1. Which of the following gives reviewers an important tool without dramatically increasing the burden?
a) Quality research
b) Replication research
c) Reproducible research
d) None of the mentioned
Explanation: Reproducible research is important, but does not necessarily solve the critical question of whether a data analysis is trustworthy.
2. Result analysis are relatively easy to replicate or reproduce.
a) True
b) False
Explanation: Complicated analyses should not be trusted.
3. What is the role of processing code in the research pipeline?
a) Transforms the analytical results into figures and tables
b) Transforms the analytic data into measured data
c) Transforms the measured data into analytic data
d) All of the mentioned
Explanation: Data science workflow is a non-linear, iterative process.
4. Which of the following is a goal of literate statistical programming?
a) Combine explanatory text and data analysis code in a single document
b) Ensure that data analysis documents are always exported in JPEG format
c) Require those data analysis summaries are always written in R
d) None of the mentioned
Explanation: Literate Statistical Practice is a programming methodology.
5. What does it mean to weave a literate statistical program?
a) Convert a program from S to python
b) Convert the program into a human readable document
c) Convert a program to decompress it
d) All of the mentioned
Explanation: Literate Statistical Programming can be done with knitr.
6. Which of the following is required to implement a literate programming system?
a) A programming language like Perl
b) A programming language like Java
c) A programming language like R
d) All of the mentioned
Explanation: R is a language and environment for statistical computing and graphics.
7. What is one way in which the knitr system differs from Sweave?
a) knitr allows for the use of markdown instead of LaTeX
b) knitr is written in python instead of R
c) knitr lacks features like caching of code chunks
d) none of the mentioned
Explanation: knitr is an engine for dynamic report generation with R.
8. Which of the following is useful way to put text, code, data, output all in one document?
a) Literate statistical programming
b) Object oriented programming
c) Descriptive programming
d) All of the mentioned
Explanation: Object-oriented programming is a programming language model organized around objects rather than “actions” and data rather than logic.
9. Some chunks have to be re-computed every time you re-knit the file.
a) True
b) False
Explanation: All chunks have to be re-computed every time you re-knit the file.
10. Which of the following tool can be used for integrating text and code in one document?
a) knitr
b) ggplot2
c) NumPy
d) None of the mentioned
Explanation: knitr is a way to write LaTeX, HTML, and Markdown with R code interlaced.