Question

The probability of a man hitting a target is $$\frac{1}{4}$$. The number of times he must shoot so that the probability he hits the target, at least once is more than $$0.9,$$  is :
$$\left[ {{\text{use }}\log \,4 = 0.602{\text{ and }}\log \,3 = 0.477} \right]$$

A. $$7$$
B. $$8$$  
C. $$6$$
D. $$5$$
Answer :   $$8$$
Solution :
Let $$n$$ denote the required number of shots and $$X$$ the number of shots that hit the target.
Then $$X \sim B\left( {n,\,p} \right),$$    with $$p = \frac{1}{4}.$$
Now,
$$\eqalign{ & P\left( {X \geqslant 1} \right) \geqslant 0.9 \cr & \Rightarrow 1 - P\left( {X = 0} \right) \geqslant 0.9 \cr & \Rightarrow 1 - {}^n{C_0}{\left( {\frac{3}{4}} \right)^n} \geqslant 0.9 \cr & \Rightarrow {\left( {\frac{3}{4}} \right)^n} \leqslant \frac{1}{{10}} \cr & \Rightarrow {\left( {\frac{4}{3}} \right)^n} \geqslant 10 \cr & \Rightarrow n\left( {\log \,4 - \log \,3} \right) \geqslant 1 \cr & \Rightarrow n\left( {0.602 - 0.477} \right) \geqslant 1 \cr & \Rightarrow n \geqslant \frac{1}{{0.125}} = 8 \cr} $$
Therefore the least number of trials required is $$8.$$

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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