Mean and variance of Bernoulli distribution example | Probability and Statistics | Khan Academy
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- Опубликовано: 9 сен 2024
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Mean and Variance of Bernoulli Distribution Example
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This man so powerful he can survey the entire population.
this is a wonderful comment
I am amazed that every time on your videos I find that little piece of information that makes all the pieces connect together. What a beautiful and simple way to define it. Good presentation must be a gift given by God! and often times is rare to find.
Variance
= Probability-weighted sum of squared-distances from the mean
= Expected value of squared-distances from the mean
I just finish wrote them down to think about them and I find your comment
You make finding the variance very complicated, the right way is just
0.6 * 0.4 = 0.24 i.e variance = p * q
Success * failure = variance
He explains that in next video.
Lmao when I saw that calculator
Thank you sir
Sir, if x,y and z are bernaulli varaites and xy are independent, yz are independent and zx are independent then show that P(xyz=0)>=3/4.May you give the idea behind this?
*Who is watching in 2020?*
2021 here
2022
2023
How did we get the mean μ = .6 ?
this guy has the same voice as the narrator on the tv series "How I met your Mother"
no he doesnt
noooo.not even close
@rahat5810 it's the variance when it is squared
why didn't we divide by N? both for the mean and for the SD?
you would have to divide by N if you were dealing with frequencies, but here you're dealing with probabilities
He uses expected value, that is the same thing as dividing by N. Watch his videos about it on this playlist
At 6.26 both standard deviation and variance is said to be 0.24. Is that a slip of tongue?
Khan do fluid mechanics? Please?
Keep on going, Sal.
please explain this question----X ~ B(n, p). The maximum value of Var (X) is
1 when 100% are successes.
In this one p=P(X=1)=0.6. Obviously if you choose p=P(X=1)=0.4 results will change but p expresses the probability that I don't like the president
Hey there,
what is the difference between Binomial and Bernoulli distribution?
Thanks in advance.
they are the same, binomial distribution is how you can show a probability mass of a bernouilli process
@@mehdihachimi9624 Thank you
Bernoulli distribution deals with the outcome of the single trial of the event, whereas Binomial one deals with the outcome of the multiple trials of the single event. Bernoulli is used when the outcome of an event is required for only one time, whereas the Binomial is used when the outcome of an event is required multiple times.
@@Some-ij6ky Thanks for your input.
wont things change if instead of making 40%=0 you made it equal 1 and 60%=2.????
Yes, this confused me at first too. The selection of f as 1 isn't arbitrary because we're considering favorability a "successful" trial. The assignment of 1 or 0 to either outcome depends on what you define as a successful trial
yes
point point point
Max Tagmark .... Are you there?
what happened to the degrees of freedom ? O.o
this is what I am asking myself aswell. and as I see the question has been unanswered for five years, I guess I have no hope for getting an answer before my exam
@@rogersyversen3633 its 7 years now
wdym u only have yes or no (1 or 0), it makes sense...u can add more independent variables in non-binomial case...or did I get this wrong?
is there any app for the calculator like he used ?
I would also like to know
Let's say we are able to go out...
I ponder this frequently
why is the mean 0.6? is it not 0.5???????????
its not. as per bernoulli's mean formula, mean=0*(1-p)+p*1.. its more than a year greater possibility that you already learnt this one , lol.
Because the data is skewed to the right. Mean is sensitive to that
Why does he change color for every letter/number he writes?
si its makes it easier for you to read
if 0 and 1 are arbitrary what if I take 100 and 1000 instead of 0 and 1?
that's not bernoulli, think of 0 and 1 like booleans or True and False...
@@mehdihachimi9624 yes correrct
I also got confused on that part, but the main idea is that the question is "what is the expected favorability?".
It's easier with coins, say you have 60% Heads and 40% tails. If the question was "what is the expected chance for a head?", you would graph P(no heads or 0Heads)=0.4 and P(a head or 1Heads)=0.6, which is basically what the graph showed.
variance is wrong it will be p(1-p) which is equal to 0.24. still thanx ur awesome
That is what he wrote, what are you talking about? He wrote variance is 0.24!
God I just wish someone would ask him to not repeat every word he says every word he says.
LOOOOL
Nope, it helps to understand the important notions
😂😂😂
variance calculation may be wrong...0-0.6 is actually 0.4 and not 0.6..nonetheless good video.thank you
0 - 0.6 = 0.4? cmon man