Strong Law of Large Numbers | Almost Sure convergence | Examples

[@manavnigam2532]

"this here this and this so this becomes this" that's all he can teach. WASTE OF TIME.

[@yjchen4374]

At 23:46 I don’t understand why we can discard the 0 case?

[@SanjeevPalita]

Sir very nice explanation I am impressed excellent 😍😍😍😍😍😍❤❤

[@entertainmentzone6838]

Please provide the proof of WLLN, SLLN & CLT

[@Mandeepkumar-lu8iy]

Jab sequence s=1/2 k liye not converge then P(A)=1 how

[@soumadebpain3779]

For s = 0.5, limXn(0.5) != X(0.5), so for all s € [0,1] the P{ w: lim(Xn(w)) = X(w)} is not equal to 1 right? Then how can you conclude Xn converge almost surely to X?

[@sonugoyal8181]

It is equal to 1 at every point in between (0,1].

[@kritanshagarwal6386]

12 tk probablity kitni acchi thi...engineering ne iski bhi chod di

[@asky.ashish]

[@asky.ashish]

🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣

[@samyamidha38]

For real 😭

[@samyamidha38]

For real 😭

[@amishasharawgi7906]

Sir can u make a video on hajek reyni inequality proof

[@shrawankumarpatel2148]

🙏🙏🙏 no word for ......

[@AkshitSharma0]

Sir please can you explain the inequality at 14:52?

[@ho-jinlee2468]

Note that P(|X1| =1) = 1 P(|X2| = 1/2) =1, ..... P(|Xn| =1/n) =1. Not being probabilistic any longer. For large n, x_n epsilon) = Sum[1;1/epsilon] P(|Xn| >epsilon) + Sum[1/epsilon; inf] P(|Xn| >epsilon) = Sum[1;1/epsilon] 1 + Sum[1/epsilon; inf] 0

[@Democraps_are_narrow-minded]

U have lost me

[@AshishAshu-pb6eh]

Kch smj m nh aaya 😑😑😑

[@gamingwizard8785]

Maybe you can try teaching in Hindi?

[@AkshitSharma0]

-1

[@HoneySingh-yp7zc]

may be he must not teach