls9146]

How the new data is handled after the model is moved to production. Example: During model development the categorical data is converted to 1 and 0 using one hot encoding... When the new data is applied in production how the categorical data or text data is processed..

[@UnfoldDataScience]

good question, u encode again and then predict.

[@financenanchahal8801]

Amazing explanation sir.....

[@vidyaanvekar]

Thanks for the wonderful explanation. You made my understanding very concrete.

[@UnfoldDataScience]

Welcome Vidya.

[@nagamuthu4382]

i would like to compare the advances level in banks. is covariance useful to compare the gross advances of public and private sector banks for 10 years.

[@UnfoldDataScience]

May be you can use advance technique. Its a simple technique.

[@karthickk6587]

Amazing Aman

[@UnfoldDataScience]

THanks Karthick

[@jananiravinag]

Great resource!

[@UnfoldDataScience]

Thanks a lot.

[@KamranNaqvi-r5w]

V good, thanks

[@omkarnarayankar5275]

Best explanation

[@humanafees8059]

Thank u so much I m.doing msc buisness analytics from Scotland seriously for every questions that hit me I come to ur channel I m.ur new subscriber God bless you

[@UnfoldDataScience]

Thanks for your words Huma.

[@animetalks2129]

sir can you suggest a tabelau course for me ? i am confused where to learn from ?.

[@ketakishitut2713]

Very well explained, thanks

[@RishabhRishab]

What purpose Covariance value / number is serving ? If I say sign of Covariance tells nature of relationship and Covariance value tells strength of relationship and there is no need of correlation .... how is this statement wrong ?

[@UnfoldDataScience]

Good question, however covariance is base of correlation hence that concept came first.

[@binitkumarsingh8409]

how to find standard deviation of x and y..basically that denominator

[@UnfoldDataScience]

We no need to compute from scratch, tool will help to do so

[@vinayverma9121]

You are amazing buddy you explained it so simply

[@UnfoldDataScience]

Thanks Vinay for your positive feedback. Please share with others as well who could be benefited from such content.

[@_itachi7904]

after so much of head banging finally I understood covariance & correlation....thank you so much...

[@UnfoldDataScience]

Thanks a lot.

[@haidiazaman3326]

fantastic channel, def deserves more views

[@UnfoldDataScience]

Thanks Haidi.

[@bipintiwari8751]

why exponential is calculated can you please explain that as well.

[@megabuzu2726]

Perfect explanation

[@UnfoldDataScience]

Thanks Matthew.

[@priyamkataria573]

Great content 🔥🔥

[@UnfoldDataScience]

Appreciate it Priyam

[@chikoo8486]

The unit you are talking about in covariance is +ve and -ve ??

[@UnfoldDataScience]

ya.

[@jay_with_the_real6381]

Excellent thanks!

[@UnfoldDataScience]

You're welcome!

[@omdodmani3205]

Loved it 😊! you made it very easy to understand thanks !

[@anaskhan4841]

Thank you Aman❤

[@yoharihernandez]

Thank you so much! it was hard for me to understand this concept until I found this video. Please keep doing more videos!

[@UnfoldDataScience]

Thank you Yohari! Will do!

[@siddheshbhalerao3013]

Thank you sir for clean explanation.

[@madhurakhaire6583]

amazing explination

[@UnfoldDataScience]

Thanks Madhu.

[@lakshaykhandelwal4284]

very well explained.. 👍

[@UnfoldDataScience]

Thanks Lakshay.

[@RamanKumar-ss2ro]

Thanks a lot for this topic.

[@UnfoldDataScience]

Welcome again :)

[@gangavijayan8906]

Why covariance is divided by standard deviation?

[@shabiyaahlam3217]

Helpd me a lot!

[@santoshsahu-oy5vo]

Dear sir, I am not getting it properly, kindly explain in detail both with detailed calculations...
Thank you so much for making the tutorials.
Could you please add graphs also with it so it will clear more...

[@champabanerjee1208]

You made it so clear....thank you so much 🙏❤️

[@UnfoldDataScience]

Welcome

[@UnfoldDataScience]

Access Hindi, English courses here- www.unfolddatascience.com/s/store
Plz register on the website

[@salmanjaved2816]

Thanks bro 👍

[@UnfoldDataScience]

Welcome Salman.

[@parol3271]

Thanks a lot . A very detailed explanation . Great yaar🙏👍👌

[@UnfoldDataScience]

Glad you liked it.

[@onuragmaji]

Good work bro ur teaching style is very cool, keep posting such great content

[@UnfoldDataScience]

Thanks Anurag.

[@m12gaming81]

sir ur doing great work luv u

[@UnfoldDataScience]

So nice of you

[@adityapatki151]

Hey I am data scientist too and really like your content . Can you make a video about how to select (statistically) control group size for marketing campaign?

[@UnfoldDataScience]

Thanks Aditya. Let me think through it. Thanks for asking.

[@soumyaranjansethi1790]

Amazing sir thank you

[@UnfoldDataScience]

Most welcome Soumya.

[@ashokmeena9631]

Sir what about virtual Interview

[@UnfoldDataScience]

Fill the form in the previous video. I will. Share invite.

[@sadhnarai8757]

Much needed,thanks :)

[@UnfoldDataScience]

Welcome :)

[@andresgrtz]

Thank you! Great teacher!

[@usmanzahid3711]

What exactly co variance is

[@sandipansarkar9211]

great explanation

[@UnfoldDataScience]

Glad you liked it

[@Manya2017]

Can you share the link of the data science group so that I can also join

[@UnfoldDataScience]

unfold_data_science on instagram

[@saurabsen3686]

Great presentation that is simple and to the point. However could not fully grasp when calculating correlation, dividing cov(x,y) by sd x multiplied by sd y yields a value between -1 and 1. Why so? Kindly revert.

[@UnfoldDataScience]

The explanation will be little more mathematical, please see the discussion here Saurabh:
math.stackexchange.com/questions/564751/how-can-i-simply-prove-that-the-pearson-correlation-coefficient-is-between-1-an

[@jrsolomon5960]

Thanks...this is very clear.

[@UnfoldDataScience]

Glad it was helpful!

[@learningsinlife]

mean will also change if 48 is made new observation

[@rediscovermath]

When you changed 32 to 48, mean will also change.

[@sandipansarkar9211]

finished watching

[@shubhamkumarjain1329]

Thank you so much... It helped a lot... But i want to know why it ranges between 1 and - 1 and not above that...

[@UnfoldDataScience]

Welcome Shubham, its because of internal mathematical formula.

[@suhatharsanyoganathapillai2203]

Thank you

[@UnfoldDataScience]

Welcome.

[@SumitSinghXd]

Great work .. These two terms were alien for me and the online website have complicated it more. Thanks to you I have understood it completely. just a single doubt , I have seen in many websites the denominator for variance is taken N-1 and in your video its N . which one should I go for

[@tgbyhn841997]

For population data N is taken and for sample data N-1

[@UnfoldDataScience]

Glad it helped!

[@UnfoldDataScience]

Thanks Rahul

[@kanamarlapudinaresh9934]

Thanks much.
In last formula, you mentioned (standard deviation of x) ( standard deviation of y ) in denominator. How we will calculate and can you explain.

[@UnfoldDataScience]

watch variance and sd video

[@Storiesbymanas]

nicely explained. thank you!

[@UnfoldDataScience]

Glad it was helpful!

[@emineakpnar6215]

it helped me a lot, thank you🙌

[@UnfoldDataScience]

Glad it helped!

[@rohitbhosale4614]

You are a champ!

[@UnfoldDataScience]

Thanks Rohit.

[@awanishmishra9782]

thanks sir

[@mosama22]

Thank you Amen :-) :-)

[@UnfoldDataScience]

Welcome

[@sudheerrao9820]

Thank you for the video Aman...if four features are positive correlated and four features are negative correlated out of 10 features in dataset...what should we do...I mean which are needs to be dropped and why?

[@UnfoldDataScience]

Good question Sudheer. To keep it short, choose the variables which are highest corelated with your target variable(Either positive or negative).

[@shoooooooooorts8002]

Please make video on statistics for data science A-Z

[@UnfoldDataScience]

ruclips.net/video/iZ2r7aIwMbc/видео.html

[@dr.sagarfirke2687]

Eexcelent

[@UnfoldDataScience]

Thanks Sagar.

[@humanafees8059]

One suggestion can u please make a video for detailed probability for beginners please it a request

[@UnfoldDataScience]

Thanks for suggesting, noted.

[@sanjeevkmr5749]

Amazing explanation. Please keep doing the great work. This channel deserves more!!!
I have heard that before training a ML model, it is advised to remove highly correlated features, Can you explain why?

[@UnfoldDataScience]

Hi Sanjeev, I created a detailed video for this question, Watch it on my channel today 7pm IST. :)

[@sanjeevkmr5749]

@@UnfoldDataScience Thanks a lot!

[@arihantchoudhary]

❤❤❤

[@afn8370]

thanksss

[@D.H.B-g8f]

Looks like while increasing the value of y you forgot to increase the mean of y