Computing expected value in a game of chance
Every outcome gets weighted by how often it happens. The number that comes out is what one play is worth on average, and its sign answers the second part.
A short walkthrough explaining what you need to know and how to solve this question type lands here once it's recorded.
ALEKS randomizes the numbers each attempt, but the question shape stays the same. Here are three example versions you might see.
A fair six-sided die. You win $5 on a 1 and lose $0.50 on any of 2, 3, 4, 5 or 6.
What is the expected value? Round to the nearest cent.
A fair six-sided die. You win $2 on a 1 and $2 on a 2, and lose $1 on any of 3, 4, 5 or 6.
What is the expected value? Round to the nearest cent.
A fair six-sided die. You win $6 on a 1 and lose $1 on any of 2, 3, 4, 5 or 6.
What is the expected value? Round to the nearest cent.
Nadia is playing a game of chance in which she rolls a number cube with sides numbered from 1 to 6. The cube is fair, so a side is rolled at random.
The game is this: Nadia rolls the number cube once. She wins $3 if a 1 is rolled and $1 if a 2 is rolled. She loses $0.40 if a 3, 4, 5 or 6 is rolled.
(a) Find the expected value of playing the game.
(b) What can Nadia expect in the long run, after playing the game many times?
How many outcomes carry a loss?
The winnings side
The losses side
(a) The expected value
(b) What does that mean?
The sign is the answer to part (b)
+$0.40 per roll, so Nadia gains, and the amount she gains is the expected value itself. Part (b) needs no new calculation.
Note this game favours the player, which is unusual. Real games of chance are built with a negative expected value for whoever is playing, and that difference is the whole business model of a casino. ALEKS gives you both kinds, so read the sign rather than assuming.
And “expect to gain $0.40” never happens on any single roll — she wins $3, wins $1, or loses $0.40. It is the long-run average, which is exactly what “after playing many times” is pointing at.