Gamma Distribution - Derivation of Mean, Variance & Moment Generating Function (MGF) (English)

[@asmitnaik07]

It is the first time that I feel proud on you when I watch this video sir...I properly understood whatever you teach you in this video... thankyou so much sir ....

[@giovanniruggiero6106]

Thank you, I was really struggling with the proof of the m.g.f of this distribution.

[@nurulhidayah185]

Thanks for the explanation, I understand
I'm from Indonesia 🙏❤️

[@happymakhanya]

Thank you, you helped me a lot

[@geraldolson7364]

Nicely done, very helpful.

[@olagokeblissman3886]

My boost I dey feel you

[@kylefang2377]

Very help, thank you!!

[@sofiarana5775]

Thank you 😊

[@emanshaheen7171]

When u prove mean how do u make dx= Bdt and there is a rule in the integration said that dx must not be interpreted as a product of d and x

[@devilock4497]

dx is just taken as 1.dx since differentiating both sides causes x to become 1. and Beta t to become Beta dt

[@karakter3]

thank you

[@ashutoshpanigrahy7326]

Thanks!

[@RahulaSamaranayake]

well explained

[@haroon2602]

I'm pretty confident this is wrong, because the expectation should be alpha/beta not alpha*beta?

[@chrisgumb8986]

You are confusing this with an alternative parameterization.
You most often see X ~ Gamma(alpha, beta)
But sometimes you see X ~ Gamma(r, lambda) where r = alpha and lambda = 1/beta

[@haroon2602]

@@chrisgumb8986 Thanks

[@tafriha786]