Question
a.
Made slowly
b.
Axes are not cleaned up
c.
Color is used for personal information
d.
All of the mentioned
Posted under Data Science
Engage with the Community - Add Your Comment
Confused About the Answer? Ask for Details Here.
Know the Explanation? Add it Here.
Q. Which of the following is characteristic of exploratory graph?
Similar Questions
Discover Related MCQs
Q. Point out the correct statement.
View solution
Q. Which of the following graph can be used for simple summarization of data?
View solution
Q. Color and shape are used to add dimensions to graph data.
View solution
Q. Which of the following information is not given by five-number summary?
View solution
Q. Which of the following is also referred to as overlayed 1D plot?
View solution
Q. Spinning plots can be used for two dimensional data.
View solution
Q. Which of the following problem is solved by reproducibility?
View solution
Q. Point out the correct statement with respect to replication.
View solution
Q. Which of the following is effective way of checking validity of data analysis?
View solution
Q. Which of the following is similar to a pre-specified clinical trial protocol?
View solution
Q. Point out the wrong statement with respect to reproducibility.
View solution
Q. Which of the following can be used for data analysis model?
View solution
Q. Reproducibility determines correctness of data analysis.
View solution
Q. Which of the following step is not required in data analysis?
View solution
Q. Which of the following gives reviewers an important tool without dramatically increasing the burden?
View solution
Q. Result analysis are relatively easy to replicate or reproduce.
View solution
Q. Which of the following is suitable for knitr?
View solution
Q. Point out the correct combination related to output statements.
View solution
Q. Which of the following is required for not echoing the code?
View solution
Q. Which of the following global options are available for figures in knitr?
View solution
Suggested Topics
Are you eager to expand your knowledge beyond Data Science? We've curated a selection of related categories that you might find intriguing.
Click on the categories below to discover a wealth of MCQs and enrich your understanding of Computer Science. Happy exploring!