In a dice game where a player's payoff is whatever the die is rolled, each player can roll how many times they want. Each payoff gets added cumulatively (e.g. roll 5 and 5, then payoff = 10). The catch is that if the user rolled a six at any point in time, they get 0 (e.g. rolled 5 and 6, then payoff = 0).
Intuitively, raising n (the number of die rolls) could raise the expected payoff but also increases the probability of at least rolling one six and getting 0 as a payoff. For example if you picked a really large n, the likelihood of rolling at least 1 six and getting 0 payout is extremely likely. But going from n=1 to n=2 you get a little higher expected payoff (checked the math manually in lieu of a general formula).
Going with the weighted average approach to come up with a formula for expected value, one part of the formula must be the weighted average of getting a 0 payout, i.e. the probability of rolling at least one six out of n dice rolls equals 1−(56)n. As such, we get:
E(X)= weighted average for each payoff
E(X)= weighted average of getting 0 + the rest of the weighted average of payoffs
E(X)=(1−(56)n)0 + the rest of the weighted average of payoffs
However, I'm having trouble wrapping my head around coming up with the rest of the equation. How can I solve this problem?
Answer
If no die equals 6, the expected value for each die equals 1+2+3+4+55=3. There are n dice, so the expected value equals 3n. We thus get:
E(X)=(1−(56)n)0+(56)n3n=(56)n3n
The highest expected payout is achieved for n=5 and n=6, with E(X)≈6.028.
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