Maximum Likelihood, clearly explained!!!

[@statquest]

Support StatQuest by buying my books The StatQuest Illustrated Guide to Machine Learning, The StatQuest Illustrated Guide to Neural Networks and AI, or a Study Guide or Merch!!! statquest.org/statquest-store/

[@tiankhean]

I just want to tell you how much I appreciate your videos. I am a 74 year old retiree living in Singapore doing time series analysis of financial markets data using NumXL software. For the first time, I understand Maximum Likelihood Estimation. I have signed on as a Member and hope to learn more by watching your unique so-clearly-explained videos. Thanks again.

[@statquest]

Wow! Thank you very much for your support!!!

[@vishalthakran1743]

bro,you just need to chill at that age!!!!

[@solar0wind]

@@vishalthakran1743 Nah, the one who rests, rusts. You need to keep going and stay stimulated with something fun, instead of just resting all day for the rest of your life. My maternal grandma became a volunteer castle tour guide in her late 70s/early 80s. My paternal grandpa learnt a whole new language because they moved to my paternal grandma's mum's country of origin for retirement. My paternal grandparents visit a technology class every week to keep with the times. The only one who has dementia now and is deteriorating fast is my maternal grandpa. He is the only monolingual of my grandparents and barely had hobbies (pretty much just gardening) after he retired. So he rested, and now he's rusting. My grandparents are btw between 1 and 3 years before 90. So this guy has plenty of time left to live his life and learn.

[@Swisspokerboy]

Sometimes I think professors make it extra hard for their students at University by explaining simple things as complicated as possible.Luckily there are guys like Joshua. Great video!

[@Quasarbooster]

Kevin H. I couldn't agree more. Thanks Stat-Quest!

[@WiseandVegan]

The untold secret to civilization (a lecture): kzbin.info/www/bejne/boG0ZaasqaaZo6s

[@keronnicholson8313]

I have always said I think the 'community' tries to remain as small and closed as possible by making it hard for people to understand.

[@Ewuraa_D]

They themselves do not understand

[@MJ-ye7dd]

@@Ewuraa_D I also think so

[@rubberlung1]

It is just ridiculous. I paid several thousands USD to my college and end up at getting better education in youtube.

[@statquest]

I'm glad to hear this video helped you out! :)

[@questforprogramming]

But some companies are asking for certifications...damn

[@prizmaweb]

It is because I paid several thousand USD for my masters but still felt my education was outdated, that I still come and watch youtube for more ( to sort of recover my investment)

[@CRockaell]

no kidding... same here!

[@xj-vn4eo]

Getting to college makes me appreciate more of the internet resource.

[@cosmopolitanPJ]

From all statistics courses I've taken so far, I've never heard about the difference between likelihood and probability. As we can expect from any StatQuest, it was clearly explained. Thank you Josh, cheers from Hungary!

[@morningmoon6100]

If you can explain a concept with simple tools, it means you really understand it well, else you are just memorizing ! You are doing a great job !

[@statquest]

Noted

[@abhinavwaddinavar9205]

I just want to express how much I appreciate your videos. I’m an 84-year-old retiree diving into the fascinating world of string theory. For the first time, concepts that once seemed incomprehensible are starting to make sense thanks to your clear and unique explanations. Your teaching style is truly a gift, and I’m excited to keep learning more through your incredible content. Thank you!

[@statquest]

Thank you very much! :)

[@Latesttechs]

I am doing my Masters in Informatics right now and I feel bad I didn't find you during my Bachelors lol would have cleared so many concepts years ago but better late than never God bless you dude lovely precise explanations to brush up on things and understand them.

[@statquest]

Thanks!

[@kienhoang3819]

I'm doing a PhD in Economics, and we learnt Maximum Likelihood with a lot of math formalisations. But then your short and simple video is exactly what I need to get the intuition behind everything. Thank you so much!

[@statquest]

Glad it was helpful!

[@pluetsy2324]

the intro made my day man.I have a shit tone of assignments and i am low on time so really that little guitar gig made me smile.Also great work on the explanations.KEEP it up!!

[@statquest]

Thanks and good luck with your assignments. :)

[@kellenswain2049]

The "Large-Boned" was priceless. Well done.

[@statquest]

Hooray! :)

[@snake1625b]

The distribution is bulking

[@andrewd1788]

no doubt some people will think that's the actual term for it and will write "large boned" in their coursework lol

[@rebelai5981]

🤣🤣🤣🤣

[@herobrine1847]

I totally thought I was misreading it and assumed it was “large bound” before taking my glance off of it… holy shit he actually said it

[@CocaBrunel]

Wow! You litterly nailed it first sentence. 'Why' seems to be the most difficult question to ever face statisticians. I've read an entire textbook and still been unable to grasp, Why at an intuitive level. " it's the optimal way to fit a distribution to your data" job done. Thankyou so much.

[@statquest]

Thank you! :)

[@siddheshzadey9714]

You're a statistical outlier when it comes to teaching! Above 100 SDs on the scale of teaching goodness :)

[@statquest]

I love this! Thank you.

[@jc_777]

Agreed. It's almost as if college stats professors have some kind of coalition for teaching badly, and somehow Josh wasn't invited.

[@kyledampier]

I literally applied to UNC because of him

[@jc_777]

This video has helped distressed students who are awake at night all around the world for over 3 years .... and counting. Joshua can make a religion for students & grad students and it will become a major religion in no time. I mean, he's literally "Joshua". The Holy Book will be named "StatQuest".....

[@statquest]

:)

[@bennasserchafi304]

you deserve an oscar. i have been struggling for years to understand this thing. and you came from nowhere and explained it in such an easy and beautiful way. i really think you.

[@lanxizhang2816]

Best teacher in the world! Even English is my second language, I can understand you easily.

[@statquest]

Hooray! :)

[@mohsenr.estabraq5808]

Whenever I get confused reading Statistics books, I come here. Thanks!

[@statquest]

Happy to help!

[@theq18]

I wish I saw your video 10 years ago during graduate school. I finally understand the maximum likelihood! THANK YOU!

[@statquest]

Better late than never! :)

[@user-up5kh2mz4n]

The enthusiasm in the video makes the learning experience more motivating!

[@statquest]

Thanks! :)

[@nimishabunga]

You have made statistics so much better and easy for people like me (who have been avoiding it for so long) , Thankyou ❤

[@statquest]

You’re welcome 😊

[@iamgroot3834]

I spent the whole day trying to understand this. Its just now that i found your video on youtube. GOD BLESS YOU. You are greaaattttttttttt.

[@statquest]

Hooray! :)

[@bhumikasoni361]

If not a teacher, you could very easily be an awesome songwriter and singer! But, as the luck would have it, you blessed us with the best statistics videos instead :D Thanks Josh for such clear explanation :)

[@statquest]

Thanks!

[@sintumavuya7495]

I loved this. You have no idea how I needed this. We just started this chapter this week and just knowing what it is that I'm trying to do is really calming. Now I can listen with understanding.

[@statquest]

Thanks!

[@srishtisingh2170]

Every time I see a video here, it makes me fall in love with statistics a little more...❤️

[@statquest]

Wow, thank you!

[@stylyxmephix2365]

Bro wtf this is the revolutionary. This is amazing. Thank you for sharing your knowledge. You made something so clear in six minutes. I am deeply impressed. May fortune be with you.

[@statquest]

Thank you!

[@burninmind]

WOW! it was literally the best explanation of MLE I've ever seen! Well done!

[@statquest]

Wow, thank you!

[@ThinkingRockh]

Gold content. Can't find anyone on KZbin really try to explain the phrase "maximum likelihood". Thank you so much!

[@archowdhury007]

Excellent video....loved the way you explained it. FINALLY!!!!! I understood what MLE actually means. Great work Josh! :)

[@statquest]

Hooray! :)

[@fatsquirrel75]

I sat through a 3 hour stats lecture earlier today and had no idea what he was talking about. Thanks to your 6min video actually learned something about likelihood functions today (and it turned out to be so straight forward too). Thanks.

[@teetanrobotics5363]

I think you're the king in machine learning and statistics on KZbin. Could you please make a playlist for deep learning as well ?

[@statquest]

I'm going to make deep learning videos in the next few months.

[@CainisUponUs]

Such amazing timing! One of my mathematically inclined friends just told me that we could use maximum likelihood to determine how many times I had to conduct an experiment to produce a statistically significant result, but I had no idea what she was talking about till I saw this!

[@Sabu113]

This is so refreshing. I just had to take these things as 'given' in my econometric course.

[@statquest]

I'm glad my videos are helpful! :)

[@matthewjung5446]

First time on your channel, the intro had me questioning what I was doing. I am eternally thankful I stayed until the end! Cheers mate, great content.

[@statquest]

Thanks! :)

[@scottgrenestedt]

Very intuitive. Phenomenal explanation, Mr. StatQuest :)

[@statquest]

Glad you think so!

[@TheFartoholic]

I've been looking for a straightforward approach to explaining this concept - you've provided the perfect blueprint. Thanks!

[@statquest]

Thanks!

[@NitishPareek]

There could not have been a better explanation of this topic.

[@statquest]

Thank you!!!

[@stekim]

Thanks statquest, grad student here and this was clearer than what I get currently at school.

[@statquest]

Hooray!!! :)

[@fransdany2452]

Sir Josh, you have no idea how helpful your explanations are in your videos. Waaay better and clearer than available statistics textbooks and lecturers. I am wondering if you can make other videos regarding difference between maximum likelihood vs penalized likelihood and the application of penalized likelihood in Firth's Logistic Regression (as well as its interpretation). I encounter a quasi-separation problem after running binary logistic regression while the sample size is not that small (~1800). Any thoughts will be highly appreciated. Best regards

[@russellandrady]

That's great. Nicely goes to the deep. That was smooth.

[@statquest]

Thanks!

[@joeaustinathimala768]

How the hell did I not know you before ? Excellent video. Kudos man.

[@statquest]

Thanks! :)

[@tiredkiris]

I don't know how to thank you but this explanation really helps me understand what I'm reading elsewhere. I really appreciate the work and thought you put into teaching us an intuitive approach.

[@statquest]

You're welcome! I'm so happy to hear that the video was helpful for your understanding.

[@rockerjatt]

Mr. Starmer, may I request for a video on MAP (maximum a posteriori) inference? Subsequently, a comparison of MLE vs MAP will also be extremely helpful

[@geraldidzakwan8666]

You saved my life, best plug in principle explanation I've ever watched. I need this to solve a best estimator problem for some probability density function.

[@statquest]

I've got a few examples of how to use MLE to estimate the best parameters. Here's an example for the exponential distribution: kzbin.info/www/bejne/pmS3XpKCgtepeMU and here's an example for the normal distribution: kzbin.info/www/bejne/ep-Zk2yceK6Ipq8

[@sherifgerges9316]

Excellent.

[@cloveramv]

4:53 BAM!

[@ericosa7002]

I am to see your effort of this platform &an excellent videos , please can you show me how R software to teaCh these statistical inference theories

[@kallehallden4855]

So in essence the type of distribution is determined by Goodness of Fit and the parameters of distribution are determined by Maximum Likelihood. Thank you professor.

[@samuelieremie8443]

Thank you so much for explaining this concept so easily. You are a true blessing.

[@statquest]

Thanks!

[@AliAPanahi]

Wow, The simplest explanation I've seen.

[@BillHaug]

needed a refresher on the concept, was rewarded with the jam... still crushing.

[@statquest]

bam!

[@jedidelalog9834]

Wonderful video!! and I spent a lot of time to understand a "silly" formula when it would be enough to see your beautiful video :)

[@statquest]

Thanks! I'm glad it was helpful. :)

[@andreajulieth100]

this is the greatest explanations that I found in all google search great job Josh

[@statquest]

Thanks!

[@grigoryshepelev8149]

Thank you a lot! I'm passing an online course on statistics that has NONE simple graphical representation of terms and teacher always looks at his papers. This sucks. But at least it has some structure on the subject.

[@statquest]

Hooray! I'm glad the video is helpful. :)

[@koochibabua1904]

Same with me. My course is on Bayesian statistics. The instructor foolishly copies from his notes by looking down all the time.

[@tigaochapanas]

MLE is a crucial concept for machine learning. Thank you so much for this nice explanation!

[@statquest]

Thanks!

[@aimeecalepso]

Every time I listen to the intro I can imagine Phoebe singing it. Thanks for the explanation, your channel is the best I found about statistics on youtube and it's helping me analyse results for my thesis

[@statquest]

Awesome! If this intro song reminds you of Phoebe, check out this one: kzbin.info/www/bejne/emHIl3t7f9iZftE

[@yashodperera]

The best statistic tutorials from youtube. Thank you

[@statquest]

Wow, thanks!

[@Праведныймиротворец]

I'm doing a masters degree and yet youtube is a better teacher

[@statquest]

Thank you! :)

[@JosephRivera517]

There are actually a lot of explanations of likelihood, but this one gives the best presentation.

[@statquest]

Thanks!

[@JosephRivera517]

@@statquest My pleasure.

[@awfominaya]

Finally clicked for me after years of trying to figure this stuff out.

[@statquest]

Hooray!!! :)

[@aaronpedraza8974]

Same case Adam, that's great!

[@shark-p4o]

"clearly explained" is actually clearly true. Thanks a lot sir

[@statquest]

Thanks and welcome!

[@kavyayugg]

No words to say 😊how easily you explained everything 🤠🤩

[@statquest]

Thanks!

[@harshalpimple3143]

Thank you so much Joshua for this uniquely-explained video!!!

[@statquest]

Thank you!

[@SupremeChickenx]

'large boned' HAHAHAHA this guy sounds 5% sarcastic at all times i love it

[@statquest]

:)

[@BillHaug]

Hey I have watched this several times for the content... thank you... and then several more for the opening song

[@statquest]

BAM! :)

[@rodrigo10239]

Simple and clear, as it should have always been! Thanks ALOT!

[@statquest]

Thanks! :)

[@isaacadjetey9618]

Intuitive way of teaching yields better understanding than the so called “robustness “……Make concepts intuitive to me in simple terms and robustness will be nothing but mere usage of dense notations. God bless you StatQuest!

[@statquest]

Thank you very much! :)

[@cantkeepitin]

Great explanation. However, from watching to doing is still a big step. I can recommend everyone to also do the calculus, really getting numbers. Maybe for a uniform distribution, having no difficult formulas, like the "normal" distribution has.

[@statquest]

I've got a few examples of the calculus in action for the binomial distribution: kzbin.info/www/bejne/anyuh2yvj6iig5Y for the exponential distribution: kzbin.info/www/bejne/pmS3XpKCgtepeMU and the normal distribution (this one is long since the math is messy): kzbin.info/www/bejne/ep-Zk2yceK6Ipq8

[@MLDawn]

I really enjoyed your terminology alert! Good catch!

[@statquest]

Thank you very much! :)

[@andreyko3yrev]

When you say "probability or likelihood" you effectively make these terms mean the same thing, while the whole point is that they are different.

[@yogiwhy9531]

The best explanation of MLE I've ever seen!

[@statquest]

Thank you!

[@maurolarrat]

In 3:33 and forward, in each step we calculate the product operator for all gaussian functions taking the data as input. The resulted product with the highest value will indicate which gaussian function to choose. am I wrong?

[@statquest]

I believe you are correct. At the first step, we have a gaussian function on the far left side of the screen - and to calculate the likelihood of that specific function (with the mean over on the left side), we calculate the product of the likelihood of that function given the first datapoint times the likelihood of that function given the second data point times the likelihood of that function given the third data point, etc. Then we shift the distribution to the right a little bit and calculate the same product using the new mean, etc. Until we find the mean that results in the largest product.

[@maurolarrat]

StatQuest with Josh Starmer Thank you very much.

[@statquest]

Hooray! :)

[@hmingthanavanchhawng9993]

I had finals tomorrow. You're a lifesaver!

[@statquest]

Good luck!

[@hmingthanavanchhawng9993]

@@statquest thanks. New subs here.

[@statquest]

@@hmingthanavanchhawng9993 BAM!

[@rameshmaddali6208]

Best thing i found for this week, so clear to understand - lots of appreciation for your lecture.

[@statquest]

Thank you! :)

[@carloschire5777]

Thank you, very clearly. It was a good recommendation in a virtual class about Maths for Data Science, greetings from Peru

[@statquest]

Muchas gracias!

[@MecchaKakkoi]

Video starts at 0:30 :D

[@utkarshanishad2413]

Excellent Explanation!!!

[@statquest]

Glad you liked it!

[@hellasleepypal]

I can’t wait to present at a conference and use “large boned” without giggling

[@statquest]

That will be a funny day. :)

[@SpecialBlanket]

I would be really careful. Weight isn't a federally protected characteristic but we're getting there. I wouldn't joke about anything that alludes to demographical features of humans and/or their sensitivity about it (which is what "big boned" means-- euphemism for fat bc people are embarrassed to say they're fat) in academia. No one's going to care in a math dept / conference but if it's mixed field with undergrads there? Ehhhh.

[@hellasleepypal]

S. E. Z thank you for pointing that out I wouldn’t use big boned, I was just kidding. Loll

[@haleemaghafoor2147]

LOVE THE WAY YOU EXPLAINING THE CONCEPT

[@statquest]

Thank you! :)

[@VictorOrdu]

Woah! Do they intentionally obfuscate this knowledge with all those formulae?

[@statquest]

That is a great question! It's not nearly as complicated as a lot of people make it seem.

[@maxxpro4]

yes

[@ivomitdiamonds1901]

Did you intentionally obfuscate this comment with the use of the word obfuscate? I think the answer to your question is the question itself. 1. You knew the word and understood and hence assumed that everyone else would. (The professors might do the same with the formulae.) 2. You just wanted to show off your vocabulary (The professors are human too.) Haha, just a thought, I know what you mean though. Cheers, Ani,

[@waterspray5743]

So weird. My textbook says nothing about MLE being the mean of the distribution. Why can't the authors just be clear and direct instead of making us read between the lines and figure out what they mean.

[@joseeduardolira4683]

Hi, Josh! Thanks for another great video! I´ve been searching, for a while now, for a video about a method for unsupervised clustering called Growing Neural Gas Networks. It has been an unsuccessful quest. Maybe you could think about a video on that theme! Congrats and thank you very much. Cheers, JE

[@statquest]

I'll keep that in mind.

[@pite9]

I'm just here for the song intros.

[@statquest]

Awesome! :)

[@Alexandru-3]

I guess they're right...if you cannot explain it simply, you don't understand it well enough. Thank you for this video!

[@statquest]

You're welcome!

[@dr.ksartplace3785]

Subscribed! I’m so glad I found this channel. I struggled with stats throughout college. To the point that I gave up on the field and avoided it as much as I could. Watch out statisticians. I’m back with “vengeance” to devour this field. :-) Seriously! Thanks for putting these videos together. Highly informative.

[@statquest]

Awesome!!!!

[@petretrusca2]

You saved me, from the terrible explanation of my teacher.

[@statquest]

Bam! :)

[@themlongplays4961]

I feel like professors don't do a great job at bridging the gap between theory and practice especially in the later upper division stats classes so I end up knowing how to calculate things but I have trouble understanding why. That's why I love this video. Thank you!

[@statquest]

Hooray!! I'm glad the video was helpful. :)

[@spaceymchaggis1792]

I just tune in for the intro ;)

[@spaceymchaggis1792]

Joshua Starmer And you're doing awesome. You videos have already helped me a lot with my work!

[@spaceymchaggis1792]

Joshua Starmer absolutely! Going through my books and R scripts can be quite dry and you videos provide another view onto certain topics. They are great!

[@andersonbessa9044]

Best explanation for maximum likelihood ever! Thanks so much

[@statquest]

Thank you! :)

[@batman76781]

What is the probability distribution of people who like the weird ass intro song the statQuest videos start with? It's distributed by Uniform(0,0).

[@statquest]

Dang....

[@dpm2213]

Did you go back to old vids and give your timelines subsections when that feature came out? What a legend.

[@statquest]

The feature came out a few months ago. I went back and added subsections to a bunch (but not all) of my old videos. It's something I do when I can't sleep at night.

[@alecvan7143]

"or large boned"

[@statquest]

yessssssss! :)

[@rikawrites7104]

ABSOLUTELY ASTOUNDED BY THE WAY YOU TAUGHT ME THIS. thank yaaaa

[@statquest]

Thanks! :)

[@dilshand.5127]

*Large Boned*

[@Lucid874]

thank you this helped giving me context and background as to what this is lol

[@statquest]

bam!

[@pewpew7108]

Very clearly explained, but man, the little intro songs are cringey

[@statquest]

:)

[@Daniel-to5jd]

best explanation of this topic that I have found so far

[@ruchitagarde4642]

@StatQuest I have started making searches on your channel rather than on youtube search bar whenever I have a question. Please do something on Conditional Random Field (CRF). Amazing work!

[@statquest]

I'll keep that topic in mind.

[@shkmamun]

I don't really understand why we we need MLE for mean which is similar to average. In-terms of standard deviation, it is also almost similar to the normal sd calculation.

[@zxlvckj1402]

Very intuitive! I've never found this kind of clear explanation on any other stats textbooks. Thank you! If there's a chance, I'd like to watch a video on Generalized Method of Moments (GMM).

[@ElinaGoroshkova]

You make the best videos on statistics. Thank you so much! After your videos I would like to study statistics and data analysis further and further! )))))LOL! And I'm 35 years old woman, and just trying to figure out a few concepts for an IRT course. Very interesting and thank you very much for your genius work!

[@abc39722]

Thanks a lot, brother. Ur videos are really easy to follow and comprehensive too.

[@statquest]

Thanks!

[@_APAROOPAPATRA]

The way u explained was really unique and easy to catch👍👍

[@statquest]

Thanks a lot 😊!

[@chinaguy101]

amazing, this is best explaining video on maximum likelihood estimation i ever seem

[@statquest]

Thank you! :)

[@msaparajita849]

Reminds me of Sheldon's show 🤣. Thanks for the explanation and that dose of dopamine 😁👍🏽

[@statquest]

Any time!