Question

If mean and variance of a Binomial variate $$X$$ are $$2$$ and $$1$$ respectively, then the probability that $$X$$ takes a value greater than $$1$$ is :

A. $$\frac{2}{3}$$
B. $$\frac{4}{5}$$
C. $$\frac{7}{8}$$
D. $$\frac{{11}}{{16}}$$  
Answer :   $$\frac{{11}}{{16}}$$
Solution :
$$\eqalign{ & {\text{We have}}\,{\text{;}} \cr & np = 2 = {\text{mean }} \cr & npq = 1 = {\text{ variance}} \cr & \Rightarrow p = \frac{1}{2}\,;\,q = \frac{1}{2}\,\,\& \,\,n = 4 \cr & {\text{Required probability}} = P\left( {x > 1} \right) \cr & = 1 - P\left( {x \leqslant 1} \right) \cr & = 1 - \left[ {P\left( {x = 0} \right) + P\left( {x = 1} \right)} \right] \cr & = 1 - \left[ {{}^4{C_0}{q^4} + {}^4{C_1}{q^3}{p^1}} \right] \cr & = 1 - \frac{5}{{16}} \cr & = \frac{{11}}{{16}} \cr} $$

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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