Tag: random variables and probability distribution

Questions Related to random variables and probability distribution

In a poisson distribution, the variance is $m$ . The sum of terms in odd places in the distribution is 

  1. $e^{-m}$

  2. $e^{-m} \cos \, h \, (m)$

  3. $e^{-m} \sin \, h \, (m)$

  4. $e^{-m} \cot \, h \, (m)$


Correct Option: B
Explanation:

$e^{-m}\cos h(m)$


 lf the mean is $\lambda$ and the variance is $\sigma^{2}$ in a Poisson distribution, then

  1. $\displaystyle \lambda=\frac{1}{2}\sigma^{2}$

  2. $\displaystyle \sigma^{2}=\frac{1}{2}\lambda$

  3. $\lambda=\sigma^{2}$

  4. $\sigma^{2}=\lambda^{2}$


Correct Option: C
Explanation:

For a Poisson distribution, mean and variance are equal .
i.e.$\lambda = \sigma^2$

If the mean of P.D. is 5, then the variance of the same distribution is

  1. $25$

  2. $10$

  3. $5$

  4. $15$


Correct Option: C
Explanation:

The mean of P.D. is $5$. 
In P.D,  the variance and mean of the same distribution is same.
So, variance = $5$

If ${\overline{x}}$ and $\sigma^{2}$ are mean and variance of poisson distribution, then

  1. $\overline{x}>\sigma^{2}$

  2. $\overline{x}<\sigma^{2}$

  3. $\overline{x}=\sigma^{2}$

  4. $\overline{x}+\sigma^{2}=1$


Correct Option: C
Explanation:

For a Poisson distribution, mean ($\mu$) and variance ($\sigma^2$ )are equal .
i.e.$\mu = \sigma^2$

The S.D. of poisson distribuition whose mean is $\lambda $ is

  1. $\lambda$

  2. $\sqrt{\lambda}$

  3. $\lambda^{2}$

  4. $\displaystyle \frac{1}{\sqrt{\lambda}}$


Correct Option: B
Explanation:

Mean = $ \lambda$
In Poisson distribution, the expected value of a Poisson-distributed random variable is equal to that is mean and is equal to its variance. 
Variance =  $ \lambda$
S.D = $ \sqrt {variance} =\sqrt { \lambda  } $

If the mean of Poisson distribution is $\displaystyle \frac{1}{2}$, then the ratio of $P(X=3)$ to $P(X=2)$ is 

  1. 1:2

  2. 1:4

  3. 1:6

  4. 1:8


Correct Option: C
Explanation:

$P(X=3)/P(X=2)$
$=\dfrac{\lambda^{3}(2!)}{3!(\lambda^{2})}$
$=\dfrac{\lambda}{3}$
$=\dfrac{1}{2(3)}$
$=\dfrac{1}{6}$
The ratio is $1:6$

In a poisson distribution, the probability of $0$ success is $10$%. The mean of the distribution is equal to

  1. $\log _{10}e$

  2. $\log _{e}10$

  3. $0$

  4. $\dfrac{1}{10}$


Correct Option: B
Explanation:

Given $P(X=0)=.1$
$\Rightarrow e^{-\lambda}=\cfrac{1}{10}\therefore \lambda = \log _e 10$

The parameter $\lambda $ of poisson distribution is always

  1. zero

  2. 1

  3. -1

  4. a finite positive value


Correct Option: D
Explanation:

In Poisson distribution the  parameter $(  > 0)$, it is always greater than zero or a finite positive value.

If X is a poisson variable with parameter 0.09,then its S.D. is

  1. 0.009

  2. 0.3

  3. 0.03

  4. 0.09


Correct Option: B
Explanation:

X is a Poisson variable with parameter 0.09.
In Poisson distribution,  
Poisson variable(X) is equal to  expected value of X and also to its variance. 
 S.D =  
$\sqrt {variance}  =  \sqrt { X } =\sqrt { 0.09 } =0.3$

The standard deviation of P.D. is 1.5, then its mean is

  1. 1.5

  2. 2

  3. 2.25

  4. 3.25


Correct Option: C
Explanation:

Given $\sigma =1.5$
We know that for a Poisson's distribution,mean and variance are equal.
$\mu=\sigma^2$
$\Rightarrow \mu =2.25$