Question:

There are three coins.One is a two headed coin,another is a biased coin that comes up heads \(75\%\) of the and third is an unbiased coin.One of the three coin is chosen at random and tossed,it shows head,what is the probability that it was the two headedcoin?

Updated On: Sep 21, 2023
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Solution and Explanation

The correct answer is: \(\frac{4}{9}\)
Let \(E_1=\)a two-headed coin, \(E_2=\)a biased coin and \(A=\)a head is shown
Now \(P(E_1)=\frac{1}{3}, P(E_2)=\frac{1}{3}, P(E_3)=\frac{1}{3}\)
\(P(A|E_1)=1, P(A|E_2)=\frac{75}{100}=\frac{3}{4}\) and \(P(A|E_3)=\frac{1}{2}\)
Therefore, by Bayes' theorem,
\(P(E_1|A)=\frac{P(E_1)P(A|E_1)}{P(E_1)P(A|E_1)+P(E_2)P(A|E_2)+P(E_3)P(A|E_3)}\)
\(=\frac{\frac{1}{3}×1}{\frac{1}{3}×1+\frac{1}{3}×\frac{3}{4}+\frac{1}{3}×\frac{1}{2}}\)
\(=\frac{\frac{1}{3}}{\frac{1}{3}(1+\frac{3}{4}+\frac{1}{2})}\)
\(=\frac{4}{9}\)
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Concepts Used:

Bayes Theorem

Bayes’ Theorem is a part of the conditional probability that helps in finding the probability of an event, based on previous knowledge of conditions that might be related to that event.

Mathematically, Bayes’ Theorem is stated as:-

\(P(A|B)=\frac{P(B|A)P(A)}{P(B)}\)

where,

  • Events A and B are mutually exhaustive events.
  • P(A) and P(B) are the probabilities of events A and B, respectively.
  • P(A|B) is the conditional probability of the happening of event A, given that event B has happened.
  • P(B|A) is the conditional probability of the happening of event B, given that event A has already happened.

This formula confines well as long as there are only two events. However, Bayes’ Theorem is not confined to two events. Hence, for more events.