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Chapter 13 · Probability

Example 21: Speaks the truth 3 times in 4: reports a six, P=38P = \frac38

ExamplesBayes' theorem · Section 13.5
The question

A man is known to speak truth 3 out of 4 times. He throws a die and reports that it is a six. Find the probability that it is actually a six.

Exam answer

Let EE⁠: the man reports that a six occurs, S1S_1⁠: six occurs, and S2S_2⁠: six does not occur.

S1S_1 and S2S_2 form a partition of the sample space (the die either shows a six or it does not).

P(S1)=16P(S_1) = \frac16 and P(S2)=56P(S_2) = \frac56

P(E∣S1)P(E|S_1) = P(he speaks the truth) =34= \frac34

P(E∣S2)P(E|S_2) = P(he does not speak the truth) =1−34=14= 1 - \frac34 = \frac14

By the theorem of total probability,

P(E)=P(S1)P(E∣S1)+P(S2)P(E∣S2)=16⋅34+56⋅14=324+524=824\begin{aligned} P(E) &= P(S_1)P(E|S_1) \\ &\quad + P(S_2)P(E|S_2) \\ &= \frac16\cdot\frac34 + \frac56\cdot\frac14 \\ &= \frac{3}{24} + \frac{5}{24} = \frac{8}{24} \end{aligned}

By Bayes' theorem,

P(S1∣E)=P(S1)P(E∣S1)P(E)=324÷824=324×248\begin{aligned} P(S_1|E) &= \frac{P(S_1)P(E|S_1)}{P(E)} \\ &= \frac{3}{24} \div \frac{8}{24} \\ &= \frac{3}{24} \times \frac{24}{8} \end{aligned}

∴\therefore The probability that it is actually a six is 38\dfrac38⁠.

Want the reason behind every step, the basics and the checks?

The one idea this problem is built on

A report of "six" can be a true report or a lie. A true report needs a six (rare, 16\frac16⁠) and the truth (34\frac34⁠). A lie needs a non-six (common, 56\frac56⁠) and a lie (14\frac14⁠). Because non-sixes are five times as common, the lies are not much rarer than the true reports, and the report is less trustworthy than "3 times out of 4" suggests. Bayes' theorem gives the exact share of true reports.

Given, to find, and the plan
Given
The man speaks the truth with probability 34\frac34⁠. He throws a die and reports a six.
To find
The probability that the die actually shows six, given his report: P(S1∣E)P(S_1|E)⁠.
Plan
(1) Name the events; check the partition. (2) Find P(Si)P(S_i) and P(E∣Si)P(E|S_i)⁠. (3) Total probability for P(E)P(E)⁠. (4) Bayes' theorem.

Basics you need

1A fair die

A six comes up with probability 16\frac16⁠, and not a six with probability 56\frac56⁠. Basics: the classical definition

2Complement

"Speaks the truth 3 out of 4 times" means he lies with probability 1−34=141 - \frac34 = \frac14⁠. Basics: rules of probability

3Theorem of total probability (Section 13.5.2)

P(E)=P(S1)P(E∣S1)+P(S2)P(E∣S2)P(E) = P(S_1)P(E|S_1) + P(S_2)P(E|S_2)⁠. Lesson: total probability and Bayes' theorem

4Bayes' theorem (Section 13.5)

P(S1∣E)=P(S1)P(E∣S1)P(E)P(S_1|E) = \frac{P(S_1)P(E|S_1)}{P(E)}⁠. Lesson: Bayes' theorem

Solution

  1. Name the events

    Let

    • EE⁠: the man reports that a six occurs;
    • S1S_1⁠: a six occurs on the die;
    • S2S_2⁠: a six does not occur.

    S1S_1 and S2S_2 are complements, so they form a partition of the sample space.

    What the die really shows is the hidden cause; his report is what we observe. We want the chance of the cause "six" given the report.
    {S1,S2}\{S_1, S_2\} is a partition. Lesson: Bayes' theorem
  2. The probabilities

    P(S1)=16,P(S2)=56.P(S_1) = \frac16, \qquad P(S_2) = \frac56. P(E∣S1)=34,P(E∣S2)=1−34=14.\begin{aligned} P(E|S_1) &= \frac34, \\ P(E|S_2) &= 1 - \frac34 = \frac14. \end{aligned}
    If a six did occur, he reports a six exactly when he tells the truth: probability 34\frac34⁠. If a six did not occur, a report of "six" is a lie. Like the book, we assume that his report is just "six" or "not six", so every lie about a non-six is the report "six" and P(E∣S2)P(E|S_2) is the whole chance of a lie, 14\frac14⁠. This is an assumption of the model: if a lie could name any of the five wrong numbers equally, P(E∣S2)P(E|S_2) would be 14×15=120\frac14 \times \frac15 = \frac{1}{20} and the answer would be 34\frac34 instead.
    P(lie)=1−P(truth)P(\text{lie}) = 1 - P(\text{truth})⁠. Basics: rules of probability
  3. The chance of the report: total probability

    By the theorem of total probability,

    P(E)=P(S1)P(E∣S1)+P(S2)P(E∣S2)=16⋅34+56⋅14=324+524=824.\begin{aligned} P(E) &= P(S_1)P(E|S_1) \\ &\quad + P(S_2)P(E|S_2) \\ &= \frac16\cdot\frac34 + \frac56\cdot\frac14 \\ &= \frac{3}{24} + \frac{5}{24} = \frac{8}{24}. \end{aligned}
    start die shows man reports multiply along the path throw S₁: six E: says six 1/6 × 3/4 = 3/24 E′: says not 1/6 × 1/4 S₂: not six E: says six 5/6 × 1/4 = 5/24 E′: says not 5/6 × 3/4 1/6 3/4 1/4 5/6 1/4 3/4
    The tree for Example 21. "Six" is reported after a real six and the truth (rose path, 324\frac{3}{24}⁠), or after another number and a lie (green path, 524\frac{5}{24}⁠). The lie path is the larger.
    The two ways of hearing "six" cannot both happen, so their probabilities add. Both products already have the denominator 24.
    Multiply along a path, add the paths. Basics: tree diagrams
  4. Actually a six, given the report: Bayes' theorem

    By Bayes' theorem,

    P(S1∣E)=P(S1)P(E∣S1)P(E)=324÷824=38.\begin{aligned} P(S_1|E) &= \frac{P(S_1)P(E|S_1)}{P(E)} \\ &= \frac{3}{24} \div \frac{8}{24} = \frac38. \end{aligned}
    The top is the true-report path, the bottom is every report of six; the 24 cancels. This is the book's 18×248=38\frac{1}{8} \times \frac{24}{8} = \frac{3}{8}⁠, written with a common denominator.
    Bayes' theorem: one path over all the paths. Lesson: Bayes' theorem
  5. What the answer means

    Before the report the chance of a six was 16≈0.17\frac16 \approx 0.17⁠; after it, 38=0.375\frac38 = 0.375⁠. The report helps, but it is still more likely (58\frac58⁠) that the die is not a six.

    A man who is right 3 times in 4 sounds reliable, but here he is reporting something rare. Five times as many throws are non-sixes, and a quarter of those turn into false reports of "six".
    P(S1∣E)+P(S2∣E)=1P(S_1|E) + P(S_2|E) = 1⁠. Lesson: Bayes' theorem
Result

The probability that the die actually shows a six is 38\frac38⁠.

(Textbook answer: 38\frac{3}{8}⁠.)

Check it with numbers

Picture 24 throws, each with a report. A six comes up about 4 times, and he truthfully reports it 3 of those times. A non-six comes up about 20 times, and he lies (reports a six) 5 of those times. So he says "six" 3+5=83 + 5 = 8 times, and 3 of these are real: 38=0.375\frac38 = 0.375⁠.

Common mistakes
  1. Answering 34\frac34⁠. That is P(E∣S1)P(E|S_1)⁠, the chance that he reports a six when a six occurs, not the chance of a six given his report.
  2. Using 34\frac34 for both branches. When no six occurs, a report of "six" is a lie, so its probability is 14\frac14⁠.
  3. Forgetting the die. The prior 16\frac16 matters; with a coin (prior 12\frac12⁠) the same truth-teller would give a different answer.
What to take away
  1. For a witness or a test, the answer depends on both its reliability and how likely the reported thing was beforehand.
  2. The same question with a coin, where both outcomes are equally likely: Exercise 13.3, Question 13.

Every fact used, and where it comes from

FactUsed inSource
An event and its complement form a partitionStep 1Section 13.5.1 (Lesson: Bayes' theorem)
Fair die; complement ruleStep 2Class XI, Probability (Basics: rules of probability)
Theorem of total probabilityStep 3Section 13.5.2 (Lesson: total probability)
Bayes' theoremSteps 4, 5Section 13.5 (Examples 15 to 21)
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