# Probability, Random Variables and Random Signals - 2 - MCQs

## Probability, Random Variables and Random Signals - 2 - MCQs

1. The Joint Cumulative Density Function (CDF) _____

a. Is a non-negative function
b. Is a non-decreasing function of x & y planes
c. Is always a continuous function in xy plane
d. All of the above

ANSWER: d. All of the above

2. What is the value of an area under the conditional PDF ?

a. Greater than '0' but less than '1'
b. Greater than '1'
c. Equal to '1'
d. Infinite

3. When do the conditional density functions get converted into the marginally density functions ?

a. Only if random variables exhibit statistical dependency
b. Only if random variables exhibit statistical independency
c. Only if random variables exhibit deviation from its mean value
d. None of the above

ANSWER: b. Only if random variables exhibit statistical independency

4. Which among the below mentioned standard PDFs is/are applicable to discrete random variables ?

a. Gaussian distribution
b. Rayleigh distribution
c. Poisson distribution
d. All of the above

5. A random variable belongs to the category of a uniform PDF only when __________

a. It occurs in a finite range
b. It is likely to possess zero value outside the finite range
c. Both a & b
d. None of the above

ANSWER: c. Both a & b

6. What would happen if the value of term [(m-x) / (σ √2)] increases in the expression of Guassian CDF?

a. Complementary error function also goes on increasing

b. Complementary error function goes on decreasing

c. Complementary error function remains constant or unchanged

d. Cannot predict

ANSWER: b. Complementary error function goes on decreasing

7. Which type of standard PDFs has/ have an ability to describe an integer valued random variable concerning to the repeated trials carried /conducted in an experiment?

a. Binomial
b. Uniform
c. Both a & b
d. None of the above