Question

A box contains $$N$$ coins, $$m$$ of which are fair and the rest are biased. The probability of getting a head when a fair coin is tossed is $$\frac{1}{2},$$ while it is $$\frac{2}{3}$$ when a biased coin is tossed. A coin is drawn from the box at random and is tossed twice. Then the probability that the coin drawn is fair, is :

A. $$\frac{{9m}}{{8N + m}}$$  
B. $$\frac{{9m}}{{8N - m}}$$
C. $$\frac{{9m}}{{8m - N}}$$
D. $$\frac{{9m}}{{8m + N}}$$
Answer :   $$\frac{{9m}}{{8N + m}}$$
Solution :
$$\eqalign{ & {E_1}\,:{\text{coin is fair, }}{E_2}\,:{\text{coin is biased,}} \cr & A{\text{ second toss shows tail}}{\text{.}} \cr & P\left( {\frac{{{E_1}}}{A}} \right) = \frac{{P\left( {\frac{A}{{{E_1}}}} \right)P\left( {{E_1}} \right)}}{{P\left( {\frac{A}{{{E_1}}}} \right)P\left( {{E_1}} \right) + P\left( {\frac{A}{{{E_2}}}} \right)P\left( {{E_2}} \right)}} \cr & = \frac{{\frac{m}{N}.\frac{1}{2}.\frac{1}{2}}}{{\frac{m}{N}.\frac{1}{2}.\frac{1}{2} + \frac{{N - m}}{N}.\frac{2}{3}.\frac{1}{3}}} \cr & = \frac{{9m}}{{8N + m}} \cr} $$

Releted MCQ Question on
Statistics and Probability >> Probability

Releted Question 1

Two fair dice are tossed. Let $$x$$ be the event that the first die shows an even number and $$y$$ be the event that the second die shows an odd number. The two events $$x$$ and $$y$$ are:

A. Mutually exclusive
B. Independent and mutually exclusive
C. Dependent
D. None of these
Releted Question 2

Two events $$A$$ and $$B$$ have probabilities 0.25 and 0.50 respectively. The probability that both $$A$$ and $$B$$ occur simultaneously is 0.14. Then the probability that neither $$A$$ nor $$B$$ occurs is

A. 0.39
B. 0.25
C. 0.11
D. none of these
Releted Question 3

The probability that an event $$A$$ happens in one trial of an experiment is 0.4. Three independent trials of the experiment are performed. The probability that the event $$A$$ happens at least once is

A. 0.936
B. 0.784
C. 0.904
D. none of these
Releted Question 4

If $$A$$ and $$B$$ are two events such that $$P(A) > 0,$$   and $$P\left( B \right) \ne 1,$$   then $$P\left( {\frac{{\overline A }}{{\overline B }}} \right)$$  is equal to
(Here $$\overline A$$ and $$\overline B$$ are complements of $$A$$ and $$B$$ respectively).

A. $$1 - P\left( {\frac{A}{B}} \right)$$
B. $$1 - P\left( {\frac{{\overline A }}{B}} \right)$$
C. $$\frac{{1 - P\left( {A \cup B} \right)}}{{P\left( {\overline B } \right)}}$$
D. $$\frac{{P\left( {\overline A } \right)}}{{P\left( {\overline B } \right)}}$$

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Probability


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