Suppose you play a series of 100 independent games. If you win a game, you win 4 dollars. If you lose a game, you lose 4 dollars. The chances of winning each game is 1/2. Use the central limit theorem to estimate the chances that you will win more than 50 dollars.
You play a series of 100 independet games.
if you win a game, you win 4 dollars. If you lose a game, you lose 4 dollars.
The chances of winning each game is 1/2. So, the losing each game is 1/2.
So here,
P(Win) = P(Lose) = 0.50
Expected number of dollars won in a game = 4 * 1/2 - 4 * 1/2 = 0
Standard deviation of number of dollars win a single game = sqrt [(4 - 0)2 * 1/2 + (0 + 4)2 * 1/2] = 4
now for 100 games,
Expected number of dollars won in a 100 games = 100* ( 4 * 1/2 - 4 * 1/2) = 0
Standard deviation of number of dollars win a single game = sqrt (100 * 4) = 20
so here as the sample size is large we will employ central limit theorem and if x is the amount of winnings in 100 games. then,
x ~ N(0, 20)
we have to find
P(x > 50) = 1 - P(x < 50) = 1 - NORMSIDST(x < 50, 0, 20)
Z = (50 - 0)/20 = 2.5
P(x > 50) = 1 - P(z < 2.5) = 1 - 0.9938 = 0.0062
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