Assume a frog is hopping between two leafs each second, with probability to jump to the second leaf and to stay. Let be the probability that after N seconds the frog is in the same starting position. Compute the probability distribution of , and solve for , and .
Assumption: The probability of jumping between leaves is independent of the past.
This section requires Javascript.
You are seeing this because something didn't load right. We suggest you, (a) try
refreshing the page, (b) enabling javascript if it is disabled on your browser and,
finally, (c)
loading the
non-javascript version of this page
. We're sorry about the hassle.
We need the probability that the frog makes an even number of jumps in order to return to its original leaf.
The probability that the frog makes exactly k jumps is ( k N ) p k q N − k , where q = 1 − p . This is the k th term of the binomial expansion of ( p + q ) N :
( p + q ) N = k = 0 ∑ N ( k N ) p k q N − k = ( 0 N ) p 0 q N + ( 1 N ) p 1 q N − 1 + ( 2 N ) p 2 q N − 2 + ⋯
To get the terms for even k , we compare this to the binomial expansion of ( − p + q ) N :
( − p + q ) N = k = 0 ∑ N ( k N ) ( − 1 ) k p k q N − k = ( 0 N ) p 0 q N − ( 1 N ) p 1 q N − 1 + ( 2 N ) p 2 q N − 2 − ⋯
We can cancel out the terms with odd k simply by adding the two expansions; hence
2 p N = ( p + q ) N + ( − p + q ) N
Of course, p + q = 1 , so this simplifies to
p N = 2 1 ( 1 + ( 1 − 2 p ) N )
For the particular question, we have p 5 = 2 1 ( 1 + ( 1 − 3 2 ) 5 ) = 0 . 5 0 2 … .
Alternatively, we can set up a recursion: p 0 = 1 , and p N + 1 = ( 1 − p ) p N + p ( 1 − p N ) (we just consider the two possible positions of the frog after N jumps). This is somewhat simpler than the first approach!
As we'd expect, as N → ∞ we have p N → 2 1 .