MCQs Probability Distributions 4

This Quiz MCQs Probability Distributions for Random Variable covers the Mean and Variance of random variables and the distribution of Random variables. MCQs Probability Distributions quiz requires knowledge of events, experiments, mutually exclusive events, collectively exhaustive events, sure events, impossible events, addition and multiplication laws of probability, discrete probability distribution, continuous probability distributions, etc.

1. The $F$-distribution curve in respect of tails is:

 
 
 
 

2. Studnet’s $t$-distribution curve is symmetrical about mean, it means that

 
 
 
 

3. If $X$ has a binomial distribution with parameter $p$ and $n$ then $\frac{X}{n}$ has the variance:

 
 
 
 

4. The probability of failure in binomial distribution is denoted by

 
 
 
 

5. A family of parametric distribution in which mean always greater than its variance is:

 
 
 
 

6. The family of parametric distributions which has a mean always less than variance is:

 
 
 
 

7. If $X\sim N(\mu, \sigma^2)$ and $a$ and $b$ are real numbers, then mean of $(aX+b)$ is

 
 
 
 

8. The relation between the mean and variance of $\chi^2$ with $n$ degrees of freedom is

 
 
 
 

9. In binomial distribution, the formula for calculating the mean is

 

 
 
 
 

10. The formula to calculate standardized normal random variables is

 
 
 
 

11. In binomial probability distribution, dependents of standard deviations must include

 
 
 
 

12. The binomial distribution is symmetrical if $p=p=?$

 
 
 
 

13. The distribution possessing the memoryless property is

 
 
 
 

14. The mode of the Geometric distribution is

 
 
 
 

15. Events having an equal chance of occurrence are called

 
 
 
 

16. The mean of a binomial probability distribution is 857.6 and the probability is 64% then the number of values of binomial distribution

 
 
 
 

17. The distribution of sample correlation is

 
 
 
 

18. The family of parametric distributions for which moment generating function does not exist is:

 
 
 
 

19. The chi-square distribution is used for the test of

 
 
 
 

20. The distribution for which the mode does not exist is:

 
 
 
 


MCQs Probability Distributions

MCQs Probability Distributions

  • A family of parametric distribution in which mean always greater than its variance is:
  • The family of parametric distributions which has a mean always less than variance is:
  • The family of parametric distributions for which moment generating function does not exist is:
  • The distribution for which the mode does not exist is:
  • The relation between the mean and variance of $\chi^2$ with $n$ degrees of freedom is
  • The $F$-distribution curve in respect of tails is:
  • If $X$ has a binomial distribution with parameter $p$ and $n$ then $\frac{X}{n}$ has the variance:
  • The binomial distribution is symmetrical if $p=p=?$
  • The mode of the Geometric distribution is
  • If $X\sim N(\mu, \sigma^2)$ and $a$ and $b$ are real numbers, then mean of $(aX+b)$ is
  • The distribution of sample correlation is
  • Events having an equal chance of occurrence are called
  • Studnet’s $t$-distribution curve is symmetrical about mean, it means that
  • The distribution possessing the memoryless property is
  • The chi-square distribution is used for the test of
  • The probability of failure in binomial distribution is denoted by
  • In binomial distribution, the formula for calculating the mean is  
  • In binomial probability distribution, dependents of standard deviations must include
  • The formula to calculate standardized normal random variables is
  • The mean of a binomial probability distribution is 857.6 and the probability is 64% then the number of values of binomial distribution

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2 thoughts on “MCQs Probability Distributions 4”

    1. Thank you dear! for mentioning the error in quiz. More explanation is added to the question.
      If you find any other possible error in quiz or posts of itfeature.com, do let me know.

      The mean of a chi-square distribution is equal to its degrees of freedom ($k$) and the variance is $2k$.

      It means that if Mean $=k=2$ then variance $= 2 \times 2 = 4$

      Therefore, $2\, Mean = 2\times 2 = 4 = \, Variance$

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