Question:

An urn contains five balls. Two balls are drawn and found to be white. The probability that all the balls are white is

Updated On: Mar 18, 2024
  • $\frac{1}{10}$
  • $\frac{3}{10}$
  • $\frac{3}{5}$
  • $\frac{1}{2}$
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The Correct Option is D

Solution and Explanation

Let $A_i ( i = 2, 3, 4, 5) $ be the event that urn contains $2, 3, 4, 5$ white balls and let B be the event that two white balls have been drawn then we have to find $P (A_5/B)$.
Since the four events $A_2, A_3, A_4$ and $A_5$ are equally likely
we have $P (A_2) = P (A_3) = P (A_4) = P(A_5) = \frac{1}{4} $
$P(B/A_2)$ is probability of event that the urn contains 2 white balls and both have been drawn.
$\therefore P\left(B/A_{2}\right) = \frac{^{2}C_{2}}{^{5}C_{2}} = \frac{1}{10} $
Similarly $ P\left(B/A_{3}\right) = \frac{^{3}C_{2}}{^{5}C_{2}} = \frac{3}{10} $
$P\left(B/A_{4}\right) = \frac{^{4}C_{2}}{^{5}C_{2}} = \frac{3}{5} $
$ P\left(B/A_{5}\right) = \frac{^{5}C_{2}}{^{5}C_{2}} = 1 .$
By Baye?s theorem,
$ P\left(A_{5}/B\right) = \frac{P\left(A_{5} \right) P\left(B/A_{5}\right)}{P\left(A_{2}\right)P\left(B/A_{2}\right) + P\left(A_{3}\right)P\left(B/A_{3}\right)+P\left(A_{4}\right)\left(B/A_{4}\right)+P\left(A_{5}\right)P\left(B/A_{5}\right)} $
$ = \frac{\frac{1}{4}.1}{\frac{1}{4} \left[ \frac{1}{10} + \frac{3}{10}+ \frac{3}{5} +1\right]} = \frac{10}{20}= \frac{1}{2} $
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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.