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Welcome to the Profiling,Simulation and Data Analysis MCQs Page

Dive deep into the fascinating world of Profiling,Simulation and Data Analysis with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Profiling,Simulation and Data Analysis, a crucial aspect of R Programming. In this section, you will encounter a diverse range of MCQs that cover various aspects of Profiling,Simulation and Data Analysis, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within R Programming.

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Check out the MCQs below to embark on an enriching journey through Profiling,Simulation and Data Analysis. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of R Programming.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Profiling,Simulation and Data Analysis. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Profiling,Simulation and Data Analysis MCQs | Page 2 of 11

Explore more Topics under R Programming

Q11.
_________ ensures reproducibility of the sequence of random numbers.

a.

sets.seed()

b.

set.seed()

c.

set.seedvalue()

d.

set.value()

Discuss
Answer: (b).set.seed()
Q12.
Point out the correct statement?

a.

When simulating any random numbers it is not essential to set the random number seed

b.

It is not possible to generate random numbers from other probability distributions like the Poisson

c.

You should always set the random number seed when conducting a simulation

d.

Statistical procedure does not require random number generation

Discuss
Answer: (c).You should always set the random number seed when conducting a simulation
Q13.
5 Normal random numbers can be generated with rnorm() by setting seed value to ______________

a.

1

b.

2

c.

3

d.

4

Discuss
Answer: (a).1
Q14.
_______ function is used to simulate binary random variables.

a.

dnorm

b.

rbinom()

c.

binom()

d.

rpois

Discuss
Answer: (b).rbinom()
Q15.
Point out the wrong statement?

a.

Drawing samples from specific probability distributions can be done with “s” functions

b.

The sample() function draws randomly from a specified set of (scalar) objects allowing you to sample from arbitrary distributions of numbers

c.

The sampling() function draws randomly from a specified set of objects

d.

You should always set the random number seed when conducting a simulation

Discuss
Answer: (b).The sample() function draws randomly from a specified set of (scalar) objects allowing you to sample from arbitrary distributions of numbers
Q16.
What will be the output of the following R code? 
> set.seed(10)
> x <- rbinom(100, 1, 0.5)
> str(x)

a.

Int [1:100] 1 0 0 1 0 0 0 0 1 0 …

b.

Int [1:100] 10 0 01 1 0 0 01 0 1 0 …

c.

Int [1:100] 1 03 0 1 0 0 0 02 1 0 …

d.

Int [1:100] 1 2 3 1 1 0 0 0 1 0 …

Discuss
Answer: (a).Int [1:100] 1 0 0 1 0 0 0 0 1 0 …
Q17.
__________ distribution is commonly used to model data that come in the form of counts.

a.

Gaussian

b.

Parametric

c.

Poisson

d.

Simulation

Discuss
Answer: (c).Poisson
Q18.
What will be the output of the following R code? 
> rpois(10, 1)

a.

[1] 7 0 1 1 2 1 1 4 1 2

b.

[1] 0 8 1 1 2 1 1 4 1 2

c.

[1] 0 0 1 1 2 1 1 4 1 2

d.

[1] 0 0 0 0 0 0 0 1 4 1 2

Discuss
Answer: (c).[1] 0 0 1 1 2 1 1 4 1 2
Q19.
Which of the following code represents count with mean of 2?

a.

Rpois(10, 2)

b.

Rpois(10, 20)

c.

Rpois(20, 2)

d.

Rpois(20, 20)

Discuss
Answer: (a).Rpois(10, 2)
Q20.
What will be the output of the following R code? 
> set.seed(20)
> x <- rnorm(100)
> e <- rnorm(100, 0, 2)
> y <- 0.5 + 2 * x + e 
> summary(y)

a.

Min. 1st Qu. Median Mean 3rd Qu. Max.
-6.4080 -1.5400 0.6789 0.6893 2.9300 6.5050

b.

Min. 1st Qu. Median Mean 3rd Qu. Max.
-6.4080 -10.5400 0.6789 5.6893 2.9300 6.5050

c.

Min. 1st Qu. Median Mean 3rd Qu. Max.
-1.4080 -6.5400 0.6789 0.6893 2.9300 6.5050

d.

Error

Discuss
Answer: (a).Min. 1st Qu. Median Mean 3rd Qu. Max.
-6.4080 -1.5400 0.6789 0.6893 2.9300 6.5050
Page 2 of 11

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