Covariance vs Correlation with simple data | Covariance vs Correlation Coefficient

Covariance vs Correlation with simple data | Covariance vs Correlation Coefficient
#CovarianceVSCorrelation #UnfoldDataScience
Hello ,
My name is Aman and I am a Data Scientist.
About this video:
In this video, In explain about covariance and correlation. This is an important statistics concept to know and hence I have explained the difference between correlation and covariance in this video through a simple data. Below topics are explained in this video:
1. Covariance vs Correlation with simple data
2. Covariance vs Correlation Coefficient
3. What is difference between correlation and covariance
4. Understanding Correlation vs Covariance
5. How is Covariance different from correlation
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[@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

[@SomnathGupta-gu2rm]

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

[@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.

[@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.

[@niii5715]

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

[@karthikaanilkumar]

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

[@user-pb6pt4rw1l]

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

[@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

[@best_movies3736]

You are simply the best! The MasterBlaster in Data Science

[@UnfoldDataScience]

Thanks alot Thurab. Continue watching

[@andresgrtz]

Thank you! Great teacher!

[@rishabhsheoran6959]

Kaafi achhcha samjhaya bhai! Good work!

[@UnfoldDataScience]

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

[@ketakishitut2713]

Very well explained, thanks

[@siddheshbhalerao3013]

Thank you sir for clean explanation.

[@soheilaahmadi4807]

Was amazing. Happy to find your tutorials on KZbin.

[@UnfoldDataScience]

Thanks Soheila.

[@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!

[@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.

[@vidyaanvekar]

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

[@UnfoldDataScience]

Welcome Vidya.

[@omdodmani3205]

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

[@champabanerjee1208]

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

[@UnfoldDataScience]

Welcome

[@anaskhan4841]

Thank you Aman❤

[@pokejishnu]

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

[@UnfoldDataScience]

Thanks Jishnu da.

[@sameerpandey5561]

Beautifully explained!!...Thanks for such content

[@UnfoldDataScience]

Thanks Sameer.

[@_itachi7904]

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

[@UnfoldDataScience]

Thanks a lot.

[@sexycurse]

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

[@omkarnarayankar5275]

Best explanation

[@financenanchahal8801]

Amazing explanation sir.....

[@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

[@ragess4rari100]

Thank you sir. You're a great teacher.

[@UnfoldDataScience]

Welcome.

[@bayz4918]

it is good keep it up

[@animetalks2129]

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

[@kiranpol1601]

wow... What a explanation

[@UnfoldDataScience]

Thanks Kiran.

[@ayushagarwal7284]

Awesome video sir...Keep shining😀

[@launchdome3219]

very helpful...good job

[@UnfoldDataScience]

Thanks a lot.

[@soumyaranjansethi1790]

Amazing sir thank you

[@UnfoldDataScience]

Most welcome Soumya.

[@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.

[@shabiyaahlam3217]

Helpd me a lot!

[@yogitabasnal]

Great explanation

[@UnfoldDataScience]

Glad it was helpful!

[@madhurakhaire6583]

amazing explination

[@UnfoldDataScience]

Thanks Madhu.

[@balajinatarajan1051]

Excellent video

[@UnfoldDataScience]

Thanks Bala.

[@jay_with_the_real6381]

Excellent thanks!

[@UnfoldDataScience]

You're welcome!

[@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?

[@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!

[@jananiravinag]

Great resource!

[@UnfoldDataScience]

Thanks a lot.

[@parol3271]

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

[@UnfoldDataScience]

Glad you liked it.

[@sandipansarkar9211]

finished watching

[@RamanKumar-ss2ro]

Thanks a lot for this topic.

[@UnfoldDataScience]

Welcome again :)

[@sadhnarai8757]

Much needed,thanks :)

[@UnfoldDataScience]

Welcome :)

[@sudhakarvasa2688]

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

[@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

[@haidiazaman3326]

fantastic channel, def deserves more views

[@UnfoldDataScience]

Thanks Haidi.

[@leilyb5224]

Perfect 👍👍👍👍

[@UnfoldDataScience]

Thank you

[@megabuzu2726]

Perfect explanation

[@UnfoldDataScience]

Thanks Matthew.

[@jrsolomon5960]

Thanks...this is very clear.

[@UnfoldDataScience]

Glad it was helpful!

[@afn8370]

thanksss

[@karthickk6587]

Amazing Aman

[@UnfoldDataScience]

THanks Karthick

[@Fact_O_Real07]

Hello Sir, so corr lies between -1 to 1 so, if -1 is coming means if we increase a little bit x then we will get high decrease in Y and if we get 1 then we increase X little bit then we will get higher increase in Y and for value near to 0 means , small change in X will make small change in Y, Is it like this?

[@UnfoldDataScience]

Close to 1(either side) means high correlation, means if you change X, Y ALSO changes. Close to zero means, not correlated means if you change X, you can expect no change in Y

[@Storiesbymanas]

nicely explained. thank you!

[@UnfoldDataScience]

Glad it was helpful!

[@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.

[@sandipansarkar9211]

great explanation

[@UnfoldDataScience]

Glad you liked it

[@emineakpnar6215]

it helped me a lot, thank you🙌

[@UnfoldDataScience]

Glad it helped!

[@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.

[@onuragmaji]

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

[@UnfoldDataScience]

Thanks Anurag.

[@learningsinlife]

mean will also change if 48 is made new observation

[@bipintiwari8751]

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

[@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

[@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).

[@lakshaykhandelwal4284]

very well explained.. 👍

[@UnfoldDataScience]

Thanks Lakshay.

[@tusharbedse9523]

Nicely explained again Aman!

[@UnfoldDataScience]

Glad you liked it Tushar.

[@suhatharsanyoganathapillai2203]

Thank you

[@UnfoldDataScience]

Welcome.

[@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.

[@salmanjaved2816]

Thanks bro 👍

[@UnfoldDataScience]

Welcome Salman.

[@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

[@dr.sagarfirke2687]

Eexcelent

[@UnfoldDataScience]

Thanks Sagar.

[@UnfoldDataScience]

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

[@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.

[@m12gaming81]

sir ur doing great work luv u

[@UnfoldDataScience]

So nice of you

[@priyamkataria573]

Great content 🔥🔥

[@UnfoldDataScience]

Appreciate it Priyam

[@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.??

[@rohitbhosale4614]

You are a champ!

[@UnfoldDataScience]

Thanks Rohit.

[@gangavijayan8906]

Why covariance is divided by standard deviation?

[@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

[@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.

[@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.

[@chikoo8486]

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

[@UnfoldDataScience]

ya.

[@mosama22]

Thank you Amen :-) :-)

[@UnfoldDataScience]

Welcome

[@usmanzahid3711]

What exactly co variance is

[@D.H.Bangalore]

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

[@humanafees8059]

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

[@UnfoldDataScience]

Thanks for suggesting, noted.

[@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

[@shoooooooooorts8002]

Please make video on statistics for data science A-Z

[@UnfoldDataScience]

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[@arihantchoudhary]

❤❤❤

[@Manya2017]

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

[@UnfoldDataScience]

unfold_data_science on instagram

[@ashokmeena9631]

Sir what about virtual Interview

[@UnfoldDataScience]

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

[@anilkumarsharma8901]

More computer power means more success

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Super computer ki power windows interface main karwa do phir Duniya following karegi Vedic math par reserch karwavo

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kids learn from udemy legends learn from unfold data science

[@UnfoldDataScience]

Thanks Sanyam. your words are always motivating. :)

[@khanraiyan123]

denominator should be N-1

[@UnfoldDataScience]

Comment pinned for this

[@vaibhavpandey7398]

I want to ask, ye t shirt sale pe ayi thi.. Wahi se li thi na 🤣🤣🤣🤣 joking. Liked ur video

[@UnfoldDataScience]

Gift mila tha , dene wale se puchna padega :D

[@inderjeetsingh1685]

Ok?

[@UnfoldDataScience]

??

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Merey research karwavo jo duniya following karney lagegi to next government aapki hee ban jayega Super computer access free main karwa do