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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 3 of 11

Explore more Topics under R Programming

Q21.
________ is a systematic way to examine how much time is spent in different parts of a program.
Discuss
Answer: (a).Profiling
Discuss
Answer: (b).Using system.time() allows you to test certain functions or code blocks to see if they are taking excessive amounts of time
Q23.
R comes with a ________ to help you optimize your code and improve its performance.
Discuss
Answer: (a).debugger
Q24.
The _______ function computes the time (in seconds) needed to execute an expression.
Discuss
Answer: (b).system.time()
Discuss
Answer: (b).Rprof() keeps track of the function call stack at regularly sampled intervals
Q26.
system.time function returns an object of class _______ which contains two useful bits of information.
Discuss
Answer: (b).proc_time
Q27.
_________ time is time charged to the CPU(s) for the R expression.
Discuss
Answer: (a).elapsed
Q28.
The elapsed time may be ________ than the user time if your machine has multiple cores/processors.
Discuss
Answer: (a).smaller
Q29.
Parallel processing is done via __________ package can make the elapsed time smaller than the user time.
Discuss
Answer: (a).parallel
Q30.
You can time ________ expressions by wrapping them in curly braces within the call to system.time().
Discuss
Answer: (b).longer

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