
Use Central Limit Theorem Please!
for single game:
| x | P(x) | xP(x) | x2P(x) |
| 1 | 0.500 | 0.500 | 0.500 |
| -1 | 0.500 | -0.500 | 0.500 |
| total | 0.000 | 1.000 | |
| E(x) =μ= | ΣxP(x) = | 0.0000 | |
| E(x2) = | Σx2P(x) = | 1.0000 | |
| Var(x)=σ2 = | E(x2)-(E(x))2= | 1.000 | |
| std deviation= | σ= √σ2 = | 1.0000 |
hence for 1000 game; expected gain/loss =0*1000 =0
and std deviaiton =1*sqrt(1000)=31.623
| for normal distribution z score =(X-μ)/σx | |
| here mean= μ= | 0 |
| std deviation =σ= | 31.623 |
P(your fortune is at least 10 dollars):
| probability = | P(X>10) | = | P(Z>0.32)= | 1-P(Z<0.32)= | 1-0.6255= | 0.3745 |
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