Check the following link .
https://www.stat.duke.edu/courses/Sp...ec/s05wk07.pdf
see page 6
"Almost sure convergence" always implies "convergence in probability", but the converse is NOT true.
Thus, there exists a sequence of random variables Y_n such that Y_n->0 in probability, but Y_n does not converge to 0 almost surely.
I think this is possible if the Y's are independent, but still I can't think of an concrete example. What is of example of this happening?
Any help is appreciated!
[note: also under discussion in math help forum]
Check the following link .
https://www.stat.duke.edu/courses/Sp...ec/s05wk07.pdf
see page 6
In the long run, we're all dead.
If you just need an example. Solution is not there.
See the thread below
http://www.talkstats.com/showthread.php?t=10189
I have uploaded the counter example part.
In the long run, we're all dead.
Let X_n be a sequence of independent random variables such that
P(X_n=0)=1-1/n and P(X_n=1)=1/n
Then X_n converges in probability to 0.
By Borel-Cantelli's lemma, since
∞
∑ 1/n = ∞ (diverges),
n=1
X_n does NOT converge almost surely to 0.
Borel Cantelli Lemma:
Let A1,A2,A3,... be events.
(i) if ∑P(An)<∞, then P(An io)=0
(ii) if the A's are independent, and ∑P(An)=∞, then P(An io)=1
where P(An io) stands for the probability that an infinite number of the A's occurs.
I don't understand the argument in red, why does Borel Cantelli lemma implies that X_n does NOT converge almost surely to 0? Are we using part (i) or part (ii) of Borel Cantelli lemma?
Can someone please explain this in more detail?
Thank you!![]()
By part (ii) of B-C lemma, since ∑ P(X_n=1)= ∑1/n = ∞, this implies that P(X_n=1 io)=1, but WHY does this imply that Xn does not converge almost surely to 0? I don't understand this.
Does it converge almost surely to any other value? If it does not converge almost surely to 0, then it converges almost surely to what value?
Thank you!
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