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

[@UnfoldDataScience]

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[@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.

[@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.

[@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.

[@bipulray2294]

Greatest teachers actually teach on humble white boards ❤️❤️❤️❤️thank you sir for this awesome explanation

[@kaciahanson5169]

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

[@UnfoldDataScience]

Thanks a lot.

[@divyamsaxena3198]

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

[@UnfoldDataScience]

Wow, thank you!

[@RachelLi-l6o]

Dude you are awesome. I will have my first data science technical interview tmr since I did my career transition from finance. I hope everything will go on well

[@rooppsychology6958]

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

[@UnfoldDataScience]

Thank you

[@mr.trinadhnookathotiassist6071]

Very simple and effective Aman

[@ramu7762]

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

[@UnfoldDataScience]

Welcome Ramu.

[@salehmuhammad6811]

Brilliant explaining techniques bro. God blessed you.

[@kingp4033]

This was so helpful! Thank you so much!

[@ashitnayak1912]

Awesome explanation. Got what I came for. ❤

[@johnvarvatoss142]

BEST EXPLANATION EVER .. THANK YOU MAN

[@UnfoldDataScience]

My pleasure, please share with friends as well.

[@harshitabisht1789]

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

[@vikrantmahajan142]

one of the best videos covering these topics.

[@nikhilpawar7876]

Best statistics video on KZbin 🔥

[@UnfoldDataScience]

Appreciate that comment Nikhil

[@Birdsneverfly]

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

[@UnfoldDataScience]

Thanks for your kind words 😊

[@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

[@manikantareddy1830]

Best one among all I watched. Cleared all my doubts. Such a great one, simplified to the core. One small doubt: My data is nominal Vs Nominal 2 sample But more than 2 categories in outcome: Example: Type of placenta Vs Baby weight (took it as nominal) Variable: Type of Placenta ( Normal / abnormal) Outcome variable Birth weight ( Low / Normal / high) I want to see the association of Type of placenta with category of birth weight Which test I can do for it Thank you sir

[@UnfoldDataScience]

Chi square

[@dayan5402]

Thanks!

[@UnfoldDataScience]

I appreciate it . Thanks for motivating me

[@shawgaa1457]

Best explanation I have found, thank you so much

[@carolMuRugi-65]

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

[@UnfoldDataScience]

Thanks Carol.

[@TonyChipedza]

Wonderful and simplified explanation, i needed this..

[@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

[@destinyplummer3176]

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

[@yaksh82]

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

[@kaiotoo7640]

very good and simple explanations. Thanks a lot

[@UnfoldDataScience]

Thank you

[@y.suresh449]

Very simply and nicely explained.

[@shubhammittal2367]

Amazing , now gets clear

[@ramkiran3685]

You are explaining so nicely which many people are not doing. Keep it up

[@UnfoldDataScience]

Thanks Ram. Hope you are doing well

[@kamran_desu]

Very clear explanations. Just to point out that correlation also has p-value for null hypothesis that there is no correlation. I think its through the F-test (not 100% sure). Correlation coefficient gives us the strength and direction while its p-value gives the confidence in the correlation claim. E,g, the correlation between two data points will be 1, since its a perfect fit, however, p-value will be high since there's no confidence given low sample size. Actually that raises another question linked to this video. When do we use F-test? Anova?

[@UnfoldDataScience]

Yes absolutely right abt correlation. F-test is more of generic high level test whereas anova is specific type of procedure that produces f statistics.

[@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.

[@36revanth]

superb man , very easily understood. appreciate it

[@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.

[@sandipaghosh8850]

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

[@UnfoldDataScience]

Thanks Sandipa.

[@purnahangsubba9400]

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

[@UnfoldDataScience]

Thanks a lot.

[@drrajkishorsharma]

A VERY NICE VIDEO WITH SUCH AN EASY EXPLANAION

[@UnfoldDataScience]

Thanks Raj.

[@ezequieldeleon93]

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

[@UnfoldDataScience]

Glad you found it helpful 😊

[@tnmyk_]

Amazing explanation! Well done!

[@UnfoldDataScience]

Glad you liked it Tanmay

[@Kumarsashi-qy8xh]

Thanks for giving all such good informations

[@UnfoldDataScience]

Welcome.

[@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.

[@AkshayRakate]

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

[@UnfoldDataScience]

Glad you liked it Akshay.

[@haillatesfaye3579]

Thanks so much. I need more from you ....... on ordinal, multinominal and poison logistic regression...

[@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

[@shashireddy7371]

Great explanation Thanks Aman

[@grievingflowers]

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

[@Natarajan7565]

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

[@annukaushik6803]

Thik is awesome outstanding

[@UnfoldDataScience]

Thanks Annu.

[@ankur8688]

To the point. Hats off.

[@UnfoldDataScience]

Thanks Ankur.

[@temiyeoluseun297]

Thank you so much. best video on subject

[@UnfoldDataScience]

Thanks Temiye.

[@debipaikaray9084]

Great Video . Thanks

[@MaserekaEric-cv8dt]

Very wonderful discussion. Thank you so much.

[@trysonchisenga9406]

I have been enlightened, thank you

[@unexpected2004]

This is great! So clear and precise !

[@UnfoldDataScience]

Thanks a lot :)

[@ritachaudhary5780]

Right

[@nasrullahturke4480]

Great overview brother ❤️ Really great 👍

[@UnfoldDataScience]

Thanks a ton

[@samirafursule8590]

This is super informative 👏

[@UnfoldDataScience]

Thanks Samira.

[@rashijain7085]

You are a good teacher

[@Shanjida_tasnim02]

Best tutorial sirji

[@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

[@fiilixwonder7675]

You are a blessing 🙌

[@mousamibinckota]

Very well explained

[@UnfoldDataScience]

Thanks Mousami.

[@nishantbisen2080]

nicely explain ,thanks a lot sir

[@UnfoldDataScience]

Welcome Nishant.

[@shurovi123]

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

[@sureshbabuneerati6733]

excellent explanation sir

[@UnfoldDataScience]

Thanks a lot.

[@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 😇

[@muhammedmk5650]

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

[@UnfoldDataScience]

Welcome.

[@adityabenere6004]

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

[@UnfoldDataScience]

Thanks Aditya.

[@KaranRajput-nb7fo]

badhiya bhai

[@UnfoldDataScience]

Thanks Karan.

[@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.

[@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 😊

[@susmitsekhar5100]

Very nice explanation...I hope you will upload the next video very soon..

[@UnfoldDataScience]

Welcome Susmit. Sure. Happy Learning.

[@geetadandin4302]

Explained very well Sir

[@monikagadre6440]

Excellent explanation in simple words

[@UnfoldDataScience]

Thanks Monika.

[@spicytuna08]

awesome clarity!!!

[@UnfoldDataScience]

Glad it was helpful! pls share with friends.

[@RohitRaj-ou7br]

Sir, your way of clearing concept is another level 🙏

[@UnfoldDataScience]

Thanks Rohit, plz share with others as well

[@k.venugopalasstprofessor4880]

GOD BLESS YOU..I think I elder to you sir.... excellent.... explanation.... great..you resembles saint RAMANIJACHARYA... who told all secrets to the world inspite of restrictions from the almighty..

[@UnfoldDataScience]

So nice of you. Thanks a lot.

[@mdtayyab121]

Thank you so much, you really unfolded it

[@UnfoldDataScience]

Glad you found it helpful 😊

[@archanabottu665]

Thank you! This is very helpful.

[@UnfoldDataScience]

Welcome Archana

[@omsairam2828]

Very good

[@UnfoldDataScience]

Thanks Ambily.

[@akshitajain3174]

Nice explanation

[@UnfoldDataScience]

Thanks Akshita.

[@atharv_preeti]

Thanks aman.

[@UnfoldDataScience]

Welcome Shiv.

[@thisumamarasinghe8171]

Sampling is taking a subset of individuals,objects or observations selected from a population to estimate characteristics and make inferences for the entire poplulation

[@subhashachutha7413]

Wow nice video

[@UnfoldDataScience]

Thanks Subhash, happy learning. Tc

[@lokesh4391]

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

[@UnfoldDataScience]

So nice of you Lokesh.

[@mithunyadav3153]

`super explanation bro

[@UnfoldDataScience]

Thanks for watching Mithun.

[@mithunyadav3153]

Thank you for making great videos ...my support is always for you !

[@thisumamarasinghe8171]

comprehensive...Thanks

[@swayansidhamishra3257]

Sampling is a technique of selecting subset of population to meke statistical inferences from them and to estimate characteristics of the total population

[@Dr.Sumesh]

Nice explanation...

[@UnfoldDataScience]

Thanks Sumesh.

[@ivancarrillo1889]

Well explained. Thanks.

[@UnfoldDataScience]

Welcome Ivan :)

[@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.

[@santoshkumargouda6270]

please make videos on A/B testing.

[@getahunsolomonofficial]

Sweet tutorial!

[@omarali6212]

Thank you for your nice clarification about this

[@jintoej2149]

Thank you for your explanation

[@abuarham6246]

Thank u.i really need this video

[@UnfoldDataScience]

You're welcome Abu

[@mecareless179]

Welll explained sir

[@somanathking4694]

sampling meaning taking some data points and considering the taken points as the new dataset basically sampling is drawing the data points from the population data set.