February 22nd, 2006, 8:18 pm
QuoteOriginally posted by: kwse_t = p(e_h + 1) + (1-p)(e_t + 1)e_h = p + (1-p)(e_t + 1)=> e_t (expected number of tosses to get 2 h from the "tail" state, which is the same as the game not having started in this case) = 1/p + 1/p^2I think of this in a slightly different way (completely equaivalent, of course): We have an expected number of flips, E. I consider the three outcomes {HH, HT, T}. Each of these outcomes either ends the game, or resturns me to my starting point where I would expect E flips again. With probability p^2 I get two heads in a row and the game ends. With probability p(1-p) I get a head and then a tail, at which point I am back to my starting point, and have an expected number E flips awaiting me to finish. Finally, with probability (1-p) I flip a tail and am back to my starting point again. Putting this together givesE = (2) p^2 + (2+E) p (1-p) + (1+E) (1-p),and solving for E gives the same result.
Last edited by
cordless on February 21st, 2006, 11:00 pm, edited 1 time in total.