Covariance vs Correlation with simple data | Covariance vs Correlation Coefficient
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- เผยแพร่เมื่อ 21 ก.ค. 2024
- 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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In the formula of cov(x,y) the denominator is N-1 . Can you please correct this sir!
I will pin this on top of the video.
actually if you are applying this formula on sample then its N-1 otherwise if you are applying on population then its N.
@@pkavenger9990 thanks
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 :)
Thanks Prasad for motivation.
Amazing video! Such simple explanation, you earned a loyal subscriber today :)
You are a Genius Sir. Thank You So Much for making these Concepts Simple and Lucid. May God Bless You 🙏🙏💐💐
You are amazing at what you do! Your passion and dedication is beyond words! Thankyou so much sir.
Thanks Gayatri for motivating me through your comment.
how calm u r while talking man ,excellent explaination! Hats off 🙇♂
IT'S REALLY AN EASY CLASS AND THE WAY OF YOUR PRESENTATION IS GREAT.
Loved it 😊! you made it very easy to understand thanks !
Amazing explanation brother..Good Job..👍👍👍
You are simply the best! The MasterBlaster in Data Science
Thanks alot Thurab. Continue watching
You are the best teacher! Got goosebumps while listening to your lecture. Thank you so much!
Thanks Kavya. Pls share with friends as well. Keep learning
Thank you so much! it was hard for me to understand this concept until I found this video. Please keep doing more videos!
Thank you Yohari! Will do!
Thank you! Great teacher!
Awesome video sir...Keep shining😀
Was amazing. Happy to find your tutorials on TH-cam.
Thanks Soheila.
Amazing explanation Aman bhai ... Made it sound so simple. Thanks this helps.
Thanks Jishnu da.
Just watched it before exam and in one go ,i understood the concept ❤keep making such videos sir 🥰🥰
Thank you sir for clean explanation.
Very well explained, thanks
Beautifully explained!!...Thanks for such content
Thanks Sameer.
Thank you Aman❤
Thanks for the wonderful explanation. You made my understanding very concrete.
Welcome Vidya.
V good, thanks
fantastic channel, def deserves more views
Thanks Haidi.
Helpd me a lot!
Amazing explanation sir.....
You made it so clear....thank you so much 🙏❤️
Welcome
Good work bro ur teaching style is very cool, keep posting such great content
Thanks Anurag.
Kaafi achhcha samjhaya bhai! Good work!
Thanks Rishabh, thoda share kar dijie apne groups me :)
Thanks a lot . A very detailed explanation . Great yaar🙏👍👌
Glad you liked it.
after so much of head banging finally I understood covariance & correlation....thank you so much...
Thanks a lot.
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?
Let me check once.
Changing the value of Y variable from 32 to 48 changes overall mean of Y and hence it cannot be subtracted from the previous.
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?
it is good keep it up
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?
Hi Sanjeev, I created a detailed video for this question, Watch it on my channel today 7pm IST. :)
@@UnfoldDataScience Thanks a lot!
with in a 1:30 sec.... i can say, you are the best teacher.
Thank you Jigyasa. Your comments mean a lot to me
Thank you sir. You're a great teacher.
Welcome.
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?
Thanks Aditya. Let me think through it. Thanks for asking.
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
Thanks for your words Huma.
When Yi value is changed from 32 to 48 mean of y will also change
Nicely explained again Aman!
Glad you liked it Tushar.
sir can you suggest a tabelau course for me ? i am confused where to learn from ?.
You are amazing buddy you explained it so simply
Thanks Vinay for your positive feedback. Please share with others as well who could be benefited from such content.
Much needed,thanks :)
Welcome :)
Thanks a lot for this topic.
Welcome again :)
sir ur doing great work luv u
So nice of you
it helped me a lot, thank you🙌
Glad it helped!
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
For population data N is taken and for sample data N-1
Glad it helped!
Thanks Rahul
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.
watch variance and sd video
Amazing Aman
THanks Karthick
finished watching
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?
Good question Sudheer. To keep it short, choose the variables which are highest corelated with your target variable(Either positive or negative).
nicely explained. thank you!
Glad it was helpful!
Best explanation
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very helpful...good job
Thanks a lot.
Thanks...this is very clear.
Glad it was helpful!
Great explanation
Glad it was helpful!
Excellent thanks!
You're welcome!
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.
May be you can use advance technique. Its a simple technique.
Great resource!
Thanks a lot.
Amazing sir thank you
Most welcome Soumya.
why exponential is calculated can you please explain that as well.
Thanks bro 👍
Welcome Salman.
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.
yes same doubt
wow... What a explanation
Thanks Kiran.
thanksss
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..
good question, u encode again and then predict.
Excellent video
Thanks Bala.
very well explained.. 👍
Thanks Lakshay.
Sir.. Divide by N Or (n-1) for finding convariance? In some lectures it is showing as by ( n-1)
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
@@UnfoldDataScience then, will it matter if it’s the case of small data set..?
What should we take then.??
Thank you
Welcome.
Thank you Amen :-) :-)
Welcome
amazing explination
Thanks Madhu.
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 ?
Good question, however covariance is base of correlation hence that concept came first.
how to find standard deviation of x and y..basically that denominator
We no need to compute from scratch, tool will help to do so
Perfect explanation
Thanks Matthew.
Great content 🔥🔥
Appreciate it Priyam
Perfect 👍👍👍👍
Thank you
Thank you so much... It helped a lot... But i want to know why it ranges between 1 and - 1 and not above that...
Welcome Shubham, its because of internal mathematical formula.
great explanation
Glad you liked it
The unit you are talking about in covariance is +ve and -ve ??
ya.
Why covariance is divided by standard deviation?
mean will also change if 48 is made new observation
You are a champ!
Thanks Rohit.
❤❤❤
Eexcelent
Thanks Sagar.
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.
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
Please make video on statistics for data science A-Z
th-cam.com/video/iZ2r7aIwMbc/w-d-xo.html
What exactly co variance is
When you changed 32 to 48, mean will also change.
Can you share the link of the data science group so that I can also join
unfold_data_science on instagram
One suggestion can u please make a video for detailed probability for beginners please it a request
Thanks for suggesting, noted.
Looks like while increasing the value of y you forgot to increase the mean of y
Sir what about virtual Interview
Fill the form in the previous video. I will. Share invite.
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Gift mila tha , dene wale se puchna padega :D
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Thanks Sanyam. your words are always motivating. :)
denominator should be N-1
Comment pinned for this