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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 4 of 11

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Q31.
The profiler can be turned off by passing _________ to Rprof().

a.

0

b.

1

c.

2

d.

NULL

Discuss
Answer: (d).NULL
Q32.
Point out the correct statement?

a.

Rprof() is used to turn off the profiler

b.

At each line of the output, the profiler writes out the function call stack

c.

The summaryprof() function tabulates the R profiler output

d.

The Rprofiler() function starts the profiler in R

Discuss
Answer: (b).At each line of the output, the profiler writes out the function call stack
Q33.
How many methods exist for normalizing the data?

a.

one

b.

two

c.

three

d.

profiler

Discuss
Answer: (b).two
Q34.
_______ divides the time spend in each function by the total run time.

a.

“by.sum”

b.

“by.total”

c.

“by.self”

d.

“by.del”

Discuss
Answer: (b).“by.total”
Q35.
Point out the correct statement?

a.

“by.total” first subtracts out time spent in functions above the current function in the call stack

b.

The summaryRprof() function calculates how much time is spend in which function

c.

By default, the profiler samples the function call stack every 0.02 seconds

d.

The Rprofiler() function starts the profiler in R

Discuss
Answer: (c).By default, the profiler samples the function call stack every 0.02 seconds
Q36.
Which of the following function actually fits the linear model?

a.

lm.time()

b.

lm.date()

c.

lm.fit()

d.

lm.interval()

Discuss
Answer: (c).lm.fit()
Q37.
The final bit of output that summaryRprof() provides is the ______ interval and the total runtime.

a.

response

b.

sampling

c.

processing

d.

retrieve

Discuss
Answer: (b).sampling
Q38.
Which of the following statement gives sampling interval?

a.

$sampling.interval

b.

$sampling.time

c.

$sampling.date

d.

$sampling.datetime

Discuss
Answer: (b).$sampling.time
Q39.
Which of the following code is not profiled?

a.

C

b.

C++

c.

Java

d.

PHP

Discuss
Answer: (a).C
Q40.
_______ grammar makes a clear distinction between your data and what gets displayed on the screen or page.

a.

ggplot1

b.

ggplot2

c.

d3.js

d.

ggplot3

Discuss
Answer: (b).ggplot2
Page 4 of 11

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