For a random walk of length [math]2m[/math], define [math]\epsilon_k[/math] to equal 1 if
[math]S_k \gt 0[/math], or if [math]S_{k-1} = 1[/math] and [math]S_k = 0[/math]. Define [math]\epsilon_k[/math] to equal -1 in all other cases. Thus, [math]\epsilon_k[/math] gives the side of the [math]t[/math]-axis that the random walk is on during the time interval [math][k-1, k][/math]. A “law of large numbers” for the sequence [math]\{\epsilon_k\}[/math] would say that for any [math]\delta \gt 0[/math], we would have
as [math]n \rightarrow \infty[/math]. Even though the [math]\epsilon[/math]'s are not independent, the above assertion certainly appears reasonable. Using Theorem, show that if [math]-1 \le x \le 1[/math], then
Given a random walk [math]W[/math] of length [math]m[/math], with summands
define the reversed random walk to be the walk [math]W^*[/math] with summands
- Show that the [math]k[/math]th partial sum [math]S^*_k[/math] satisfies the equation
[[math]] S^*_k = S_m - S_{n-k}\ , [[/math]]where [math]S_k[/math] is the [math]k[/math]th partial sum for the random walk [math]W[/math].
- Explain the geometric relationship between the graphs of a random walk and its reversal. (It is not in general true that one graph is obtained from the other by reflecting in a vertical line.)
- Use parts (a) and (b) to prove Theorem.