Explore topic-wise MCQs in Engineering Mathematics.

This section includes 21 Mcqs, each offering curated multiple-choice questions to sharpen your Engineering Mathematics knowledge and support exam preparation. Choose a topic below to get started.

1.

If E(x) = 2 and E(z) = 4, then E(z – x) =?

A. 2
B. 6
C. 0
D. Insufficient data
Answer» B. 6
Discussion
2.

Out of the following values, which one is not possible in probability?

A. P(x) = 1
B. ∑ x P(x) = 3
C. P(x) = 0.5
D. P(x) = – 0.5
Answer» E.
Discussion
3.

If ‘X’ is a continuous random variable, then the expected value is given by ___________

A. P(X)
B. ∑ x P(x)
C. ∫ X P(X)
D. No value such as expected value
Answer» D. No value such as expected value
Discussion
4.

The expected value of a discrete random variable ‘x’ is given by ___________

A. P(x)
B. ∑ P(x)
C. ∑ x P(x)
D. 1
Answer» D. 1
Discussion
5.

If a variable can certain integer values between two given points is called ___________

A. Continuous random variable
B. Discrete random variable
C. Irregular random variable
D. Uncertain random variable
Answer» C. Irregular random variable
Discussion
6.

A variable that can assume any value between two given points is called ___________

A. Continuous random variable
B. Discrete random variable
C. Irregular random variable
D. Uncertain random variable
Answer» B. Discrete random variable
Discussion
7.

A table with all possible value of a random variable and its corresponding probabilities is called ___________

A. Probability Mass Function
B. Probability Density Function
C. Cumulative distribution function
D. Probability Distribution
Answer» E.
Discussion
8.

What would be the probability of an event ‘G’ if H denotes its complement, according to the axioms of probability?

A. P (G) = 1 / P (H)
B. P (G) = 1 – P (H)
C. P (G) = 1 + P (H)
D. P (G) = P (H)
Answer» C. P (G) = 1 + P (H)
Discussion
9.

Mutually Exclusive events ___________

A. Contain all sample points
B. Contain all common sample points
C. Does not contain any sample point
D. Does not contain any common sample point
Answer» E.
Discussion
10.

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. If random variables do not exhibit deviation from its mean value
Answer» C. Only if random variables exhibit deviation from its mean value
Discussion
11.

What is the area under a conditional Cumulative density function?

A. 0
B. Infinity
C. 1
D. Changes with CDF
Answer» D. Changes with CDF
Discussion
12.

Which of the following mentioned standard Probability density functions is applicable to discrete Random Variables?

A. Gaussian Distribution
B. Poisson Distribution
C. Rayleigh Distribution
D. Exponential Distribution
Answer» C. Rayleigh Distribution
Discussion
13.

THE_EXPECTED_VALUE_OF_A_DISCRETE_RANDOM_VARIABLE_‚ÄÖ√Ñ√∂‚ÀÖ√Ë‚Àւ§X‚ÄÖ√Ñ√∂‚ÀÖ√Ë‚ÀÖ¬•_IS_GIVEN_BY?$#

A. P(x)
B. ‚àë P(x)
C. ‚àë x P(x)
D. 1
Answer» D. 1
Discussion
14.

Out of the following values, which one is not possible in probability ?$

A. P(x) = 1
B. ‚àë x P(x) = 3
C. P(x) = 0.5
D. P(x) = – 0.5
Answer» E.
Discussion
15.

If ‘X’ is a continuous random variable, then the expected value is given by$#

A. P(X)
B. ‚àë x P(x)
C. ‚à´ X P(X)
D. No value such as expected value
Answer» D. No value such as expected value
Discussion
16.

If E(x) = 2 and E(z) = 4, then E(z – x) =$

A. 2
B. 6
C. 0
D. Insufficient data
Answer» B. 6
Discussion
17.

If a variable can certain integer values between two given points is calle?
A. Continuous random variable
B. Discrete random variable
C. Irregular random variable
D. Uncertain random variable
Answer» C. Irregular random variable
Discussion
18.

A variable that can assume any value between two given points is called
A. Continuous random variable
B. Discrete random variable
C. Irregular random variable
D. Uncertain random variable
Answer» B. Discrete random variable
Discussion
19.

What would be the probability of an event ‘G’ if H denotes its complement, according to the axioms of probability?$

A. P (G) = 1 / P (H)
B. P (G) = 1 – P (H)
C. P (G) = 1 + P (H)
D. P (G) = P (H)
Answer» C. P (G) = 1 + P (H)
Discussion
20.

Mutually Exclusive events
A. Contain all sample points
B. Contain all common sample points
C. Does not contain any sample point
D. Does not contain any common sample point
Answer» E.
Discussion
21.

What is the area under a conditional Cumulative density function ?
A. 0
B. Infinity
C. 1
D. Changes with CDF
Answer» D. Changes with CDF
Discussion