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Chapter 13 · Probability

Exercise 13.3 · Q13 (MCQ): Speaks the truth with 45\frac45⁠: head actually appeared, P=45P = \frac45

Exercise 13.3Bayes' theorem · Section 13.5
The question

Probability that A speaks truth is 45\frac45⁠. A coin is tossed. A reports that a head appears. The probability that actually there was head is

(A) 45\frac45    (B) 12\frac12    (C) 15\frac15    (D) 25\frac25

Exam answer

Let E1E_1⁠: a head appears, E2E_2⁠: a tail appears, and RR⁠: A reports a head. E1E_1 and E2E_2 form a partition of the sample space (a toss gives exactly one of them).

P(E1)=P(E2)=12P(E_1) = P(E_2) = \frac12 (fair coin), P(R∣E1)=45P(R|E_1) = \frac45 and P(R∣E2)=1−45=15P(R|E_2) = 1 - \frac45 = \frac15⁠.

By Bayes' theorem,

P(E1∣R)=12⋅4512⋅45+12⋅15=410÷510\begin{aligned} P(E_1|R) &= \frac{\frac12\cdot\frac45}{\frac12\cdot\frac45 + \frac12\cdot\frac15} \\ &= \frac{4}{10} \div \frac{5}{10} \end{aligned}

Answer: (A) 45\dfrac45

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

The one idea this problem is built on

The report "head" can come from a true head (A tells the truth) or from a tail (A lies). Bayes' theorem compares the two routes. Because the coin gives head and tail equally often, the comparison is just truth against lie, 4 to 1, so the answer is the probability of telling the truth, 45\frac45⁠.

Given, to find, and the plan
Given
A speaks the truth with probability 45\frac45⁠. A coin is tossed (taken as fair) and A reports a head.
To find
The probability that a head actually appeared, given the report: P(E1∣R)P(E_1|R)⁠, and which option it is.
Plan
(1) Name the events; check the partition. (2) The four probabilities, including the chance of a lie. (3) Total probability for P(R)P(R)⁠. (4) Bayes' theorem. (5) Examine every option.

Basics you need

1Complement rule

If A speaks the truth with probability 45\frac45⁠, A lies with probability 1−45=151 - \frac45 = \frac15⁠. Basics: rules of probability

2Conditional probability (Section 13.2)

After a head, A reports a head only by telling the truth: P(R∣E1)=45P(R|E_1) = \frac45⁠. After a tail, A reports a head only by lying: P(R∣E2)=15P(R|E_2) = \frac15⁠. Lesson: conditional probability

3Total probability and Bayes' theorem (Section 13.5)

For a partition E1,E2E_1, E_2⁠: P(R)=∑P(Ei)P(R∣Ei)P(R) = \sum P(E_i)P(R|E_i) and P(E1∣R)=P(E1)P(R∣E1)P(R)P(E_1|R) = \frac{P(E_1)P(R|E_1)}{P(R)}⁠. Lesson: Bayes' theorem

Solution

  1. Name the events

    Let

    • E1E_1⁠: a head appears on the coin;
    • E2E_2⁠: a tail appears on the coin;
    • RR⁠: A reports that a head appears.

    E1E_1 and E2E_2 form a partition of the sample space: a toss gives exactly one of head and tail, and each is possible.

    What the coin really shows is the hidden cause; A's report is the result we observe. We write RR for the report because the letter A already names the person.
    Partition: pairwise disjoint, exhaustive, nonzero probabilities (Section 13.5.1). Lesson: Bayes' theorem
  2. The four probabilities

    P(E1)=12,P(E2)=12,\begin{aligned} P(E_1) &= \frac12, \\ P(E_2) &= \frac12, \end{aligned} P(R∣E1)=45,P(R∣E2)=1−45=15.\begin{aligned} P(R|E_1) &= \frac45, \\ P(R|E_2) &= 1 - \frac45 = \frac15. \end{aligned}
    The coin is taken as fair, as usual when nothing else is said. If a head appeared, A reports a head exactly when A tells the truth. If a tail appeared, A reports a head exactly when A lies. A's chance of telling the truth is taken to be 45\frac45 whatever the coin shows.
    P(lie)=1−P(truth)P(\text{lie}) = 1 - P(\text{truth})⁠. Basics: rules of probability
  3. The chance that A reports a head

    Since E1E_1 and E2E_2 form a partition, by the theorem of total probability

    P(R)=P(E1)P(R∣E1)+P(E2)P(R∣E2)=12⋅45+12⋅15=410+110=510.\begin{aligned} P(R) &= P(E_1)P(R|E_1) \\ &\quad + P(E_2)P(R|E_2) \\ &= \frac12\cdot\frac45 + \frac12\cdot\frac15 \\ &= \frac{4}{10} + \frac{1}{10} = \frac{5}{10}. \end{aligned}
    start coin shows A reports multiply along the path coin E₁: head R: says head 1/2 × 4/5 = 4/10 R′: says tail 1/2 × 1/5 = 1/10 E₂: tail R: says head 1/2 × 1/5 = 1/10 R′: says tail 1/2 × 4/5 = 4/10 1/2 4/5 1/5 1/2 1/5 4/5
    The tree for Question 13. The rose path (a head, then a true report) has product 410\frac{4}{10}⁠; the green path (a tail, then a false report of a head) has 110\frac{1}{10}⁠. Together, P(R)=510P(R) = \frac{5}{10}⁠.
    A report of a head comes either from a head and the truth or from a tail and a lie, never both, so the two path probabilities add.
    Multiply along a path, add the paths. Basics: tree diagrams
  4. A head, given the report: Bayes' theorem

    By Bayes' theorem,

    P(E1∣R)=P(E1)P(R∣E1)P(R)=410÷510=410×105=45.\begin{aligned} P(E_1|R) &= \frac{P(E_1)P(R|E_1)}{P(R)} \\ &= \frac{4}{10} \div \frac{5}{10} \\ &= \frac{4}{10} \times \frac{10}{5} = \frac45. \end{aligned}
    The top is the "true head" path; the bottom is both routes to the report. The answer equals A's chance of telling the truth only because the coin is fair: with P(E1)=P(E2)P(E_1) = P(E_2)⁠, the halves cancel and 4545+15=45\frac{\frac45}{\frac45 + \frac15} = \frac45⁠.
    Dividing by a fraction is multiplying by its flip. Basics: dividing by a fraction
  5. Examine every option

    • (A) 45\frac45⁠: equals P(E1∣R)P(E_1|R) from Step 4. Correct.
    • (B) 12\frac12⁠: this is P(E1)P(E_1)⁠, the chance of a head before the report is heard. It ignores the report, which is evidence for a head. Wrong.
    • (C) 15\frac15⁠: this is P(R∣E2)P(R|E_2)⁠, the chance that A lies; it is also P(E2∣R)=1−45P(E_2|R) = 1 - \frac45⁠, the chance that there was a tail after all. Wrong.
    • (D) 25\frac25⁠: this is 12⋅45=410\frac12\cdot\frac45 = \frac{4}{10}⁠, the probability of the path "head and a true report", P(E1∩R)P(E_1 \cap R)⁠. It forgets to divide by P(R)=510P(R) = \frac{5}{10}⁠. Wrong.
    Each wrong option is a number that appears on the way to the answer, which is why it is offered. Only the conditional probability P(E1∣R)P(E_1|R) answers "given that A reports a head".
    P(E1∣R)=P(E1∩R)P(R)P(E_1|R) = \frac{P(E_1 \cap R)}{P(R)}⁠. Lesson: conditional probability
Result

The probability that there actually was a head is 45\frac45⁠: option (A). (Textbook answer: (A).)

Check it with numbers

Picture 100 tosses. About 50 are heads, and A truthfully reports a head on 45×50=40\frac45 \times 50 = 40 of them. About 50 are tails, and A falsely reports a head on 15×50=10\frac15 \times 50 = 10 of them. So A reports a head 40+10=5040 + 10 = 50 times, and 40 of these were real heads: 4050=0.8\frac{40}{50} = 0.8⁠, the same as 45=0.8\frac45 = 0.8⁠.

Common mistakes
  1. Choosing (D). 25\frac25 is the joint probability P(E1∩R)P(E_1 \cap R)⁠; a conditional probability must be divided by P(R)P(R)⁠.
  2. Choosing (B). The report changes the chance of a head; 12\frac12 is the chance before the report.
  3. Forgetting the lie route. A can report a head after a tail, with probability 15\frac15⁠; leaving it out makes the bottom 410\frac{4}{10}⁠, the same as the top, and gives a "probability" of 1.
  4. Thinking the answer is always the truth probability. It is 45\frac45 here only because the coin is fair; with a die and a six it is different (book Example 21 gets 38\frac38 from a truth probability of 34\frac34⁠).
What to take away
  1. For "reports that…" questions, the two routes to the report are "it happened and the speaker tells the truth" and "it did not happen and the speaker lies".
  2. When the two causes are equally likely, Bayes' theorem reduces to comparing P(R∣E1)P(R|E_1) with P(R∣E2)P(R|E_2)⁠: here 4 to 1.
  3. Compare book Example 21 (a die and a six, Examples 15 to 21), where an unlikely event keeps the answer far below the truth probability, and Question 5, the blood test.

Every fact used, and where it comes from

FactUsed inSource
Partition of a sample spaceStep 1Section 13.5.1 (Lesson: Bayes' theorem)
P(E′)=1−P(E)P(E') = 1 - P(E)Step 2Class XI axioms (Basics: rules of probability)
Conditional probability P(R∣E)P(R|E)Steps 2, 5Section 13.2 (Lesson: conditional probability)
Theorem of total probabilityStep 3Section 13.5.2 (Lesson: Bayes' theorem)
Bayes' theoremSteps 4, 5Section 13.5; Example 21 is a truth-teller with a die (Examples 15 to 21)
Dividing by a fractionStep 4Arithmetic (Basics: dividing by a fraction)
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