Its actually unfair the amount of value you give in these videos. It took me 10 minutes (7 minutes + replaying some parts) to understand a topic, something my professor could never do. And even if I relied on the good old textbook, I still wouldn't understand it this quickly. God bless
You are amzing! There are two brilliant parts. The first one is 1:15 when you differentiate between binomial and negative binomial distributions. The second one when you show the distribution in a graph at the end of the video. VERY WELL DONE!!
I could not understand this from my stats textbook even after trying for 30 whole mins(even the formula didnt make much sense to me without proper explanation) and it only took me 7 mins to understand it so well here.. thanks for this honestly.
This is great..I went through several Edx ,they were so mathematical that we get lost.Your explanation helps to fundamentally build whats exactly needed for this topic..
I am watching this in 2022 and this video is still the most accurate and the best video on Negative binomial distribution or any topic u pick of statistics and probability. THANKS A LOT PROFESSOR! #luv_from_INDIA
Superb stuff. Clean visuals, intuitive explanation, and helpful prods about potential misunderstandings. Some Ivy League professors struggle for hours to teach these concepts in a useful, unpretentious way, and then you come along and make it so easy that it can be digested in 5 minutes. For embarrassing some overpaid hacks of Harvard, you deserve a proposal of marriage or something.
You could even look at this way. For example, in the sum on telephone calls, you could simply model the problem as a binomial with X=2 and then multiply P(X=2) by 0.09 to get the answer !! Doing this might help you get an intuitive sense of the negative binomial distribution and what it hopes to achieve. Think about it !
Great explanation; I'm working through Hogg, McKean & Craig and could not understand how they arrived at the negative binomial pmf; seeing how you did it made it clear. Oddly enough, your explanation made clear to me how the text was explaining it the same way; I just couldn't see it.
Excellent video! Explained very clearly and concisely. Thank you for taking the time to do this. I'm looking forward to watching many of your other videos, as I'm assuming it will make my future studying much easier. kudos to you for a job well done!
Oh my! I love your videos, but I was hoping to find out mean and variance of this distribution and there isn't. Thank you so much for your amazing explanation. Cheers.
Your videos are really helpful and explain every detail precisely. I recently started learning statistics. it was very hard for me to understand and the digest the statistics concepts. But then I found your channel and I am very thankful to you :). I really appreciate your efforts here.
Where can I make a donation for the great work you have done?! I have watched all of your distribution video and I want to thak you infinitely. May God bless you and your family and keep doing what you are doing cause we need guys like you!!! ;)
Because we're interested in the probability that the rth success occurs on exactly the xth trial. For this to happen, 1) the first x-1 trials must contain exactly r-1 successes and 2) the xth trial must be a success. To find the probability that in the first x trials there are r successes, where x is fixed, we'd use the binomial distribution. The probability that the rth success occurs on precisely the xth trial is less than the probability of getting r successes in x trials.
In the formula sheet my professor provided, it says that the mean for negative binomail is equal to r(1 - p) / p. How come this formula is different from the one in the video, which is simply r / p
Dear jbstatistics,In wiki i read : "number of successes in a sequence of independent and identically distributed Bernoulli trials before a specified (non-random) number of failures (denoted r) occurs" So what is r? Number of successes or failures?
My question, in the plot, why does the probability decrease if the number of calls increases? Logically the more calls I make, the higher probability I get to complete 3 surveys.. thanks
Can I apply this to Keno gambling? For example - In Caveman Keno- Initially player can pick 2-10 numbers ranging from 1-80.Then system will pick 3 numbers excluding the numbers which player has picked. Again the computer will select the 20 numbers ranging from 1-80. Depending on the number of eggs matched+ number of catches the bet is calculated.What is the probability that egg is catched? What type of probability this will follow?
Can somebody explain to me why they had to use the exact same letter in a different case. For P(X=x), X and x are not exactly the same, and the notation can be really confusing. Why couldn't they write x as a different letter like n? Was this notation really the best they could come up for this formula? Was there really no other notation that is better than this?
Hi Firas. There are a number of different ways of defining the random variable here. For example, we could define X to be the number of trials required to get the rth success (as I did in this video), or the number of failures before getting the rth success. (We could also flip it around and define the random variable to be the number of successes before getting a certain number of failures). It looks like your text has defined the random variable to be the number of failures before getting the rth success.
Sir, can you please explain why is it called a negative binomial distribution....My teacher in my viva asked this ques and on Wikipedia, I found a very vague answer saying that its because some terms are easier to write as negative number hence the negative
Thanks for the kind words! I very much hope you find my videos helpful. Cheers.
Its actually unfair the amount of value you give in these videos. It took me 10 minutes (7 minutes + replaying some parts) to understand a topic, something my professor could never do. And even if I relied on the good old textbook, I still wouldn't understand it this quickly. God bless
I'm glad to be of help!
These videos will go down in history as one of THE best
GOATED stuff right there fr fr no cap ong. the explanation do be bussin respectfully
Thanks!
You are amzing!
There are two brilliant parts. The first one is 1:15 when you differentiate between binomial and negative binomial distributions. The second one when you show the distribution in a graph at the end of the video. VERY WELL DONE!!
+Ghada Elsayed Thanks!
I agree with the graph, very helpful to see the distribution graphically!
I also agree. That was a perfect video
@@jbstatistics this cleared up so many things for me, i am forever grateful ToT
You Sir, are a legend.
Thanks!
Sigma JB😅
Thanks Mohammed. I'm always glad to hear when people find my work useful. I'll definitely be keeping it up and adding videos. All the best.
This discrete probability is one of the least talked-about functions. You spell it out great! Thank you.
I could not understand this from my stats textbook even after trying for 30 whole mins(even the formula didnt make much sense to me without proper explanation) and it only took me 7 mins to understand it so well here.. thanks for this honestly.
I cannot thank you enough for your videos. They are so helpful and are getting me through my stats class. Very clear and concise!
I have never understood this concept until watching your video. Super clear and helpful!
I'm glad to be of help!
You've done what my professor and book couldn't. That is to make me understand this in 7mins!! xD
+BOB BOB You're welcome!
man, i had to drop prob and stat class because i couldn't grasp the concept and here we are, crystal clear. Thank you
This is great..I went through several Edx ,they were so mathematical that we get lost.Your explanation helps to fundamentally build whats exactly needed for this topic..
1:00 "And if we're interested in the number of trials to get the... TWELFFTH success.."
Lmao hidden gem
natedsamuelson LOL what was that lmaooo
I nearly spit my coffee out when that happened hahahaha
LMAO
the best video for this topic !!!! the formula in my book was very complex and here I found the simplest method to solve the question. thanks a lot
You're very welcome!
Your videos are at the rescue when strucked middle of any maths topic. 🙏 Hats off to your hard work.
I am watching this in 2022 and this video is still the most accurate and the best video on Negative binomial distribution or any topic u pick of statistics and probability. THANKS A LOT PROFESSOR! #luv_from_INDIA
The difference a good instructor makes. So glad I go to college while having access to UA-cam. I feel bad for everyone who didn't.
I'm glad to be of help!
Watching the video after 10 years of upload and still getting benefit from this. Thanks for the clear explanation.
It's still good stuff :) Glad to be of help!
i love how u mix with humor to keep us focused
Very well explained, all my confusion is gone. Thank you very much!
You are welcome, and I'm glad to be of help. I hope your semester went well.
You're welcome, and thanks! Different strokes for different folks -- I'm sure some of my students leave the same comment on other youtube channels :)
You're welcome! I try hard to be concise in my videos, while still getting the important points across. (So I like to hear that word!)
thanks a lot man, you saved me..you can't understand how useful your lessons are....keep goin!!!!
Superb stuff. Clean visuals, intuitive explanation, and helpful prods about potential misunderstandings. Some Ivy League professors struggle for hours to teach these concepts in a useful, unpretentious way, and then you come along and make it so easy that it can be digested in 5 minutes. For embarrassing some overpaid hacks of Harvard, you deserve a proposal of marriage or something.
Seriously, I have understood the concept of distribution after watching this video.And those graph is so helpful. Thank you so much sir....
I'm glad I could help you understand!
Thanks for the compliment! I'm glad I helped you see it. Cheers.
You could even look at this way. For example, in the sum on telephone calls, you could simply model the problem as a binomial with X=2 and then multiply P(X=2) by 0.09 to get the answer !! Doing this might help you get an intuitive sense of the negative binomial distribution and what it hopes to achieve. Think about it !
After 2 days of trying to figure out all the differences I finally understand. Thank you soooooooo much
Great stand-alone video to learn about the negative binomial distribution.
if i saw your video few months ago my grade would have been a lot better. Thank you so much.
Great video, my book explains this way to fast and this really helped. I can see myself re watching these vids a lot before my module is over.
It has been useful for me after 8 years. Thank you sir.
You are very welcome! I built them to last the test of time :)
The way you teach is frekkin AWESOME!!!
Thanks!
Well explained. organized presentation, no waste of time. A natural teacher. Must be a well-organized person in life. Thank you.
My semester is great thanks to u pls do keep up we need more selfless people like u
An excellent explanation of this distribution. Very clear and easy to follow.
Your lecture is clearer than what my professor put on board. Thank you .
Yes sir, I found ur video very useful for my students in University of Indonesia, Jakarta
@ 6:19 How would you multiply the (10-1|3-1)*0.09^3?
the numbers in the parentheses is a combinatoric notation
@@DaffaAlifPratama THANK YOU SO MUCH
Great explanation; I'm working through Hogg, McKean & Craig and could not understand how they arrived at the negative binomial pmf; seeing how you did it made it clear. Oddly enough, your explanation made clear to me how the text was explaining it the same way; I just couldn't see it.
Excellent video! Explained very clearly and concisely. Thank you for taking the time to do this. I'm looking forward to watching many of your other videos, as I'm assuming it will make my future studying much easier. kudos to you for a job well done!
You are very welcome. And thanks for the compliment!
my prof skipped this in probability theory, thank you so much u explained it so well
Oh my! I love your videos, but I was hoping to find out mean and variance of this distribution and there isn't. Thank you so much for your amazing explanation. Cheers.
I give the mean and variance at 4:19, just after discussing the pmf.
this is the video. the one ive been looking for
Thank you very much, your videos are excellent! I learn the concepts much easier by you than by my professor!
Wow, you make it look simple! You have a gift! Awesome.
your videos are divine for stats undergrads
Excellent and clear step-by-step explanation. jbstatistics, Sir, you are amazing.
Thanks for the compliment!
This is such a helpful video for building intuition about these distributions.
exceptional teaching style
If Khan academy is the Walmart of learning videos, then you are the store that delivers the groceries straight to me! lol
Well, I do aspire to be better than the "Walmart of learning videos"!
Khan academy does not cover quantity... it is slow.... this is fast .... good .... straight to the point
This explanation is sooo clear and precise thank you sir you are amazing
You make this looks like Kindergarten Math, much appreciated.
Your videos are really helpful and explain every detail precisely. I recently started learning statistics. it was very hard for me to understand and the digest the statistics concepts. But then I found your channel and I am very thankful to you :). I really appreciate your efforts here.
Where can I make a donation for the great work you have done?! I have watched all of your distribution video and I want to thak you infinitely. May God bless you and your family and keep doing what you are doing cause we need guys like you!!! ;)
You're welcome! Glad to be of help!
Your explaination is so clear! Thankyou sir! It helps me a lot!
You are very welcom!
I coded the diffrence between binomial and negative binomial in my mind as, like the diffrence between period and frequency. Thanks for the videos!
thanks a bunch!!!you've made all the distributions really simple
Because we're interested in the probability that the rth success occurs on exactly the xth trial. For this to happen, 1) the first x-1 trials must contain exactly r-1 successes and 2) the xth trial must be a success.
To find the probability that in the first x trials there are r successes, where x is fixed, we'd use the binomial distribution.
The probability that the rth success occurs on precisely the xth trial is less than the probability of getting r successes in x trials.
May God give you immensely!❤
Please do videos on jointly distributed random variables. your videos are the only reason I am passing my prob class so far
Best impact I’ve ever experienced
Great explanation, you’re a legend
honestly, this helps so much. SO MUCH. Thank you SO MUCH
I might answer questions to clarify a point on a video, but I don't answer other questions or help with homework or assignments. Cheers.
Thank you sir.with the help of your teaching,l easily study the formula's sir
This video helps clarify a lot of confusions!!
I'm glad to be of help!
In the formula sheet my professor provided, it says that the mean for negative binomail is equal to r(1 - p) / p.
How come this formula is different from the one in the video, which is simply r / p
You are correct.
May I ask how did you calculate the variance of the possibility distribution?
so good man. so understandable! keep the work up! wish u success in your academic life!
I'm glad I could help, and thanks for the kind words! All the best.
This is really well explained.
Thnks justin beiber statistics..i am gonna devour your all lectures.
good good stuff, i have a quiz today so you just saved me.
Please keep uploading videos.. your videos are very helpful. Thanks...
Thanks for the explanation sir
Your videos are extremely helpful! Thank you so much!
You are welcome!
Dear jbstatistics,In wiki i read :
"number of successes in a sequence of independent and identically distributed Bernoulli trials before a specified (non-random) number of failures (denoted r) occurs"
So what is r? Number of successes or failures?
You explain so well.
thank you so much man, u have been helpful through out my semester
Thank you very much. Very clear presentation.
Very concise and informative! thanks!
My question, in the plot, why does the probability decrease if the number of calls increases? Logically the more calls I make, the higher probability I get to complete 3 surveys.. thanks
I couldn't solve for the expectation value of negative binomial distribution, is the expression for expectation value(mean here) is correct?
you saved my life. thank you
r is the number of successes, where each trial can be classified as either a success or a failure. r must be a positive whole number (1, 2, 3, ...).
how do you input the equation at 6:25 into the calculator in order to get to the answer of 0.01356?
choose(9,2) * 0.91^7 * 0.09^2 * 0.09
Can I apply this to Keno gambling? For example - In Caveman Keno- Initially player can pick 2-10 numbers ranging from 1-80.Then system will pick 3 numbers excluding the numbers which player has picked. Again the computer will select the 20 numbers ranging from 1-80. Depending on the number of eggs matched+ number of catches the bet is calculated.What is the probability that egg is catched? What type of probability this will follow?
Great lecture video! Thank you so much!
Great explanation. The video was clear in informative!
wow maths is beautiful when you really understood good
Can somebody explain to me why they had to use the exact same letter in a different case. For P(X=x), X and x are not exactly the same, and the notation can be really confusing. Why couldn't they write x as a different letter like n? Was this notation really the best they could come up for this formula? Was there really no other notation that is better than this?
Hi Sir, In my book I have the means equation as r(1-p)/p
whats the difference.
That was well explained tho thanks
Hi Firas. There are a number of different ways of defining the random variable here. For example, we could define X to be the number of trials required to get the rth success (as I did in this video), or the number of failures before getting the rth success. (We could also flip it around and define the random variable to be the number of successes before getting a certain number of failures). It looks like your text has defined the random variable to be the number of failures before getting the rth success.
Thats True
You are Great I swear.
And I think thats because the text uses a combination of ( x+r-1 / r-1 ) p^r (1-p)^x
if we went through the question consideringg X as failure do we have to get the same answer we got in this problem ?
Sir, can you please explain why is it called a negative binomial distribution....My teacher in my viva asked this ques and on Wikipedia, I found a very vague answer saying that its because some terms are easier to write as negative number hence the negative
i can't thank you enough god bless you❤
Very helpful lecture, just wondering what to do when r successes is a fraction say r=0.2 ? Thanks.
I was scratching my head for hours on this distribution, then i found your channel xD