Bootstrapping Main Ideas!!!

[@statquest]

NOTE: A lot of people ask "What happens when the original collection of measurements is not representative of the underlying distribution?" It's important to remember that a confidence interval is not guaranteed to overlap the true, population mean. A 95% CI means that if we make a ton of CIs using the same method, 95% of them will overlap the true mean. This tells us that 5% of the time we'll be off. So yes, a sample that is totally bonkers is possible, but rare. Understanding this risk of making the wrong decision, and managing it, is what statistics is all about. Also, at 5:55 I say there are up to 8^8 combinations of observed values and possible means, but this assumes that order matters, and it doesn't. So 8^8 over counts the total number of useful combinations and the true number is 15 choose 8, which is 6435 (for details on this math, see: en.wikipedia.org/wiki/Multiset#Counting_multisets ) Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/

[@natasgestel6873]

We take for granted all that went behind that idea of 95% CI that you stated - it was Jerzy Neyman's who came up with that definition. Have you read "The Lady Tasting Tea"? A bit of a history of some incredible mathematicians, including Ronald Fisher and Jerzy Neyman. The 95% comes up on page 123. Thanks for all your valuable statistics videos!

[@statquest]

@@natasgestel6873 Yes, I've read the book. Those dues were pretty smart.

[@PastryDonut]

Thank you for explaining that order doesn't matter. I was looking for the clarification on this everywhere.

[@alexandersmith6140]

So, if we take our sample of 8 observations, and we calculate a 95% confidence interval around the sample mean by bootstrapping, and then a genie appears and tells us that the true population mean lies outside of that confidence interval, that's the same as saying that our original 8-observation sample's mean actually wouldn't appear 95% of the time if we repeated the experiment infinitely many times, each experiment being an 8-observation sampling of the population?

[@statquest]

@@alexandersmith6140 The definition is of a 95% CI is that if we repeated the process of creating the 95% CI a ton of times, 95% of the CIs created that way would overlap the true mean. Thus, if collected 8 measurements and used Bootstrapping to calculate a 95%, then that if we repeated that process of creating the 95% CI a ton of times (collected 8 measurements, then calculated the CI with bootstrapping), then 95% of those CIs will overlap the true mean. In other words, it doesn't matter if we use bootstrapping, or some formula to calculate the CI, in both cases we have to collect 8 measurements a ton of times.

[@yannivdp1600]

I have done a master's in stats and a course in data analysis, and the only reason I've passed these things is that after a long and confusing lecture I can just come and watch you explain it in simple terms. Bam! Thank you so much!!

[@statquest]

Thanks! I'm glad my videos are helpful! :)

[@BheezHandle]

I am presently in your shoes, taking a Data Science Course but thanks to @statquest. giving him Double Bam!!

[@PunmasterSTP]

That's cool! How are your studies/career going?

[@NeuralNine]

There is nobody on KZbin that explains statistics better or in a more entertaining way than you! Keep it up!

[@statquest]

Wow, thanks!

[@NTesla00]

Passed all my stats courses already (thanks to your videos for a major part), but I'm still watching these as they come out, lol. Keep it up Josh, this channel is so good.

[@statquest]

Thank you very much! :)

[@haloforgeguy453]

Still floored that this works as a method

[@statquest]

I know - it's so easy, yet so effective.

[@patrickjdarrow]

​@@statquest is it really so effective? We really can only be as confident -- that bootstrapping produces characteristic data -- as we are that the sample is representative of the distribution -- right? Unconfident extrapolation seems like a good way to pollute datasets.

[@statquest]

@@patrickjdarrow Just like any statistical method, you have to have a reasonable sample size. n = 8 as a minimum is a good starting point.

[@gamuchiraindawana2827]

What I love about you is that you explain the big picture first. You help me understand why we should care in the first place, or the motivation behind the concept. Then you dive into the details afterwards, you make the information more accessible without compromising the technical integrity of the information. A very rare skill indeed, I'm reading Introduction To Statistical Learning in R ( ISLR ) and some chapters aren't intuitive, whenever I read a chapter that doesn't make sense I just watch your videos. That's how I know you're not compromising the technical integrity of the information, because what you say doesn't contradict what I read in academic papers, it's just easier to understand than what I read in academic papers. You are one of a kind!

[@statquest]

Thank you very much!

[@gamuchiraindawana2827]

@@statquest No, thank YOU Josh!

[@CaptainFeatherSwordz]

I think you summed up the value of these videos really well. Starting with the big picture and then zooming into the details is so much more beneficial for learning and I think this is one of the things Josh nails!

[@gamuchiraindawana2827]

@@CaptainFeatherSwordzIt's worlds apart from what the education system has conditioned us to right?

[@monoarul_islam_3]

You're probably the best guy for this job. Even though I don't know where I'm gonna apply all these. I just keep going through all of your videos. After finishing up this playlist I'll watch the ML playlist. Keep amazing us. Thank you JOSH

[@statquest]

Thanks!

[@Esmeralda_Art]

My man sounds sounds excited and bored at the same time and Im here for it 😂 Great explanation, something my Prof couldn’t manage. Elite university my ass lol

[@statquest]

bam!

[@Hemzees]

I can never get over how your videos make me love statistics when all my professors and recommended texts made me run away from it. Super grateful!! Also, I think I asked when this video was coming about a year ago.

[@statquest]

Glad it finally came out! :) Sorry it takes me so long to make videos.

[@KillerFridge]

I love SQ, because I finally "get" bootstrapping, despite having used it for years!

[@statquest]

BAM! :)

[@KillerFridge]

@@Synthanicmusic I do as a data scientist. Honestly, If you know that you don't know what you're doing then you are going to be better positioned than most; it means you will be questioning why you are applying certain tests/methods, rather than just doing so blindly. Especially in the workforce you will see a lot of badly reasoned statistics!

[@nautical1078]

Thanks for the videos, embarrassingly I'm relearning a lot of these concepts even though I graduated with a Statistics major. It's coming a lot easier now.

[@statquest]

Glad to help!

[@vladimirbriceno6051]

Don't be embarrassed, it's not your fault, but the education system's

[@nancygonzalez3193]

Happens a lot more often than you think. I graduated with a physics major not long ago and I can say I still cannot consider myself a physicist. I constantly keep finding myself learning things from awesome channels like Josh's that I'm supposed to know by now.

[@ankiwikman1218]

I've always grasped well enough to get a good grade but not well enough to embed, so I have to go back a lot.

[@aishah8398]

I wonder n feel so much regard for the institution and teachers, who taught you... no doubt, you are doing an incredible job...stay blessed always

[@statquest]

Thank you! :)

[@bubblebath2892]

I am justt speechless at - how can you mae something so complicated so simple , hats off to you and thanks a ton

[@statquest]

Thank you!

[@잠자기장인-x3r]

You sir are an absolute legend. Really helping me getting through my course, because my professor explains the same concept in a method that is 100 times harder to understand

[@statquest]

Happy to help!

[@vtphan2012]

Another great video. This video explains how to do bootstrap, which is the easy part. The more difficult part is to understand why bootstrap works. The conceptual challenge is that bootstrapping assumes that if we were to repeat an experiment, it would produce one of the outcomes we had observed. This could be a huge assumption, depending on the applications. Boot strapping does not add any new information to what has been observed.

[@statquest]

Noted

[@sgpleasure]

"The reason why this works is because the histogram of the sample tends to look very similar to the histogram of the population. That's really the key idea behind the bootstrap, and we will see how this idea can be used in all kinds of complicated situations. " Taking an online course on bootstrap regression and came here to try to understand why bootstrap works when it does not generate any new information.

[@vtphan2012]

@@sgpleasure When you sample from a population, it’s unsurprising that the distribution of the sample resembles the distribution of the population. So, you’re not really obtaining any new information. In essence, we’re only pretending it’s new information, when in fact, it’s just reconfirming existing information.

[@rhexieleelafuente4271]

What a comprehensive and fun discussion! I really had trouble understanding the concept of bootstrapping by myself but your lecture helped me a great deal :> Kudos!

[@statquest]

Glad it was helpful!

[@aneishajay7949]

I read a section on bootstrapping countless times and only understood it finally after watching your video! All I have to say to that is: BAM! (and thanks a bunch)

[@statquest]

Hooray!!! :)

[@meanyapickles]

All semester long I have been floundering through my statistics class, no thanks to my professors' boring and quite difficult-to-follow lectures on the materials. I've felt so dumb all semester, so when the next section called for "bootstrapping" I finally decided to throw her lecture videos aside and see if someone could explain the concepts better on KZbin. Boy am I glad I stumbled upon this. The visuals are straight to the point and the way you talk through everything very slowly and clearly is SOOO helpful. The enthusiasm and goofiness helps me keep my attention, which is a pain for me with ADHD. I could rewatch my prof's videos 5 times and retain nothing. Makes me wanna just burst into tears from frustration. But I felt like I could actually keep up with this video and _understand_ it! TL;DR thank you for making this, it was a HUGE improvement over my professor's teaching style and I will DEFINITELY be consulting you for future topics. You're a peach

[@statquest]

Hooray! Thank you very much. Just for reference, here's a list of all of my videos: statquest.org/video-index/

[@meanyapickles]

@@statquest thank you very much

[@yuvrajkhanna2819]

Watched the Stanford's and other lectures on similar topics, but you made it really simple and easier to understand. You teach good!! BIG BOOM BAMM !! thanks man

[@statquest]

Thank you! :)

[@diegobuenovillafane869]

BEST explanation EVER of bootstrap. Thanks for your dedication!

[@statquest]

Glad it was helpful!

[@abhishekpawar921]

Thanks for uploading these videos. It takes a lot of time and efforts to make such quality content. Thank you, Sir.

[@statquest]

Glad you like them!

[@travelthetropics6190]

Wow! this is the first time I learned this. awesome!

[@statquest]

BAM! :)

[@quorrexnoway9127]

This kinda feels illegal xD Really nice explained!

[@statquest]

Thank you! :)

[@qi2li2n_prance]

You made this concept so much easier to understand than what I was supposed to be learning it from. Thank you so much!!

[@statquest]

Glad it was helpful!

[@witchaponkitthaworn5998]

I am learning machine learning and came to this term , this videos explain it very clear, thank you.

[@statquest]

Thanks!

[@ayenisedaghat4667]

You are a legend my friend! A legend. I am doing my masters in Data Science this fall and this is amazing

[@statquest]

You can do it!

[@hugoviotti9795]

Always glad to see a new statquest! BAM!

[@statquest]

BAM! :)

[@AliasNichtVerfügbarDrölf]

Not the information I was looking for but i couldn't stop myself from watching it to the end. It was quite entertaining :)

[@AliasNichtVerfügbarDrölf]

*BAM

[@statquest]

That's awesome! BAM! :)

[@alessandrobucci951]

One of the most useful video on this topic on youtube, thanks!

[@statquest]

Wow, thanks!

[@oscarrosalescorzo]

The work you do is awesome!! Love it.

[@statquest]

Thank you!

[@jasonvoreseeas6578]

I'm going to recommend this channel to a bunch of my machine Learning nerds. This guy deserves every hype possible!

[@statquest]

Thank you! :)

[@andreyele3464]

Josh, you're sent to us from heaven, thanks

[@statquest]

:)

[@tsuchiko_7155]

OMG, it was a truly easy-to-understand video! Both the animation, narration, and explanation!!!! I wanna give a billion likes!!!

[@statquest]

Wow, thanks!

[@everyhinghere1377]

this is better than college-level advanced course !!! thank you

[@statquest]

Wow, thanks!

[@ignasialemany7738]

The triple BAM was amazing, thank you!

[@statquest]

Thank you!

[@jaundersousa3530]

A professor at the university I studied at was apparently a key contributor to Bootstrapping. Excellent job at explaining it in such an easy-to-understand way!

[@aditya4974]

What's the University and Prof's name?

[@statquest]

bam!

[@AvatardSwag]

This is the most amazing video I've seen on bootstrapping, thank you! Quadruple Bam!

[@statquest]

Wow, thanks!

[@w157-p5x]

blud just dropped one of the best explanatory videos out there and thought we wouldnt notice☠☠☠

[@statquest]

bam! :)

[@keepcontinue]

Excellent explanation as always by StatQuest!!! Thx a lot!!!

[@statquest]

BAM! :)

[@adityarazpokhrel7626]

So smoothly explained. Thank you sir.

[@statquest]

Thank you!

[@hermesavurquijo9961]

Thanks a lot, your video helps me and hopefully it will help my paper too

[@statquest]

Thanks!

[@dutonic]

Wow this is so good. The intro made me laugh so hard, it wasn't even that funny I just didn't expect it.

[@statquest]

Thanks!

[@luko141]

Mr. Josh - u are amazing. World needs more ppl like u. Its like education on another level. Thank you

[@statquest]

Thanks! :)

[@yohanessatria2220]

bruh... this explanation is simply awesome!

[@statquest]

Glad you liked it

[@sevenindigo5945]

I can only say one thing: BAM!!! you are the best teacher BAM!!!

[@statquest]

Thank you!

[@davusieonus]

i loved your bams and the illustrations for the steps and your explanation helped a lot

[@statquest]

Thank you!

[@НосокНесуществующий]

The intro was gold 🔥

[@statquest]

bam!

[@punditgi]

Very clear explanation. Well done!

[@statquest]

Thank you! :)

[@Acampandoconfrikis]

Best intro ever Pixar would envy you

[@statquest]

bam!

[@НосокНесуществующий]

Wow, that was super easy to understand. Thank you very much

[@statquest]

double bam! :)

[@PunmasterSTP]

Bootstrapping? More like "Bro, it's awesome knowledge you're dropping!" 👍

[@statquest]

Bam! :)

[@PunmasterSTP]

@@statquest Boot! 🥾

[@alaminmustafa8902]

I love the terminology alert😂 quadruple bam !😂

[@statquest]

bam!

[@tomatocultivator9539]

Thank you for explaining... Eat tomato and stay healthy....

[@statquest]

bam! :)

[@namitaratnakar_6591]

Love the explanation ..... Thank uh soo much❣️

[@statquest]

Thanks!

[@williamss4277]

Thank you for the teaching 🎉

[@statquest]

Any time!

[@dashsingh30095]

Statquest is the netflix for data science concepts.

[@statquest]

bam!

[@studyselection2881]

Are there even comments that you do not comment on? Very good video, thank you!

[@statquest]

Sometimes there are, but it's rare.

[@bellahuang8522]

I'm studying at a top 10 research university in the States and every professor has a PhD from Harvard/Stanford, but none of them teach stats as well as StatQuest 🙃

[@statquest]

Thanks! :)

[@amirmusavi3141]

i read 30 pages of a book , almost get sth,watch 10 min of statquest, fully understand the subject, you're the best bro

[@statquest]

Thanks!

[@annaspitczok9471]

Big BAM for so much statistic knowledge in such little time

[@statquest]

Hooray!

[@thomasporritt8323]

Great way to break bootstrapping into common language.

[@statquest]

Thanks!

[@dejanspasovic377]

Amazing videos, simple and well explained.

[@statquest]

Many thanks!

[@musefaredi5540]

Nice way of explanation!! BAM!!!

[@statquest]

Thanks!

[@ezequielzion]

Amazing, I love when you say Bam 😂

[@statquest]

Bam! :)

[@ElSamyto]

Okay you are the best thank you for doing this video !

[@statquest]

Thank you!

[@lahaale5840]

Thank you so much, your videos are always so helpful to me

[@statquest]

Glad you like them!

[@Observe411]

Great video! Btw, you could probably do a really good Solid Snake voice. Would love to get an Easter egg in one of the next videos!!

[@statquest]

That would be funny. :)

[@thomasdelossantosverrijp8117]

thank you, this was very helpful

[@statquest]

Glad it was helpful!

[@gitaecookiemonster2892]

Love all of your videos!! Thanks a lot!

[@statquest]

Glad you like them!

[@GeerathBhat-vm1vp]

Thank you so much for your wonderful videos. I have a small request to provide a lecture on FLDA, GMM, EM Algorithm, MLE estimation, MAP estimation. Also, there are some lectures which are not in the book, please also include those lectures too. Thank you so much again!!!. I want to learn more and more from your lectures.

[@statquest]

Thanks! I'll keep those topics in mind.

[@estevaodias6404]

Awesome! The proofs about it seems to be nice

[@statquest]

Thanks!

[@thepresistence5935]

9 th wonder I learned bootstrapping and confidence intervals! hurray!

[@statquest]

double bam! :)

[@SP-qk6vd]

In 8:23 the notation on the x-axis should be median values not mean values since we are using median as statistic measurement for bootstrapping in this case...pls look into it

[@statquest]

Yep. That's a typo.

[@Tozziz]

Dear Josh I bought a few study guides :) Thanks so much for your videos

[@statquest]

Awesome! Thank you so much for your support!!

[@mahdiranjbar3569]

Ur videos are just so cool, tnx a lot

[@statquest]

Glad you like them!

[@Mesye_bober]

Nice work , man

[@statquest]

Thanks!

[@darnelb1912]

Great video! I learn so much with you!

[@statquest]

Awesome! Thank you!

[@YK-jn2kp]

I loved the idea of shameless self promotion idea lol. Thanks for your time and effort.

[@statquest]

Thank you! :)

[@vig9737]

Josh is on Spotify! BAM

[@statquest]

bam!

[@britling9101]

i dont like stats, but damn, this is so easy to understand and the BAMs Got me laughing HAHHA Tysm Josh! Might made me wanna binge watch some of ur vids and learn stats in my own time damn

[@statquest]

Hooray!

[@arifmemovic3383]

You rock Josh. Thanks for making this video!

[@statquest]

Thanks!

[@yingyanhuang1688]

You are amazing! Thank you!

[@statquest]

Thanks!

[@alexyang2002]

really clear, thanks

[@statquest]

Thank you!

[@utkarshsingh2675]

easy to understand....thanks josh!

[@statquest]

Thank you!

[@dylanspodcast]

This guy is great!

[@statquest]

Thanks!

[@DurjoyRoy-ll4zt]

Loved it... Big BAM!

[@statquest]

Thanks!

[@AnalyticsAlchemy-nq3kq]

Nice explanation...awesome

[@statquest]

Thank you!

[@fgfanta]

University professor explained it in a confused and insufficient way (to put it politely), then I came to StatQuest.

[@statquest]

bam!

[@leonelemiliolereboursnadal6966]

you are the best man!!!, tirple bamm!

[@statquest]

Thank you!

[@RobertaBraga_]

Thanks Josh, you are the one!

[@statquest]

Thank you and congratulations again. I'm so glad I was helpful. BAM! :)

[@DragonDragon-qr6mq]

bam. so clear explaination. thx

[@statquest]

Thanks!

[@RoRight]

BAMM! It will be great if you can compare and contrast cross-validation and bootstrapping for us.

[@statquest]

One huge difference is that Bootstrapping uses sampling with replacement.

[@darnelb1912]

I was thinking the same! I usually use bootstrapping when the "test data" in folds is too small, but I really don't know the advantage of using CV instead Bootstrapping or viceversa

[@anakagung7613]

Awesome song!

[@statquest]

Thanks!

[@JosephElfassi]

Super clear, thanks!

[@statquest]

Thank you!

[@alternativepotato]

Josh i dont know if u take requests, but i would love a video about lstm, grus, recurrent neural networks in general. Anyways lovely video.

[@statquest]

Thanks! I'll keep those topics in mind.

[@aszx-tv4pq]

finally statistics make sense

[@statquest]

bam!

[@bushraw66]

Thank you

[@statquest]

TRIPLE BAM!!! Thank you so much for supporting StatQuest!!! :)

[@olivier306]

absolutely perfect god bless you

[@statquest]

Thank you!

[@Cuddpo]

Thank you 🙏

[@statquest]

You’re welcome 😊!

[@marlocosta5531]

Thank you JOSH!

[@statquest]

bam!