Efficiency || Efficient Estimators || Properties of Estimators || Theory of Estimation (In Hindi)

[@himanshujha7919]

best playlist for statistics💯💯💯💯

[@JubairKalam]

Such a good explanation sir...

[@Learningweb.1365]

Amazing bro

[@GauravKumar-sh8on]

Daily video uploaded karo or 1hour ki videos bnaya karo sir

[@statslearning]

Okay boss 😅

[@noorsial1089]

Great 👍

[@k.k.kolumn]

Var(Xm) kaise calculate kiya sir?? Eska video nhi mila playlist me

[@pallabimohanty8172]

Last video check karo.Isi video ka pehle wale vdo me hai.

[@ambikaramola4600]

Sir y 3 ki place mea 9 kse hua Inka square n 7 ka b 49??

[@Harshit_joshi861]

Sir ये normal population का variance ही sigma^2/n होगा या सभी distributions का??

[@statslearning]

Normal distribution ka hi hoga.

[@yeshanikavindya6785]

Thank u sir ❤

[@GauravKumar-sh8on]

Sir aaj ki video kab uploaded karoge please kar do sir

[@statslearning]

Abhi thoda busy hun dear.. sunday ka baad regular upload karunga videos.. exam kab hain?

[@GauravKumar-sh8on]

@@statslearning ok sir

[@aishwaryasrivastava8023]

Sir I have a doubt, you said in previous video that consistent estimators follow invariance property where as unbiased estimator don't. But here sample mean is consistent as well as unbiased so isn't it a contradiction between the above statement.

[@statslearning]

No.. it is not necessary for unbiased estimators to be invariant whereas in case of consitent estimators, these will always invariant

[@aishwaryasrivastava8023]

@@statslearning Oh okay, got it. thank you sir😊

[@renuagarwal6724]

Sir aap 1 baar to kh rhe h eta less than equal to 1 aur phir usi k cases m 3 case l liye less than, greater than and equal How is it possible

[@statslearning]

eeta should be less than one for efficient estimator.. for relative efficiency it can take less than one and more than one values.

[@GauravKumar-sh8on]

Thanks sir

[@GauravKumar-sh8on]

Sir video bnaoge aaj to please video uploaded karo

[@statslearning]

Ok boss

[@GVR7573]

Sir 7 bahar 49 kese hua?

[@statslearn]

var(aX) = a^2 Var(X); a being a constant.

[@mdanisulislam2752]

Var(ax)=a^2 var(x) Law of varience bro

[@sahilkrshah6399]

how is n=4 in variance of x bar?

[@statslearn]

var(x bar) is equal to sigma square/n so n =4. thus var(xbar) = sigma square /4.

[@sabinasultana813]

Sir yaha pe var( x bar )=sigma sq /4 kaise aya?

[@statslearning]

variance of sample mean is sigma square by n..

[@sabinasultana813]

@@statslearning sry sir but ye sigma sq /16 nhi hoga ky.....

[@statslearning]

sigma square by 16 hoga but summation ke andar 1 rahega jo 4 ho jayega so finally sigma square by 4 ayega

[@sabinasultana813]

@@statslearning ok thank you sir🙂

[@paruParu-rc1bu]

@@statslearning haha sahi hai...maths