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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 7 of 11

Discuss
Answer: (c).ggplot.data create a new ggplot plot from a data frame
Q62.
______ display a smooth density estimate.
Discuss
Answer: (b).geom_density
Q63.
Which of the following draws nothing?
Discuss
Answer: (c).geom_bin2d
Discuss
Answer: (c).qplot is used for quick plot
Q65.
_________ describe the type of plot you will produce.
Discuss
Answer: (a).geoms
Q66.
__________ is interval represented by a vertical line, with a point in the middle.
Discuss
Answer: (b).geom_pointrange
Q67.
Which of the following create a set of identity mappings?
Discuss
Answer: (d).ggorder
Q68.
_________ is new package that makes it easy to “tidy” your data.
Discuss
Answer: (c).tidyneat
Discuss
Answer: (d).All of the mentioned
Q70.
Which of the following is complementary to tidyr?
Discuss
Answer: (b).dplyr

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