What is a Normal Distribution?

[@alecdelu83]

Bro, this video should be nominated to a Nobel Prize. It clarified me very important concepts, I think I love you. Thanks for your clarity, you are AMAZING.

[@Covenante39]

THANK YOU! I hate when professors or books talk like we already know why this normal distribution exist. Very helpful!

[@zafraan3038]

God bless you human.

[@biniljoy2542]

Thank you 😇

[@sumanthmopidevi2341]

This is the real way of teaching thank you very much for your explanation .

[@BeyondNoise9]

Man !!!! I've never seen a better teacher. Absolutely BRILLIANT ! PLEASE UPLOAD MORE !!!! ❤️🙏🏻😭

[@Maria-sf8yg]

thank you thousands of times,not thousands, millions. you're a life saver. keep going

[@nievesroca6159]

I don't ever comment but I just had to, THANK YOU SO MUCH for these videos! They're saving my life right ahead my statistics final...There really is no book nor video that explains stats as understandable as this channel! :)

[@AbdUllahKhan-qx8ml]

Amazingly explained. I was always confused by Z. You explained why we need to find and use Z. Thanks

[@HazieRox]

You explain so well, thanks for this! hope to see more videos

[@MdALatif-wt7yo]

Thank you for your nice, informative and clearly explained video.

[@chaotic_singer13]

this guy, bluebrown guy and stat quest guy is pioneer of stats/maths/ML and DL ngl!!!!

[@justahumann810]

For those wondering how we use the Z distribution table : We simply do this algebra 0.4998 (for Z being the biggest value in the table which is 3.59) - 0.4332 (Z = 1.5) = 0.0666 ~ 0,067 (I guess so... )

[@anurandutta2217]

That helped me alot. Thanks sir! Love from India 🇮🇳

[@souvikroychoudhury3612]

Outstanding explanation. Cleared everything

[@barriegatus4344]

Bloody brilliant. Am trying to teach my students stats and put them on to your site. They now understand stats.!!! Good old Aussie - congratulations on great teaching. Go the Wallabies.

[@nicodas]

Very nice visual way of teaching. The software you are using helps to make connection between various parts of learning, when zoomed out. When zoomed out, I get the "I can see the bigger picture" feeling. This software can easily transfer to visualising subjects like history and many more.

[@AdityaMishra-kq9iq]

hi bro, how are you after 6 years

[@shresthaditya2950]

Why Normal Distribution is everywhere Answer: Central limit theorem(as n increases, the distribution of the sample mean or sum approaches a normal distribution) 7:02- Converting Any Normal Distribution to Standard Normal Distribution(Where Mean=0 and Std=1) by using z score and the value which is obtained after applying z-score is the value which will fall in the standard normal distribution

[@Jeffkingson]

you are the best teacher on youtube. Thank you!

[@abishekraju4521]

9 years later... still saving lives. Ahead of exams that is. Still saving em' all nonetheless. This video is what it took for things to finally click for me. It was that _"a-ha!"_ moment.

[@snehaghosh9957]

Very informative video , you have explained everything so clearly along with graphs and diagrams , truly awesome !! thanks a bunch for the help 😊😊

[@ScottEngineer]

Well done!! This has been a game changer for someone that is currently taking statistics. Thank you for putting this video together!!

[@preeethan]

I don't think even the founders would be able to explain it so well :) God bless ya!

[@srishtigupta7904]

Can you please explain how you used the table... Like what values you selected or what you subtracted or added to get that value?

[@sharynmain2432]

Yes most needed!

[@jakesparrow5716]

Excellently concise explanation.

[@abhishekmestry7033]

sir , you are God .....the perfect explaination that's the exact thing I wanted..thank you so much❤

[@shreddersengupta7384]

One of the best videos on Internet, completely cleard all my doubts, Pls make some course on Udemy, I have taken some course there, but most failed to make these concepts clear properly.

[@AS-nx9fu]

Thank u for this... I finally understood the logic applied

[@hugueslortieforgues3867]

I find the picture of the students in the classroom at 2:02 very misleading! It has the shape of a normal curve, but it is not a normal curve. The taller students should be on the right side, not in the middle.

[@nirajpatel2400]

I was also thinking the same...

[@mouli106]

The whole idea is to correlate that as the number of students increase, the arrangement of heights tend to be a normal curve. Thus find the arrangement in line with whats being explained.

[@krishnabarfiwala5766]

True but then how would the height variable explain normal distribution??

[@sugamshrestha9166]

exacltyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy

[@Abhilashachaturvedi]

You know you are awesome..n gifted the way u simplified things here....coming from a stat novice :)

[@bamboozledan]

Really easy to understand thank you so much.

[@aimanali9868]

Perfect as always ❤ New subscriber

[@sebon11]

Very clear explanation

[@AgamGamez]

Thank you for helping others. Explained well.

[@hamshahamsha3636]

Thanks you From Sri Lanka

[@aneeshaph5007]

great teacher😊

[@swarnachoppella388]

Thank you so much!!! It's really great Video :)

[@NandishPatelV]

Brilliant! Thanks Justin. KeepSmiling 😊🐣

[@mtmrf4489]

WHAT AN EXPLANATION APPRECIATED

[@ankitchotaliya4431]

30th of july 2021 superb man

[@MaxZRider]

Amazing explanation. the examples helped so much!

[@javeriaaftab9358]

Your content is amazing plz make some videos related to stochastics

[@SDEY369]

nice explanation

[@ebewhitecaspian3402]

I think the probability you found for above 190 cm height should be on the left of the line towards mean and not at the right of 190 cm line.its a mistake. It should be 1-0.067

[@mhsahinahmad6041]

perfect explanation. thank you

[@anushaaaa5001]

bless this man

[@manjunathakarantha452]

Hi, Thanks for the video. It would be great if you can do an extensive video on Central Limit theorem

[@Nick12391]

Please do lognormal distribution!

[@bhaskarpaliwalbp]

Please make a video on Weibull distribution

[@Jerrel.A]

Very well explained!

[@jitendar7]

Clear explanation , thanks

[@karankewat1.10]

Thank You 😊

[@minnaabdelkader1945]

Thank you.

[@angelomenezes6044]

Thanks for this awesome explanation dude!

[@omarallam4548]

Thanks a lot ❤

[@JaiShriRamJaiRaghuveer]

1.5 z value = 0.933 , this is area till 1.5 or upto 190 height, we are looking for greater than 190, so the calculation is 1-0.933 = 0.067. Love you all. Peace

[@PrasannPandya]

Thank you for such a good explanation!

[@shavisharma3367]

Thank you. You're great.

[@shreddersengupta7384]

@3:25 For two coin toss, total outcomes are HH, HT,TH,TT 0H = TT => 1/4 = 0.25 1H = HT,TH => 2/4 = 0.50 2 H = HH, => 1/4 = 0.25

[@sumeetKumar91]

We want more videos from you. That was fucking brilliant!!

[@sabari7881]

Great explanation !!!

[@playerplaying3936]

Really helpful thanks a lot

[@anandk5536]

Yes I did normal distribution. Could you teach Gamma distribution.

[@liamhoward2208]

So the parameters are what create the distribution? What would the support of a normal distribution look like?

[@eswaranb8889]

Simple and clear

[@nasarshah3631]

Nice teaching method

[@paominhaokip6430]

Can u do a little detailed about normal distribution

[@ankitghosh8256]

The data you took from he table seems corresponding to -1.5. I dont know if this is a mistake of my understanding or a overlooked mistake. Please help me to get this clarified. Thank you in advance

[@nurbekyelesh5690]

i think its mistake too

[@priyankakushwaha1157]

How can this distribution be used in statistics, data analytics and real life? What are the limitations of normal distribution and how can they be circumvented?

[@hansikareddy6765]

Because variance is the square of standard deviation

[@Maciek17PL]

I don't really understand how does central limit theorem apply to the classroom example

[@ankitarockinggirl]

How is it different from Binomial distribution? Every trial has 2 outcomes, getting a six and not getting a six. Every roll is independent.

[@yuvarajyuvi2747]

Well done dood, thank u so much

[@dean8147]

Which distribution theoretically, represents the distribution of arrival rates of an event taking place.? Not sure if this is articulated well enough however i have a dataset that captures the arrival rate of unscheduled cars arrving at a garage for emergency repair. Sampling the data and plotting it on a histogram; it takes form of a normal distribution but im uncertain in my decison. Thanks for anyone who can help.

[@MrKingoverall]

I LOVE YOU MAN!!!!!!!

[@krishnabarfiwala5766]

At 4:15 explanation, did u find the probability of heads and prob of sixes using binomial distribution? i was wondering it has to be binomial if not then which?

[@Angelwrites]

Tell me exactly how you calculate the 0.067%

[@ervinabajrami]

Thank you!!

[@raghavendrakaushik4871]

Why is the standard deviation of a normal distribution = 1?

[@tanmaychandak9958]

thanks

[@AMRUTA-s7t]

a better resolution video and one video on CLT is requested

[@boburjonmamatov5079]

Thanks alot!!!

[@richashrivastava3981]

How is SD 1 in standard normal distribution

[@neon4119]

did you do a video about log normal?

[@SriKandarpa]

very nice

[@MohammedNoureldin]

At 4:17 the probability of getting six (the shown value) is wrong. Isn't it? I would expect to get 1/6 and not 0.33

[@gian-lucahardmeier2806]

the probability of getting one 6 is actually 0.323. you can calculate this like that: 1. what do we want to calculate? -> the probability of getting one 6 2. how many rolls? -> 10. if you think about it, one possible scenario where we hit only one 6 could be (no = not 6, yes = 6): no, no, no, no, yes, no, no, no, no, no. now you have to calculate the probability of that scenario: (5/6)^9*(1/6) = 0.0323 (5/6)*9 because thats the probability to roll no 6 for 9 times and (1/6) for rolling one 6. but thats only one possible scenario. If you think about it, there are 10 possible scenarios with 10 rolls and only hitting a 6 once. you could roll a 6 with roll number 1 and then 9 times no 6. or you roll a 2, then a 6 and then 8 times something except a 6. so to recap there are 10 different scenarios and on scenario has the probability of 0.0323 which means: 0.0323 * 10 = 0.323

[@pythongui5199]

Nice

[@harshitjain7428]

4:20 the graphs x-axis not having exact values maybe, thanks anyway content's great

[@anirudhranjan2934]

Exact values meaning?

[@rnbsn]

V nice

[@abhayanand1668]

Yo man. The best..

[@robosergTV]

if i have only the data w/o the standard deviation, how do I calculate it ?

[@levitatingmonkeys9544]

great introduction vid, well explained. thank you!

[@manilambardar3163]

Your voice or accent sometimes seems like ‘Lucifer’ Netflix

[@mustafazulfiqar7764]

👌👍👍👍

[@juanbertone1941]

Is there A button to give more than one like? Thank you!

[@Awesome-sh7db]

Not all heroes wear capes T-T

[@victorisrael6191]

Nerdest shii😂😂

[@rsreelekshmi60]

Thank you❤

[@sathiswaranpalanisamy4471]

I have been learning statistics as part of AIML, confused so long why and where to calculate z-score and p-values. Your simple and amazing explanations save my lot of time. Thanks a lot!!! Truly you are a legend

[@vikashgauravvkg]

such an excellent explanation

[@ClaudioApuzzo]

Keep making these videos