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AI SL · 13.2

Probability Distributions

13.2.3

Fair games and further distributions

13.2.3

Fair games and further distributions

Target: I can decide whether a game is fair by finding the expected gain. (+5 more)

By the end of this section

Key points

Fair games

  • A game is fair when the expected gain for each player is zero.
  • Expected gain = E(payout) − stake. Find the expected payout from a distribution, then take off what the player pays to play.
  • Expected gain above 0: the game favours the player. Below 0: it favours the organiser. Say who, and by how much per game.
  • To find an unknown stake or prize, write expected gain = 0 and solve. Money paid out is negative: in a game where a loss is −n, the equation is (chance of win) × win − (chance of loss) × n = 0.

Distributions from outcomes and formulae

  • Sum of two dice: draw the table of all equally likely outcomes, count how many give each total, and divide by the number of outcomes.
  • Several tosses: a tree diagram lists every route. Add the routes that give the same count of heads.
  • A formula distribution is a table in disguise: evaluate it at each value, check that it adds to 1, then use E(X) = Σ x P(X = x).
  • Without replacement: the second draw is out of one fewer item.

Unknown constants

  • One unknown k or c: write the sum of probabilities = 1 and solve.
  • Two unknown probabilities a and b need two equations: the probabilities add to 1, and E(X) equals the value given. Solve the pair together (the equation solver on your calculator is quick).
  • Check your answers: a and b must both be between 0 and 1.
  • Conditional probability inside a formula distribution: divide by the probability of the condition.

Explore: a probability distribution table

Type the values X can take and the probability of each. Leave one probability empty and it is found for you.

x
P(X = x)
Total of the probabilities
Expected value, E(X)

Type a table to see its bars and its expected value.

  1. The marker under the axis is E(X). Change one probability at a time. Which way does the marker move, and why?
  2. Can E(X) be a value that X never takes? Try the fair die.
  3. In the game, change the prize so that the game is fair.

Worked examples

Problems like the ones in class. Pick one, try it, then open the working.
Is the game fair?

A game costs $5 to play. You roll a fair eight-sided die. If it shows 8 you win $20. If it shows 5, 6 or 7 you win $6. Otherwise you win nothing. Is the game fair?

Score85, 6 or 71 to 4Win ($)2060Probability1/83/84/8
Working
  1. Expected payout

    \(E(\text{win})=20\times\frac{1}{8}+6\times\frac{3}{8}+0\times\frac{1}{2}=4.75\)

    Each prize times its probability.

  2. Expected gain

    \(\text{gain}=4.75-5=-0.25\)

    Subtract the stake. A fair game has expected gain 0.

  3. Conclude

    Expected gain = −0.25 dollars, not 0

    Not fair. On average the player loses 25 cents a game, so it favours the organiser.

Video walkthrough coming
Finding the stake that makes it fair

Kim draws one card at random from a standard pack of 52. If it is a picture card (jack, queen or king) Kim wins $9. Otherwise Kim pays $n. Find the value of n that makes the game fair.

Working
  1. Probabilities

    \(P(\text{picture card})=\frac{12}{52},\quad P(\text{other})=\frac{40}{52}\)

    There are 3 × 4 = 12 picture cards.

  2. Expected gain = 0

    \(\frac{12}{52}\times9-\frac{40}{52}\times n=0\)

    A loss of $n counts as −n.

  3. Solve

    \(108=40n\Rightarrow n=2.7\)

    Multiply through by 52, then divide by 40. The player pays $2.70 on losing.

Video walkthrough coming
Picture cards in a hand of two

Two cards are dealt from a standard pack of 52 without replacement. X is the number of picture cards (jack, queen, king). Find the probability distribution of X and E(X).

Working
  1. Probabilities

    \(P(0)=\frac{40}{52}\times\frac{39}{51}=\frac{10}{17},\ P(1)=2\times\frac{12}{52}\times\frac{40}{51}=\frac{80}{221},\ P(2)=\frac{12}{52}\times\frac{11}{51}=\frac{11}{221}\)

    The second card is out of 51.

  2. x012P(X = x)10/1780/22111/221
    Table

    \(\frac{10}{17}+\frac{80}{221}+\frac{11}{221}=1\)

    The total is 1.

  3. E(X)

    \(E(X)=0\times\frac{10}{17}+1\times\frac{80}{221}+2\times\frac{11}{221}=\frac{6}{13}=0.462\)

    Check: 2 cards, and 12 of 52 are picture cards: 2 × 12/52.

Video walkthrough coming
The larger of two spinners

Two fair spinners, each numbered 1 to 5, are spun together. Y is the larger of the two scores (Y is that score if both are the same). Find the probability distribution of Y and E(Y).

Working
  1. max12345112345222345333345444445555555
    All the outcomes

    25 equally likely outcomes. Each cell shows the larger score.

    Rows are the first spinner, columns the second.

  2. y12345P(Y = y)1/253/251/57/259/25
    Count

    Number of cells for each value: Y = 1: 1, Y = 2: 3, Y = 3: 5, Y = 4: 7, Y = 5: 9, each out of 25.

    The larger score is more likely to be a high value, so the table is not even.

  3. E(Y)

    \(E(Y)=1\times\frac{1}{25}+2\times\frac{3}{25}+3\times\frac{1}{5}+4\times\frac{7}{25}+5\times\frac{9}{25}=\frac{19}{5}=3.8\)

    Check: more than the mean of one spinner, which is 3.

Video walkthrough coming
A formula with an unknown k

A discrete random variable X has \(P(X=x)=k(2x+1)\) for x = 0, 1, 2, 3. (a) Find k. (b) Find P(X ≥ 2). (c) Find P(X = 3 | X ≥ 1). (d) Find E(X).

Working
  1. Values and k

    \(k(1)+k(3)+k(5)+k(7)=16k=1\Rightarrow k=\frac{1}{16}\)

    Put x = 0, 1, 2, 3 into 2x + 1, add, and set the total to 1.

  2. x0123P(X = x)1/163/165/167/16
    Table

    P(X = x) = 1/16, 3/16, 5/16, 7/16

    Evaluate the formula at each x.

  3. P(X ≥ 2)

    \(\frac{5}{16}+\frac{7}{16}=\frac{3}{4}\)

    Add the last two.

  4. Conditional

    \(P(X=3\mid X\ge1)=\frac{\frac{7}{16}}{\frac{15}{16}}=\frac{7}{15}=0.467\)

    X ≥ 1 leaves x = 1, 2, 3. Their total, 15/16, is the denominator.

  5. E(X)

    \(E(X)=0\times\frac{1}{16}+1\times\frac{3}{16}+2\times\frac{5}{16}+3\times\frac{7}{16}=\frac{17}{8}=2.125\)

    Multiply each x by its probability and add.

Video walkthrough coming
Two unknown probabilities

The table shows the probability distribution of X. Given that E(X) = 2.85, find a and b.

x1234P(X = x)0.1a0.35b
Working
  1. Sum to 1

    \(0.1+a+0.35+b=1\Rightarrow a+b=0.55\)

    First equation.

  2. Use E(X)

    \(1(0.1)+2a+3(0.35)+4b=2.85\Rightarrow 2a+4b=1.7\)

    Second equation. Multiply each x by its probability and set the total equal to 2.85.

  3. Solve the pair

    a + b = 0.55 and 2a + 4b = 1.7: a = 0.25, b = 0.3

    Solve with the equation solver on the calculator, or by substitution. Both values are between 0 and 1.

Video walkthrough coming