Anova T test Chi square When to use what|Understanding details about the hypothesis testing

Anova T test Chi square When to use what|Understanding details about the hypothesis testing
#Anova #TTest #ChiSquare #UnfoldDataScience
Hello,
My name is Aman and I am a data scientist.
About this video:
In this video, I explain about Anova, T-test, Chi square, correlation and the scenarios on when to use what. I explain with a simple data about different features of data including categorical and continuous variables. I explain about all these techniques like Anova, T-test, Chi-square, correlation in detail.
Below questions are answered in this video:
1. When to use Anova and chi-square test
2. When to use T-test for hypothesis testing
3. Categorical variable correlation
4. How to do hypothesis test using Anova
5. Chi-square correlation
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
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[@UnfoldDataScience]

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[@YashpalNSharma]

Sample is an example set of a data population.
This video should have more views! I have read multiple blogs and sources but couldn’t understand things as easy as explained here.
Thank you again Aman! 🙏🏻

[@UnfoldDataScience]

Glad it was helpful Yashpal.

[@destinyplummer3176]

All the years in my undergrad...it finally makes sense, thank you!

[@iktejsinghjabbal4145]

I have'nt come across any video with a simpler explanation of these basic statistical analyses. Kudos to the tutor for making it so simple to understand!

[@UnfoldDataScience]

Glad it was helpful Iktej.

[@salonisingh6032]

I am speechless. i am doing Phd . and currently doing course work of phd. our faculty did not taught this.i was restless for months, saw numbes of videos on youtube but nothing solved my problem. one simple video of 9 min solved my every doubt and now i am confident that i can do this. thank you so much sir.

[@harshitabisht1789]

Most simplest explanation of these topics I have ever studied. Thnx so much

[@kaciahanson5169]

You just saved my life with this assignment! Thank you!

[@UnfoldDataScience]

Thanks a lot.

[@vikrantmahajan142]

one of the best videos covering these topics.

[@shahzebshah7368]

Thank You Very Much, Sir.
It Takes A Lot Of Time And Brainstorming To Summarize These Concepts In Videos Like This. I Have Been Looking For This Video Since Very Long. This Video Removes All Of My Doubts.

[@MaserekaEric-cv8dt]

Very wonderful discussion. Thank you so much.

[@user-el5br3ff7n]

very well explained even a layman can understand why these test is used for. Thanks a Lot brother.

[@kingp4033]

This was so helpful! Thank you so much!

[@shawgaa1457]

Best explanation I have found, thank you so much

[@bhavikdudhrejiya852]

Very nice video.
Learning points of the video:
1. Test on : One continues features , Hypothesis on : mean , Comes under : One Sample Test , Name of Test : One Sample T-Test , Accept & Rejection hypothesis criteria on what scale comparison : p value
2. Test on : One categorical features - Two subclass , Hypothesis on : proportion between two class , Comes under : One Sample Test , Name of Test : One Sample Proportion Test , Accept & Rejection hypothesis criteria on what scale comparison : p value
3. Test on : Two continues features , Hypothesis on : correlation , Comes under : Two Sample Test , Name of Test : Correlation with T-Test , Accept & Rejection hypothesis criteria on what scale comparisons : correlation & p value
4. Test on : Two categorical features , Hypothesis on : proportion between two class based on other class , Comes under : Two Sample Test , Name of Test : Chi-Square Test , Accept & Rejection hypothesis criteria on what scale comparison : p value
5. Test on : One categorical feature - Two subclass & One continues feature , Hypothesis on : Difference of mean between two class(variance) , Comes under : Two Sample Test , Name of Test : Two Sample T-Test , Accept & Rejection hypothesis criteria on what scale comparison : p value
6. Test on : One categorical feature - More than two subclass & One continues feature , Hypothesis on : Difference of mean between more than two class(variance) , Comes under : Two Sample Test , Name of Test : ANOVA , Accept & Rejection hypothesis criteria on what scale comparison : p value

[@UnfoldDataScience]

Amazing. Thanks a lot for making me believe that it was understood. Keep learning.

[@shurovi123]

Very well explained and to the point. Thank you so much.

[@shubhammittal2367]

Amazing , now gets clear

[@sitharaayesha792]

Thank you very much for this clear and crisp explanation. It has been extremely helpful to understand the concept :)

[@UnfoldDataScience]

Glad it was helpful Sithara. Thanks for watching.

[@TonyChipedza]

Wonderful and simplified explanation, i needed this..

[@divyamsaxena3198]

Beautiful... Only one word... Can't thank you enough brother... I thank god that I found you...

[@UnfoldDataScience]

Wow, thank you!

[@36revanth]

superb man , very easily understood. appreciate it

[@Natarajan7565]

Sample/samples are a part of researching masses which is an ideal representation of the masses

[@ashitnayak1912]

Awesome explanation. Got what I came for. ❤

[@santhoshgattoji7517]

Perfect summary of the tests! Thanks again Aman. Now sampling : " this is the process of taking a sample of data from the actual population" and answer to your Q) "if we have numbers 1 to 100 can 1 to 10 a sample? A) generally NO because a sample should consist a min of 30 data points.

[@UnfoldDataScience]

Thanks Santhosh. my follow up question - If I tell you to take 30 sample from above data, can u take number 1 to 30? :)

[@santhoshgattoji7517]

@@UnfoldDataScience no aman, these 30 should be randomly selected from the population.

[@omarali6212]

Thank you for your nice clarification about this

[@nup2943]

You simplified everything about all tests...Thank you so much🙂

[@UnfoldDataScience]

Welcome

[@janelynpheyloyola8988]

Thank you so much. Very well explained. This was very helpful 😊

[@a.a7493]

Man you just explained it sooooooo well wow… best explanation on utube i spent so many time looking and wasting time not getting it but you just killed it ❤

[@UnfoldDataScience]

Thank you 😇

[@kasetyannurhanif8393]

studying for media data science subject from korea university here :') thank you so much for your video!!

[@shashireddy7371]

Great explanation
Thanks Aman

[@Akshayrenake-qg4vs]

Amazing!

[@jintoej2149]

Thank you for your explanation

[@bhanusreevangari509]

Excellent explanation

[@carolhephzibahkimani8938]

Wow! What a great explanation. I Understood everything. Thank you.

[@UnfoldDataScience]

Thanks Carol.

[@AkshayRakate]

crisp and clear explanation !!!!!!!!!

[@UnfoldDataScience]

Glad you liked it Akshay.

[@Shanjida_tasnim02]

Best tutorial sirji

[@thisumamarasinghe8171]

comprehensive...Thanks

[@nikhilpawar7876]

Best statistics video on UA-cam 🔥

[@UnfoldDataScience]

Appreciate that comment Nikhil

[@johnvarvatoss142]

BEST EXPLANATION EVER .. THANK YOU MAN

[@UnfoldDataScience]

My pleasure, please share with friends as well.

[@ramu7762]

I have seen many videos but your explanation is simple and easy to understand. Thank you very much.

[@UnfoldDataScience]

Welcome Ramu.

[@temiyeoluseun297]

Thank you so much. best video on subject

[@UnfoldDataScience]

Thanks Temiye.

[@rotatitatat6574]

Thank you very mush sir

[@geetadandin4302]

Explained very well Sir

[@vineetkaur1667]

Thanks for the simplified explanation, keep making more such content

[@UnfoldDataScience]

Thank you Vineet, I will

[@muthuvijayannn]

Well explained sir

[@ezequieldeleon93]

This is a world class video. Thank you so much.

[@UnfoldDataScience]

Glad you found it helpful 😊

[@unexpected2004]

This is great! So clear and precise !

[@UnfoldDataScience]

Thanks a lot :)

[@ritachaudhary5780]

Right

[@hadikhalil1939]

thanl you alot my friend

[@fiilixwonder7675]

You are a blessing 🙌

[@mecareless179]

Welll explained sir

[@VivekPal-dj2jo]

Wonderful

[@aravindsreerama7023]

thanku very much for the guidence provided

[@UnfoldDataScience]

Welcome Aravind.

[@Birdsneverfly]

Very very good video. Excellent explanation. As a Data Scientist, I can only admire this explanation.

[@UnfoldDataScience]

Thanks for your kind words 😊

[@getahunsolomonofficial]

Sweet tutorial!

[@sandipaghosh8850]

Awesome explanation...Thank you a lot for all these videos...

[@UnfoldDataScience]

Thanks Sandipa.

[@Anamika-nb3tv]

Great

[@lokesh4391]

Thank you so much Aman . You videos are very clear and able to understand very easily.

[@UnfoldDataScience]

So nice of you Lokesh.

[@Islamicquranquotes786]

I m really impressed...I will be waiting for more of ur videos.... awesome explaination ❤️❤️

[@UnfoldDataScience]

Thank you so much 😀

[@mdtayyab121]

Thank you so much, you really unfolded it

[@UnfoldDataScience]

Glad you found it helpful 😊

[@kaiotoo7640]

very good and simple explanations. Thanks a lot

[@UnfoldDataScience]

Thank you

[@rashijain7085]

You are a good teacher

[@KaranRajput-nb7fo]

badhiya bhai

[@UnfoldDataScience]

Thanks Karan.

[@rupamishraspsychology6958]

Excellent lecture sir. Helpful for Ph.d scholars. Very helpful. Easy to understand

[@UnfoldDataScience]

Thank you

[@sheelarajendran2946]

Thank you so much sir...

[@spicytuna08]

awesome clarity!!!

[@UnfoldDataScience]

Glad it was helpful! pls share with friends.

[@abuarham6246]

Thank u.i really need this video

[@UnfoldDataScience]

You're welcome Abu

[@adityabenere6004]

Thanks sir amazing .. simple and to the point explanation 🔥🔥

[@UnfoldDataScience]

Thanks Aditya.

[@comedyworld4730]

This is first time I got to know which test is applicable in which situation.
Thank you so much sir.
Please make more videos on statistics
Like PCA

[@UnfoldDataScience]

Keep watching

[@omsairam2828]

Very good

[@UnfoldDataScience]

Thanks Ambily.

[@annukaushik6803]

Thik is awesome outstanding

[@UnfoldDataScience]

Thanks Annu.

[@purnahangsubba9400]

Very precise and clear explanation, thank you sir, would love to watch more videos on subject....Beautiful presentation

[@UnfoldDataScience]

Thanks a lot.

[@princeowususekyere2889]

Brilliant

[@ravichaudhary4892]

Thank you so much bhai..... Specially for explaining so clearly that what is the difference between one sample and two sample..

[@UnfoldDataScience]

Welcome Ravi.

[@naushinomeed5965]

perfect !

[@sandipansarkar9211]

finished watching

[@RohitRaj-ou7br]

Sir, your way of clearing concept is another level 🙏

[@UnfoldDataScience]

Thanks Rohit, plz share with others as well

[@monikagadre6440]

Excellent explanation in simple words

[@UnfoldDataScience]

Thanks Monika.

[@BintSkander]

So helpful, thank you!

[@UnfoldDataScience]

Thank you.

[@archanabottu665]

Thank you! This is very helpful.

[@UnfoldDataScience]

Welcome Archana

[@akshitajain3174]

Nice explanation

[@UnfoldDataScience]

Thanks Akshita.

[@genogeno5220]

Thank you for this simple explanation. Clears all my questions now. I have subscribed and will follow up with your videos. You rock 💪👏

[@UnfoldDataScience]

Glad to be helpful. Thanks for your positive feedback 😊.

[@mousamibinckota]

Very well explained

[@UnfoldDataScience]

Thanks Mousami.

[@Kumarsashi-qy8xh]

Thanks for giving all such good informations

[@UnfoldDataScience]

Welcome.

[@souravbiswas6892]

Excellent explanation, keep up good work 👍

[@UnfoldDataScience]

Thanks Sourav. Happy Learning. Have a nice weekend:)

[@ankur8688]

To the point. Hats off.

[@UnfoldDataScience]

Thanks Ankur.

[@ivancarrillo1889]

Well explained. Thanks.

[@UnfoldDataScience]

Welcome Ivan :)

[@abdifatahfarahhamud6426]

Thank you sir, you make it too easy to understand thank you

[@UnfoldDataScience]

You are welcome.

[@sureshbabuneerati6733]

excellent explanation sir

[@UnfoldDataScience]

Thanks a lot.

[@Shrutiijaiswal]

Thank you so so so much sir!
Amazing to see your method of teaching. Tomorrow is my exam and this is indeed helpful

[@UnfoldDataScience]

All the best Shruti. Hope exam was good.

[@SoumyaDasgupta]

The people who reacted dislikes came here for Gym videos for abs. Awesome explanation bhai.

[@UnfoldDataScience]

Thanks Soumya :)

[@arpanchakraborty2557]

Absolutely right 😂

[@adhikarieswar1372]

Nice explanation sir

[@atharv_preeti]

Thanks aman.

[@UnfoldDataScience]

Welcome Shiv.

[@soheilaahmadi4807]

Thank you so much for these amazing tutorials. I am working on the ANSUR dataset which contains anthropometric measurements. there are two sets of data one for males and one for females. For females, we have around 2000 samples and for males, 4000 samples. There are about 93 features that are the same for both genders. Features such as weight, height, waist circumference and etc. I want to concatenate these two datasets and do some clustering analysis on them means looking at them as just humans and ignoring the gender. I would like to know if I can do that or I need to do some analysis before that to find if there is a significant difference between each feature for different genders. Like comparing waist circumference for males dataset with waist circumference for females dataset. Which test should I apply? and what other things should I consider? Regards

[@UnfoldDataScience]

Both ways possible, either u combine data first then analyze or vice versa.
Coming to tests, many test can be performed depending on my variable type. For example hypothesis related to waist circumference can be done using anova

[@drrajkishorsharma]

A VERY NICE VIDEO WITH SUCH AN EASY EXPLANAION

[@UnfoldDataScience]

Thanks Raj.

[@salonisingh6032]

I am speechless. i am doing Phd . and currently doing course work of phd. our faculty did not taught this.i was restless for months, saw numbes of videos on youtube but nothing solved my problem. one simple video of 9 min solved my every doubt and now i am confident that i can do this. thank you so much sir.

[@UnfoldDataScience]

Thanks Saloni. I put your comment on my LinkedIn. Your comments are precious.

[@salonisingh6032]

@@UnfoldDataScience thank you sir

[@vishnubhandare9489]

Nice presentation

[@UnfoldDataScience]

Thanks Vishnu.

[@user-in7fc3hg8e]

subscribed bro, very clear explanation

[@UnfoldDataScience]

Thanks and welcome

[@muhammedmk5650]

Good explanation brother...thanks a lot ...

[@UnfoldDataScience]

Welcome.

[@samratshimpi5093]

Keep making such videos sir (y)

[@UnfoldDataScience]

Thank you samrat, I will.

[@tnmyk_]

Amazing explanation! Well done!

[@UnfoldDataScience]

Glad you liked it Tanmay

[@AbcdAbcd-ol5hn]

Super

[@shreyasb.s3819]

Nice explained

[@UnfoldDataScience]

Thanks for liking Shreyas :)

[@nishantbisen2080]

nicely explain ,thanks a lot sir

[@UnfoldDataScience]

Welcome Nishant.