Introduction to the Bernoulli Distribution

[@entidoe8]

yeah he is CRYSTAL CLEAR in all of his lectures . straight to the point . most important point is that he takes minimal time and teaches maximum of the topic . Very few can maintain this balance between precise explanation , wonderful time management , and the way he presents the topic, keeps the concentration going on till the end of the lecture . thank you very much jbstatistics

[@DailyDarsh]

This comment is older than my brother

[@rinskydances93]

Thank you SO much. I was nearly in tears trying to understand the jibberish our lecturer was throwing at us. You give clear explanations of WHAT is happening, HOW and WHY, which is what students need and teachers just don't get it :(. Your videos are giving me hope to pass Business Statistics ! Thanks again.

[@Sunnydayz5656]

Amazing love it

[@lofi_ish5613]

omg, you are the best. I hope you do well in life. I am in this class where my teacher has absolutely 0 idea of how to teach. all she does is just read the slides and expect us to understand all of this. it is so stupid and frustrating. I got a quiz worth 5 percent of my grade and an assignment worth 8 percent of my grade to do this week. you are a lifesaver.

[@jbstatistics]

You're welcome! And thanks for the compliment. I'm glad you find my videos helpful!

[@Blackmetalstudios]

took my teacher 45 minutes to explain what you did in 5, thanks

[@jbstatistics]

I try to be concise and get to the point. Sometimes I'm successful :)

[@SaqibAlikhantanoli]

​@@jbstatistics Can you please do a video on Weibull Distribution and Finding it Fitting Parameters (Weilbull Fitting). Thank you for great tutorials!

[@ultimatefraudcrymier2633]

@@jbstatistics thanks a lot My master was not at all willing to teach us this in online classes

[@alvarorubenvera5915]

@@ultimatefraudcrymier2633 We all know we pay university to watch videos on youtube

[@kashaf1423]

Same🤝😂

[@kenhuang1871]

I find these explanations to be very clear. Thanks for helping us all understand stats!

[@jbstatistics]

+Ken Huang You are very welcome. And thanks for the compliment!

[@VS-ey2lf]

Sir, you're truly a legend!! If I didn't find you on youtube I might fail the class!! I have a test tomorrow watching all your tutorials. Already watched the whole playlist of basics of probability, now I'm on this one. Thanks again

[@jbstatistics]

You are very welcome!

[@starja4477]

Your videos are so amazing

[@yousufazad6914]

much like the Bernoulli Distribution, this video is short, concise and to the point. Good job mate!

[@jbstatistics]

Thanks!

[@manshisinha7953]

I've been searching for a video like this for a while and at last i found it. This helped a lot ..thanks🖤 Keep up the good work!

[@jyotikavarmani4454]

Thank you very much for this and every video of yours. I've been through so many videos of statistics before coming to your videos. And you are simply the best. Your clarity and precision are outstanding. Thanks again :)

[@jbstatistics]

You are very welcome, and thanks so much for the kind words!

[@faruqsandi6184]

What a great explanation. Cristal clear in 301 seconds. Thank you.

[@jbstatistics]

You are very welcome!

[@joshguevara9570]

Amazing dude. Clear, concise and straight to the point.

[@reabetsoeadoro8966]

I am so sad that I am only discovering your channel. You are highly appreciated

[@bilbm5208]

Sir, You're making my life better ! thank you so much :)

[@johnn8759]

Bilal Boumaad You can find detailed information, formulas and calculators for "Bernoulli distribution" on trignosource - "trignosource.com/bernoulli%20distribution.html"

[@krystiantomczuk4836]

Great explanation. I really like how clean your video is, very focused on the current task at hand. Superb!

[@jbstatistics]

Thanks for the compliment!

[@Hersh0828]

Underrated statement 3:43 - "What is the point of all this?"

[@jbstatistics]

I try not to just teach the specific topics, but why we might care about it.

[@jbstatistics]

You are welcome Kim! I'm glad you like them.

[@scanguru]

Love the videos. great explanation. Simple and clear. Thanks for creating them.

[@MrAlbashiri]

The explanation is Crystal clear. Thank you for the amazing video.

[@m3tz13]

Thank you so much ! :D omg I'm really thankful for this awesome, clear and simple lesson.

[@jbstatistics]

You are very welcome. And thanks for the compliment!

[@vijaybangari496]

better,simple,useful and exactly what's required explanation...

[@johnn8759]

Vijay Bangari You can find detailed information, formulas and calculators for "Bernoulli distribution" on trignosource - "trignosource.com/bernoulli%20distribution.html"

[@cherishburks1396]

My guy, you are better than Khan Academy!

[@Jack-dx7qb]

Thank you sir for making this *informative* and *crystal-clear* video.

[@jbstatistics]

I'm glad to be of help!

[@aidanwhite8670]

Thanks for not making this a 20 minute video

[@johnn8759]

Aidan White You can find detailed information, formulas and calculators for "Bernoulli distribution" on trignosource - "trignosource.com/bernoulli%20distribution.html"

[@MexterO123]

Why can't statistics class be like this. :/ Straight to the point.

[@johnn8759]

Memo Pony You can find detailed information, formulas and calculators for "Bernoulli distribution" on trignosource - "trignosource.com/bernoulli%20distribution.html"

[@DetectiveConan990v3]

man this is so much more helpful than my professor

[@GoodLuckForever-wi9kb]

Best Of Luck Forever For Sharing Such a Deep Knowledge in such a simple way. Well Done Sir

[@auggie081]

You have awesome videos man, I hope they start getting more attention... Seriously, you >>> Khan academy

[@jbstatistics]

Thanks for the compliments auggie! I agree with all your points :)

[@anika_ara9363]

totally agree with you! I have found this today and I am loving it! :-D

[@anika_ara9363]

totally agree with you! I have found this today and I am loving it! :-D

[@jbstatistics]

+Anika_Ara Thanks! I'm glad you find them helpful!

[@Jeremy_Fisher]

Khan Academy is good for most things. Their strength is the sheer amount of topics they cover. But in general, I find more specific channels like jbstatistics, are better for learning specific topics. Well done, jbstatstics, you did a great job on your channel.

[@roadkil899]

Man I love you..Missed those lec in the Uni and I have finals from another week..Now I'm learning from you..Thank you sooooo much :D

[@anomienormie8126]

Very nice and concise. Clear notes and pronunciation.

[@TheChumbotxj9]

These videos saved me!! Thanks for making them!

[@jbstatistics]

I'm glad to be of help!

[@observever7808]

One of the best 5 minutes of my life LOL

[@hanheeyang9837]

thanks bro, u better then ma teacher. and u gots da good voice

[@otsogilelecta]

far much better than ma lecture's notes

[@paralokesh9991]

Great mouse writer and excellent lecture.

[@AmaniAridja]

I really appreciate your explanation please do some exercises of discrete probability distribution

[@priyakiran6402]

Very nice and to the point inputs....keep going

[@pidchayaninchutipattana7612]

Youve just saved my life

[@jas08057]

Perfect explanation, thank you so much!!!

[@yangxuanxuan]

very clear and decent explanation, thank you!

[@surbhikohli8559]

extremely helpful video. Superb explanation

[@jbstatistics]

You are welcome!

[@rachsteve3996]

Wow bro what an explanation Thankssss😇😇😇

[@ziekaman2450]

sorry a little bit too abstract for me. Very unclear what the difference between X and x actually is. Also no idea how to find p.

[@kaizerbyparthpratyush217]

It's basic algebra bro X and x are the same place holder. Eg- X = x could be X = 4.

[@halkcompany7173]

In 5 minutes I understood more than in a 90-minute lecture

[@kimmusak1611]

Thanks for the great videos you have them here

[@helenso9462]

YOU ARE AMAZING SIR maybe god bless you!

[@harryli2546]

hey guys, quick questions, can we assume x = 3 or 4 instead of 1 or 0? Would that function still hold?

[@jbstatistics]

No, it wouldn't work as is. If you want to write P(X=3) = 1-p and P(X=4) = p in one function, then you'd have to tweak the Bernoulli pmf to P(X=x) = p^(x-3)(1-p)^(4-x) for x = 3, 4.

[@TheAprilMendez]

this is incredibly clear. Thank you!!

[@anirudhthatipelli8765]

Thanks, this was very clear.

[@tawseeftaher9109]

resume 2:00

[@valeriereid2337]

Excellent.

[@giraganipallavi4594]

thq very much sir ur videos are helpfull

[@WilliamKinaan]

Kindly why the mean equals to "p"? Should it be "[ (p) + (1-p) ] / 2" = 0.5 ?

[@adminenetzone6330]

Do all descrete probablity distributions depend on bernoulli trail? Or there are descrete distributions that depend on other trails?

[@evanv2258]

college would be much more productive if all professors taught like you do :)

[@TarunArora01]

I came here to get my queries solved but seems like they have been multiplied now :'D

[@ulamss5]

So little x can only be 0 or 1?

[@cedricmmangisa385]

Yes

[@sanjeevdubey8913]

Awesome man. Keep it up.

[@jbstatistics]

Thanks! I'll get back to video production soon.

[@gpminsuk]

Question.. let's say I pull an American adult once a month. And number of American adult lawyers increases over time (p changes over time). Is this still Bernoulli distribution?

[@jbstatistics]

For the Bernoulli, n = 1, so each time you draw an American the # of lawyers you get (0 or 1) is Bernoulli. The following month, n=1 again, and you once again have a Bernoulli r.v., this time with a different p. Same idea in the following months. Each and every time it's Bernoulli, just Bernoulli with differing p. If you're asking whether the sum of those Bernoulli random variables would have a binomial distribution, then no, no it wouldn't (since p changes from trial to trial).

[@Rizz-hu4jq]

thanks sir ....it helps a lot

[@F91RPG]

Sorry although you said there is not too much difficulty, but I still don't understand why variance= p(1-p)

[@eryseayliid1535]

Is the Bernoulli distribution the same as the "normal" distribution? It was asked in the sample exam but I wasn't able to find anything indicating or denying it :/ Update: Normal distribution is in the topic of Continuous Random Variables, and not in Discrete Random Variables, so the 2 cannot be the same under any circumstances.

[@jbstatistics]

They are very, very different distributions. Pretty much the only thing they share in common is that they can both be labelled as probability distributions.

[@eryseayliid1535]

@@jbstatistics Thanks for the reply and the content, both are amazing! C:

[@thedeathofbirth0763]

You simply rock!

[@Irina-k2p3m]

thank you teacher I love you

[@giliniieriop5700]

Very helpful! Thank you!

[@jbstatistics]

You are very welcome!

[@sangmadewira4726]

Hold on, I dont understand why the variance is p(1-p), why is it the p of success times the p of failure?

[@jbstatistics]

I derive the mean and variance of the Bernoulli here: kzbin.info/www/bejne/mHSZiHymh8yAq8U&ab_channel=jbstatistics

[@sangmadewira4726]

@jbstatistics holy cow what a fast response, thanks sir

[@SaqibAlikhantanoli]

​ @jbstatistics Can you please do a video on Weibull Distribution and Finding it Fitting Parameters (Weilbull Fitting). Thank you for great tutorials!

[@mohammedsamsuddin5126]

Great Video Keep it up

[@jbstatistics]

Thanks!

[@khalidmuhammed3058]

Does it relate to logistic regression ?

[@sedatcapar]

Your lecture is good, but the example is wrong. if the variable X is the number of lawyers then what is the probability of 2 layers?

[@jbstatistics]

The probability of getting two lawyers in a sample of one person is generally accepted as 0. The example is not wrong. X represents the number of lawyers in s sample of size 1. In other words, is the person a lawyer or not? A Bernoulli random variable results from a single trial of a yes/no 1/0 scenario.

[@kl6544]

but what if the person is pregnant?

[@probono2876]

Great Stuff, many thanks !!!

[@johnn8759]

pro bono You can find detailed information, formulas and calculators for "Bernoulli distribution" on trignosource - "trignosource.com/bernoulli%20distribution.html"

[@ArijitBiswasdotcom]

Hi, could you kindly clear my doubt? What if we pick more than 1 sample in a trial? Would that still follow the Bernoulli Distribution? Or are we allowed to only pick 1 sample per trial?

[@jbstatistics]

A Bernoulli random variable is one that takes on the possible values 0 and 1. If you have a situation where your random variable takes on values that are different from those, you don't have a Bernoulli random variable.

[@ArijitBiswasdotcom]

Thank you very much for answering! However I do have this doubt ... even if we pick 2 samples i.e. if we toss 2 coins, the possible values the coins can take on are 0 or 1. Is this a Bernoulli Distribution or some other? Could you kindly help me with this please?

[@jbstatistics]

You need to be a little more precise with the problem. You're tossing 2 coins. Coins aren't random variables on their own -- they are coins. What are you counting? What is your random variable? What values can that random variable take on?

[@ArijitBiswasdotcom]

Okay sure! Suppose I want to count the number of heads that comes up when I toss 5 coins in a single trial. So the random variable is - number of heads, the possible values that it can take on are H or T. So what would be the distribution of the number of heads in this case? Would it be Bernoulli still? Thank you in advance for your help!

[@jbstatistics]

If you toss 5 coins and count up the number of heads, then the possible values of that random variable are 0, 1, 2, 3, 4, 5. The possible values of the random variable are not restricted to 0 and 1, so it's not a Bernoulli random variable. If the coin tosses are independent with a constant probability of success, then the number of heads follows a binomial distribution. (A binomial distribution with n = 1 is a Bernoulli distribution.)

[@thanojishing534]

power of 0=1 so p(x=0)=(1/200)power 0.(1-1/200)power 0=0?sdnt it be 0? how it is 199/200? please explain in detail sir

[@jbstatistics]

P(X=0) = (1/200)^0(1-1/200)^(1-0) = 199/200.

[@thanojishing534]

o got ya... i missed (1-1/200)^(1-0)... thank you for responding

[@pubgdynamodecks4927]

cud these be used for simulation and modelling??

[@jbstatistics]

Sure, depending on what you are simulating and modelling :)

[@shrimatkapoor2200]

Why do they teach the Bernoulli distribution if we can just learn about the Binomial distribution directly

[@siyuwang1928]

you saved my gpa

[@thabangkhoetha6978]

Wow I always ask myself what's the point and what are we rying to find out and i got the answer here

[@godsavebulusdul9648]

this is awesome

[@Sam91]

well explained, Thankyou. (:

[@johnn8759]

Shiv Aditya Mishra You can find detailed information, formulas and calculators for "Bernoulli distribution" on trignosource - "trignosource.com/bernoulli%20distribution.html"

[@pramishprakash]

Thank you sir....

[@jbstatistics]

You are very welcome!

[@たかはしいつき-f7l]

What if its like x=0 P(x)= 2000

[@jbstatistics]

I don't know what that means. The probabilities must lie between 0 and 1.

[@たかはしいつき-f7l]

@@jbstatistics yeah that one is not Bernoulli hahahah

[@deginettilahun]

very good

[@jbstatistics]

Thanks!

[@Nishkarshnagle]

Man who disliked this video,, man

[@drallisimo34]

cool stuff!!!

[@Dom-fx4kt]

Brilliant.

[@muhammadwaseem2304]

Thank you🙂

[@benjaminli3808]

The Patrickjmt of Statistics n_n

[@backagain-forgive]

Thank you

[@EbenezerMandala]

thanks sir

[@ericphilip]

Your voice!!

[@Puhazhenthi]

❤

[@yash3842]

this is quite sad

[@dishaghatak3732]

i love you

[@muhnnd2168]

omg

[@kevinloones5395]