could you make videos on this distributions Geometric Distribution Hypergeometric Distribution Negative Binomial Distribution Continuous Probability Distributions Uniform Distribution Exponential Distribution Laplace / double-sided exponential Cauchy Distribution Gamma Distribution Rayleigh Distribution Beta Distribution
What if I had example: First day there is 3 students asking question, second day there were 5 students asking question. Do i take lambda to be 4 (as average) ?
Nice video! By the way, I tried to calculate the probability of a fly lighting 8 times in 20 seconds. I didn't know exactly how to do it so instead of lambda = 3 (3 lights/10 sec), I used lambda = 6 (6 lights/20 sec), which gives us a probability of 25.6%. Can anyone help me? Is it correct?
Well, if you plug those values, λ=6 and y=8, you should get 10.32% as the chance for getting exactly 8 times or am I wrong? I checked with an online poisson calculator and it seems like 25.6% is the chance of getting 8 or more times in 20 seconds? What exact formula did you use? (All that is of course, assuming we can just scale 3/10 up to 6/20 which is an assumption I'm not sure is OK. I mean consider if we asked about the odds of getting 4 times in 10 seconds, where 3/10 was the expected value? We get around 16% so I'm not sure we can scale things up and down that way...)
@@plasticflower Hi. Thanks for the reply (I don't remember which formula I used). By the way, are you a mathematician, a statistician or something like that? You seem to have some knowledge in the area, and I just happen to be struggling with another stathistical problem. Could you give me a brief help? I can explain it to you in detail in some of your videos' comment.
@@jooao_guerra Hey, no I'm just taking a course on statistics at the moment, so I don't really have any deeper knowledge. But if there's another problem you could just post it here and maybe I can give you an idea or another angle? No promises though :P
When given a rate, you scale it up to the desired unit of interest (in your case 20 seconds). Lambda is the expected value, so in a 20 second interval you would expect to see 6 occurences, therefore λ = 6. Then, Pr(X=8) = 0.103258. Source: en.wikipedia.org/wiki/Poisson_distribution#Probability_mass_function
I know I’m a stickler guys, but any math person is going insane right now. I have to say it. It isn’t Yuler’s number. It’s Oiler’s number. Euler->Oiler. 🤬
how would you do this Say you started a TH-cam channel about a year ago. You’ve done quite well so far and have collected some data. You want to know the probability of at least x visitors to your channel given some time period. The obvious choice in distributions is the Poisson distribution which depends only on one parameter, λ, which is the average number of occurrences per interval. We want to estimate this parameter using Maximum Likelihood Estimation. Simulate 100 visits to your youtube channel, assuming that they will a Poisson distribution with a mean of 10 visits per minute. Plot the arrival time vs visitor index.
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Wish you explained how the formula came about but nonetheless thank you for the visuals and clear explanation
The croissant distribution
Hahahaha
HAHAHAHAHA
lol
I can't focus anymore
this comment finally made it clear to me how to pronounce poisson properly.
Clear, simple and concise. Brilliant explanation. Very useful!!
Glad it was helpful!
5 minutes and i had it all...Thanks 365 Data Science.!!!
Thank you so much! Such clear, coherently and simple explanation!
So underrated channel
tanks a lot. I understand poisson concept
completely
Very well explained. These statistical methods' formulae take time to understand but this video makes them quite easier to understand.
Clear and Concise
your videos are interesting ! i like them ! its one of the best that i see
thanks for explanation
Very helpful, I like the clarity
What's the solution to the firefly problem? Is it .8% probability?
Thank you Sir, the video was good
We need to know where the equations come from.
Good video, cleared up a lot for me. However still lost on those formula's
could you make videos on this distributions
Geometric Distribution
Hypergeometric Distribution
Negative Binomial Distribution
Continuous Probability Distributions
Uniform Distribution
Exponential Distribution
Laplace / double-sided exponential
Cauchy Distribution
Gamma Distribution
Rayleigh Distribution
Beta Distribution
are you gonna finish that (french accent) poisson?
Thank you man
thank you sir
What if I had example: First day there is 3 students asking question, second day there were 5 students asking question. Do i take lambda to be 4 (as average) ?
Is there a reason why you uploaded 2 Poisson Dist video in your playlist? Or is Exponential Dist missing?
IT'S PRONOUNCED EULER
THANKS MY FRIEND😼
thank you
Can you please make the Probability Mass function and Probability density function videos.
So useful! Thank you.
oh my god!!...you really rock!..loved this
useful video.. subscribed.
aren't ya the same guy, who advertises for Simplilearn!?!? btw the content is very lucrative.
Very well put together
Brilliant!
Helpful ✌✌🙏
OILER
It's pronounced "oiler," not "you-ler."
That's my only complaint.
hahaha... I almost missed it
Very useful 😃
thank you!
Nice video!
By the way, I tried to calculate the probability of a fly lighting 8 times in 20 seconds.
I didn't know exactly how to do it so instead of lambda = 3 (3 lights/10 sec), I used lambda = 6 (6 lights/20 sec), which gives us a probability of 25.6%.
Can anyone help me? Is it correct?
Well, if you plug those values, λ=6 and y=8, you should get 10.32% as the chance for getting exactly 8 times or am I wrong? I checked with an online poisson calculator and it seems like 25.6% is the chance of getting 8 or more times in 20 seconds? What exact formula did you use?
(All that is of course, assuming we can just scale 3/10 up to 6/20 which is an assumption I'm not sure is OK. I mean consider if we asked about the odds of getting 4 times in 10 seconds, where 3/10 was the expected value? We get around 16% so I'm not sure we can scale things up and down that way...)
@@plasticflower Hi. Thanks for the reply (I don't remember which formula I used). By the way, are you a mathematician, a statistician or something like that? You seem to have some knowledge in the area, and I just happen to be struggling with another stathistical problem. Could you give me a brief help? I can explain it to you in detail in some of your videos' comment.
@@jooao_guerra Hey, no I'm just taking a course on statistics at the moment, so I don't really have any deeper knowledge. But if there's another problem you could just post it here and maybe I can give you an idea or another angle? No promises though :P
When given a rate, you scale it up to the desired unit of interest (in your case 20 seconds). Lambda is the expected value, so in a 20 second interval you would expect to see 6 occurences, therefore λ = 6. Then, Pr(X=8) = 0.103258.
Source: en.wikipedia.org/wiki/Poisson_distribution#Probability_mass_function
Le Poisson, Le Poisson! How I love Le Poisson, how I love little fishes don’t yoooooouuu ???
I know I’m a stickler guys, but any math person is going insane right now. I have to say it.
It isn’t Yuler’s number. It’s Oiler’s number. Euler->Oiler. 🤬
Euler is pronounced oy-ler not yu-ler.
Thank you.
AMEN DUDE
Now is right :)
how would you do this
Say you started a TH-cam channel about a year ago. You’ve done quite well so far and have collected some data. You want to know the probability of at least x visitors to your channel given some time period. The obvious choice in distributions is the Poisson distribution which depends only on one parameter, λ, which is the average number of occurrences per interval. We want to estimate this parameter using Maximum Likelihood Estimation.
Simulate 100 visits to your youtube channel, assuming that they will a Poisson distribution with a mean of 10 visits per minute. Plot the arrival time vs visitor index.
Good stuff, but the pronunciation of 'Euler' is very wrong...
The only thing that you didn't nail is pronouncing Euler. It's pronouned as "oiler" not U-ler. But overall, I like the content.
Is anyone else here after starting Gravity's Rainbow?
Great
i feel this video ended a bit early.
Usefullll !!!!
nice
What did you just say???
Where transition
*translation
*Euler* is pronounced *Oi-ler* not *You-ler.* Great explanation otherwise
👍
Where did the formula came from?
Oh is this an engineering tutorial?
Sorry for asking proof but please
why use lamada and what mean
I've got some videos on the Poisson distribution and its derivation, in case you're interested.
pronounces poisson correctly, can’t pronounce euler correctly
half-backed explanation, not impressed at all