Statistics- What is Pearson Correlation Coefficient? Difference between Correlation and Covariance

In this video we are going to understand about Pearson Correlation Coefficient. We will also understand the difference between Covariance and Correlation.
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[@amishsharma7578]

You are in love with the word "particular" :)

[@danielleroberts8252]

THANK YOU! I am NOT a data or math person and have been trying to wrap my head around this statistics test and what it does for a communications methodology course. All I could find is how to do it, but not how to figure out if it was the right test for my data. Now I understand and can see if it works better than the Chi-Square for my data.

[@amitupadhyay6511]

thw glitter in his eyes and the slight smile when he completes explaining a concept shows his hardwork and dedication

[@beautyisinmind2163]

simply say:
Covariance: tells if two variables are positively or negatively correlated
Correlation: tells how strongly variables are correlated and in which direction

[@anandacharya9919]

Excellent Sir,, nobody can explain much simple than this way, Thank you so much

[@ibrargeorge5360]

U r a gr8 teacher I have searched so many statistics teachers but r u different ways to teach thank u .u hv cleard my confusion God bless u

[@NONAME_G_R_I_D_]

you are one of my favourite math teachers in all time I swear!

[@GreyWolf_369]

Dude, thanks for such crystal clear explanations, making the concepts easier to comprehend.

[@abumonyeigbo5040]

So happy to come across this video. I have been trying to understand what the Pearson correlation and covariance are and how to use them. Thank you for uploading this video.

[@lokeshkaturi4040]

Hi Sir, you give valuable details of stats and their application which gives an idea how to see the data and implement algorithms .Thanks a lot!

[@prakash8876]

Wow, thank you. its a clear explanation in short time. God bless you.

[@brudra0]

7:40 what u wrote initially was correct, X increases Y decreases.

[@saagerbabung5652]

yes, but both are actually same lol.

[@vatsalkachhiya5796]

@@saagerbabung5652 you are correct bro😂. It same as saying it's not water it's H₂O.

[@VVV-wx3ui]

This is one super good explanation of the relationship between Features. Its a beauty of you sessions, talking about Stats w.r.t to its play in ML Algorithms (feature engineering). You are guru to me in Data Sciences.

[@vishnuprabhakar7327]

are you working in the field of data science

[@martinjames4293]

Excellent video and explanation - Thanks for making and uploading it.

[@akshatchouhan5199]

You lectures are super exciting and the way you explain is amazing.

[@vijetabahuguna7688]

Thank u so much for explaining this typical topic in simplest way.... Now it's clear to me

[@mohammadmousavi1]

Your explanation are clear, to the point and short … great job 👏… You have a gift in teaching… please make more of these short videos about different topics

[@abhishank1062]

Feeling good to have mentor like you

[@aartibalhara9996]

Awesome explanation..i am using this test in my research work, for which i need to know everything about this test..uh explained well.

[@udayraj82]

Thanks for the Video, easily explained the concept and its use.

[@Mithilesh165]

Thanks sir, i am really enjoying the journey to Data Science ,You are awesome

[@vijaylivelife]

Awesome stuff Krish Naik.. You make these concepts so easy to understand. Thanks a lot brother.

[@mihirgaglani4167]

Dude your videos are very very understanding. Thank you a lot ! cheers mate

[@lifeisfun9]

Again an amazing explaination. Thank you Sir

[@manpreetkj3]

I wish you were my stats prof! Thank you for this simple explanation!

[@anirudhyadav-mq8nd]

Thanks for uploading...was looking in the playlist since morning.

[@anirudhyadav-mq8nd]

Could you please make a video on sql,how much knowledge should one possess abt sql for data analyst role. Pls help.

[@akshatsrivastava6840]

sir thank you alot because of you i am able to learn ML easily. Thank you sir .

[@dineshrawat8438]

Good explanation and finally well connected with how to select feature for dropping..

[@inddrayadav2719]

Concept clear simply.. thanks you Sir

[@Parcha24]

Thanks bro, I can see the passion and hardwork you put in 👌🏻

[@pritishpattnaik4674]

Great sir , absolutely amazing

[@mikelgiroud8798]

Great One. Would like to see you give more brief example or just statement on how and which theory used in a particular AI/Machine Learning/Tech field and why each theory/concept is important for each field i.e., why Pearson CC is important for ML and how it is used

[@asimssheikh]

Great simple explanation. Thank you.

[@lalithapriya9484]

really superb way of conveying concepts , Great job sir

[@micheleadriaans6688]

Thank! Great explaination!

[@logeshwarana.r4461]

Very useful and well explained sir because of ur videos I am interested to learn more stat thk u so much sir

[@newtonkamanga1930]

I failed to understand what my college professor was trying to deliver!!!..thank you it's so much clear now

[@dennisdennis7069]

Man I love your work, in particular and general👌

[@ravirajmahajankatti4691]

Thank u Krish. Great explanation.

[@sandipansarkar9211]

superb.But one thing is if the correlation between two independent variables is 1 rhen they can be treated as 1 variable and hence we can drop one og the .So this is the importance of Pearson correlation.This is the importance of Correlation in data science. Did not know that.Now its clear.Thanks Krish

[@AmitVishnukumarModhMCS]

superb explaination sir.

[@pranjalsingh1287]

Explained beautifully

[@user-bs7dh1ty8f]

Thanks , well explained

[@Sumeet_100]

thank you so much for this video !!!

[@pawanbhandarkar4199]

Great stuff. Succinct and clear!

[@mehediazad1780]

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[@ibrahimmondal9104]

Yahh !!
I got it.....this video is very helpful for me 👍👍👍👍👍👍

[@adityaretissin1856]

Explaination on point!

[@adityakayasth4401]

The way you explained this hell topic was sooooo amazing sir awesome video 👍👍👍👍

[@vroomvroom4308]

Awesome Elaboration

[@amritsudershan8620]

Really excited lecture boss...

[@shiwangful]

great explanation sir, it helped me a lot.

[@tharunagaram8803]

Great explanation.

[@thepresistence5935]

understood clearly thanks bro

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Sir your English speaking soft skill superb 👌👌👌👌

[@goitomfitsum6722]

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[@sushilkumarpadhy8154]

Krish bhai ... explained beautifully... great 👍

[@dipinanda1]

Brilliant. Thank you so much buddy

[@santhoshkumar-lm4hs]

1000likes..extra ordinary..very simple explanation

[@gowthamjeevanantham6144]

brilliant explanation krish

[@jetace5564]

Brilliant explanation mate

[@ganeshreddymangunuru5001]

Good stuff sir and explained in understandable manner 🤝

[@kaitlyndoodle]

Thank you!

[@traptigupta2628]

so much helpful 👍👍

[@jozuatjonatsoi3670]

Thank you very much

[@dilipgyawali1776]

thank u sir ...great explanation ......u were right at 07:32 too.

[@madhubonigala767]

We loved the way u are explaining..Thanks for sharing knowledge 👍..can you also do a playlist on calculus so that it would be helpful for new learners like me??

[@kranthikumarjorrigala]

Hi, your explanation about concept is nice. One suggestion from my side is explain how to implement those concept with python after the theory part. Please make video on tests used to find nonlinear relationship and how to find relationship between categorical dependent variable and multiple categorical and continuous independent variables. This would help many people I guess. Thanks for useful content.

[@rizwanrehman6833]

kranthi kumar yes it will be very useful

[@abhinavanand380]

Thank you soo much sir😊

[@unsatisfiedgamer4116]

sir happy new year
love ur teaching sir

[@hanman5195]

i see Superb strength in you as well along with Pearson correlation.
If you have time please prepare videos on (t test z test anova chi square) to evaluate ML models.
Thank you very much.

[@saifnazir9251]

Thank you

[@SurajKumar-iw1ly]

Nicely explained

[@Sujo6]

nice explanation.

[@MukeshThakur-qp5ft]

@krish Naik in second graph of correlation X increases and Y decreases.

[@kevin-bm1vf]

Very helpful

[@ilmctmp]

Great video. Thanks for posting such lucid material. +1 for your expressions
It will be great if you could also give a proof on why dividing by standard deviation gives the strength. I found it a little bit difficult to understand the logical reasoning. In the covariance video, you clearly explained for a +ve relation why does covariance increase and vice versa.

[@aditidump]

sir if youve found an ecplanation.. could you let me know?

[@viveknikam5981]

I watch ur every video.... when u prepared all this??? Great....

[@kpratik5551000]

@@therealaspirant1882 No, who told you?

[@mrunalsrivastava2015]

can we compute correlation between two rows of a single matrix??

[@viveknikam5981]

@@mrunalsrivastava2015 yes. do take transpose first

[@mrunalsrivastava2015]

@@viveknikam5981 yes same I did. Thanks

[@theishaskitchen5540]

Thank you sir

[@shreymodi1494]

nice one @Krish Naik

[@vijaykalva7842]

Awesome one sir.

[@GauravSingh-ku5xy]

Damn good explanation. Keep up the good work sir.

[@mosespeter9711]

Thanks

[@pinfo7325]

THANK YOU

[@sreeramsaravanan8132]

One kind request.Please post a video on which statistical tests are used in different cases

[@jayshreedonga2833]

thanks

[@pollabkumar5599]

Thnx 😊

[@indian-inshorts5786]

u are awesome sir keep doing this

[@glorysonhorace3265]

Awesome🔥🔥

[@ritesh01pawar54]

thanks sir

[@muhammadzubairbaloch3224]

please make some videos on reinforcement learning

[@shraddhashirke1992]

Awesome video...
Wht if correlation value of two independent variables is -1 then also can we exclude one variable?

[@Palletooriabbai]

I showed this video to 4th grade student 👩‍🎓 now he is teaching exactly same thing for me 😊

[@SantoshKumar-nc4xr]

Very very thanks sir . Today I have got lots of money from this video.

[@SwavimanKumar]

The Machine learning book you recommended in the description is having examples in it of the older version of tensorflow. Do you have any latest book recommendation on the same topic?

[@umagurung1399]

Thank u sir

[@ankitdeshmukh6881]

Very informative video. I just had a doubt regarding this. Is the correlation coefficient also described through the correlation heatmap built using seaborn?

[@semrana1986]

Good stuff. Generally, Persons Corr can only caputre linear correlations and tend to miss non-linear correlations

[@doctordilanka]

What can capture non-linear correlations?

[@asifhly]

Love it... I'm am physics man.

[@KalyanGk0]

Better than my teachers who done phd's