Understanding the Variance of a One-Dimensional Random Walk

Join the discussion
Registration is free. Ask a follow-up in this thread, or start your own.
5 replies · 15K views
grad
Messages
12
Reaction score
0
Hi,

I know that the expectation E(Sn) for a one-dimensional simple random walk is zero. But what about the variance?

I read in http://en.wikipedia.org/wiki/Random_walk#One-dimensional_random_walk" that the variance should be E(Sn2) = n.

Why is that? Can anyone prove it?

Thank you very much!
 
Last edited by a moderator:
Physics news on Phys.org
Just write down the definition of [itex]S_n[/itex] and you will be able to answer your question yourself.
 
Var(Sn) = E(Sn2) = E(Z12 + Z22 + Z32 + ... + Zn2) =* E(Z12) + E(Z22) + ... + E(Zn2) = 1 + 1 + ... + 1 (n times) = n

*variables are independent and uncorrelated

Is this correct then?
 
This is almost correct. [itex]S_n[/itex] is defined to be [itex]Z_1+\ldots +Z_n[/itex], where the [itex]Z_i[/itex] are independent (or at least uncorrelated) with mean zero and variance one. It follows that
[tex] S_n^2 = \sum_{i,j=1}^n{Z_i Z_j}[/tex]
and not, as you wrote,
[tex] S_n^2 = \sum_{i=1}^n{Z_i^2}[/tex]

However, using independence of the [itex]Z_i[/itex] you can still do a similar computation to prove [tex]\mathbb{E}\left[S_n^2\right]=n[/tex].
 
You're welcome:smile: