Important MCQ Random Variables 1

 The post is about MCQ Random Variables. There are 20 multiple-choice questions related to random experiments, random variables and types of random variables, expectations, discrete random variables, and continuous random variables. Let us start with the MCQ Random Variables Quiz.

Online MCQs about Random Variable with Answers

1. Which of the following statements describes continuous random variables?

 
 
 
 

2. A variable whose value is determined by the outcome of a random experiment is called

 
 
 
 
 

3. If $X$ and $Y$ are random variable then $E(X + Y)$ is equal to

 
 
 
 

4. Two random variables $X$ and $Y$ are said to be independent if:

 
 
 
 

5. If $X$ is a discrete random variable, the function $f(X)$ is

 
 
 
 

6. For a random variable $X$, $E(X)$ is

 
 
 
 

7. A variable (Random Variable) assuming an infinite number of values is called

 
 
 
 

8. When four coins are tossed, the value of a random variable (Numbers of head) is

 
 
 
 

9. If $X$ and $Y$ are two independent variables, then

 
 
 
 

10. If $X$ is a random variable and $a$ and $b$ are constants then $Var(aX+ b)$ is equal to

 
 
 
 

11. Which of the following statements accurately describes a key difference between discrete and continuous random variables?

 
 
 
 

12. A continuous variable is a variable that can assume

 
 
 
 

13. A variable (Random Variable) assuming a finite number of values is called

 
 
 
 

14. If $X$ is a continuous random variable, then function $f(X)$ is

 
 
 
 

15. A _____ random variable has a countable number of possible values.

 
 
 
 

16. A continuous random variable is a random variable that can

 
 
 
 

17. Which of the following are examples of discrete random variables?

 
 
 
 

18. If $C$ is a non-random variable, the $E(C)$ is

 
 
 
 

19. If $X$ is a random variable that can take only non-negative values, then

 
 
 
 

20. If $X$ and $Y$ are independent random variables then $E(XY)$ is equal to

 
 
 
 
 

MCQ Random Variables Quiz

MCQ Random Variables Quiz
  •  If $X$ is a continuous random variable, then function $f(X)$ is
  • A variable (Random Variable) assuming an infinite number of values is called
  • A variable whose value is determined by the outcome of a random experiment is called
  • If $X$ and $Y$ are random variable then $E(X + Y)$ is equal to
  • If $X$ is a discrete random variable, the function $f(X)$ is
  • When four coins are tossed, the value of a random variable (Numbers of head) is
  • A variable (Random Variable) assuming a finite number of values is called
  • If $X$ and $Y$ are independent random variables then $E(XY)$ is equal to
  • Two random variables $X$ and $Y$ are said to be independent if:
  • If $X$ and $Y$ are two independent variables, then
  • A continuous random variable is a random variable that can
  • If $X$ is a random variable that can take only non-negative values, then
  • For a random variable $X$, $E(X)$ is
  • If $C$ is a non-random variable, the $E(C)$ is
  • A continuous variable is a variable that can assume
  • A ———– random variable has a countable number of possible values.
  • Which of the following statements accurately describes a key difference between discrete and continuous random variables?
  • Which of the following are examples of discrete random variables?
  • Which of the following statements describes continuous random variables?
  • If $X$ is a random variable and $a$ and $b$ are constants then $Var(aX+ b)$ is equal to
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Important MCQs Probability Distributions 4

The post is about MCQs Probability Distributions. There are 20 multiple-choice questions covering the topics related to Chi-Square distribution, F-distribution, Binomial distribution, Student’s t distribution, and properties of distributions. Let us start with MCQs Probability Distributions.

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MCQs Probability Distributions Quiz

MCQs Probability Distributions with Answers
  • 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 shape of 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
  • Student’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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Best Probability Distribution Questions 3

The post is about Probability Distribution Questions. There are 20 multiple-choice questions covering topics related to normal probability distribution, standard normal probability distribution, and its properties. Let us start with the Quiz Probability Distribution Questions.

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Probability Distribution Questions with Answers

MCQs Probability Distribution Questions with Answers
  • The area under the normal curve on either side of the mean is
  • In the case of a symmetrical distribution
  • The mean deviation of Normal Distribution is
  • The Normal Distribution has parameters
  • In Normal distribution, the parameters which control the flatness of the curve is
  • We use normal distribution when $n$ is
  • The median of the normal distribution corresponds to the value of $Z$ equal to
  • The lower and upper quartiles of standard normal variate are respectively
  • The shape of the normal curve can be related to
  • The total Area under the normal curve is
  • Which of the following parameters controls the relative flatness of a normal distribution
  • In a normal distribution $E(X−\mu)^2$ is
  • If $X\sim N(55,49)$ then $\sigma$
  • The Normal Curve is asymptotic to the
  • The shape of the normal curve depends upon
  • If $X\sim N(16, 49)$, then mean is
  • Normal Distribution is
  • If $Y=5X + 10$ and $X$ is $N(10,25)$, then mean of $Y$ is
  • Normal Distribution is
  • The formula in which binomial distribution approaches normal probability distribution with the help of normal variable is written as
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