Mean and variance of Binomial Distribution - A simple proof

[@md.mahedihassanlemon954]

Clear interpretation 😇...Take love❣️❣️ from Bangladesh 🇧🇩🇧🇩🇧🇩

[@JEE-nf1cv]

Clear explanation thank you very much

[@beenarai5273]

Easy and best way to teach thank you so much sir 😊

[@DrHarishGarg]

So nice of you.... Thanks

[@liwen9244]

Hi sir, I just wanna ask when we prove Var(X), why cannot we directly use sum of x^2 *p -{E(X)}^2?But we need to write X^2 in X(X-1) form? Thx !❤❤

[@kuldeepkonwar2195]

Derivation becomes difficult other way.

[@user-ov7qg2wt6p]

In your previous video about Binomial distribution, for discrete it was probability density function and here you are mentioning about pmf. I m confused with pdf and pmf

[@DrHarishGarg]

No problem its name only. ... In general, pmf is used for discrete distribution while pdf for continuous one...

[@risahabhbeast7370]

Sir why did the domain change from 0 to 1 when we cancelled out x 1:36

[@endoumamoru3835]

If you put 0 in denominator, you will get (-1)!

[@DrHarishGarg]

When we cancel x it means x=0 exclude from the domain , thats why x change from 0 to 1.... Similarly for variance, we cancel x(x-1) thus x change from 0 to 2... Hope it clear.

[@Dupamine]

what does it even mean for something to be 'expected value of 5 or 6'?

[@DrHarishGarg]

Probability of 5or 6 is 1/6+1/6= 1/3.. Based on number of dice thrown, you can find the expected value as n*(1/3) =n/3

[@Dupamine]

@@DrHarishGarg Thank you Dr. harish . me and my friend watch your videos everyday. I understood the math behind this in the video but i am confused on what does 'expected value' conceptually mean in the case of dice. Usually it means the 'mean' but 'mean' makes less CONCEPTUAL sense when thinking of throwing dices.

[@misstopper1]

Thank you sir

[@tavleensasan2408]

Sir why E(X(X-1))=x.(x-1). P(x) why not E(X(X-1))=x(x-1).P(x(x-1)) in Variance derivation.

[@AniketGupta-gn2we]

Thank u very much

[@poonambajaj17]

In last example the mean(0.4) is not greater than variance(1.6) which is the resultant of relation between mean and variance of binomial distribution. Does it mean that the distribution or that example does not belong to binomial?

[@DrHarishGarg]

Yes, when mean < variance for a random variable X then it means that X does not follow Binomial distribution.,

[@shivanikumari6778]

Thanku sir 😊

[@berealistic4658]

Plzzz let me know theirs proofs do come in exams????????

[@DrHarishGarg]

Yes

[@harsh15ish]

machaya boss

[@MuhammadmustaphaZanna-ov8cw]

Sir please

[@shaik.......mini....3187]

Cool

[@socialmedia3167]

how q come? 2/3

[@endoumamoru3835]

q = 1 - p So, 1-(1/3 )= 2/3

[@MdZiyaurrahman_123]

P kha se aa gya

[@vinitagnyanasuntharam1736]

Thanks sir