Welcome to your complete guide for Reproducible Research quiz answers! Whether you’re working through practice quizzes to solidify your understanding or preparing for graded quizzes to test your knowledge, this guide is here to help.
Covering all course modules, this resource will teach you the importance of reproducibility in research, including best practices for data analysis, documentation, and ensuring that your findings can be independently verified by others.
Reproducible Research Quiz Answers for All Modules
Table of Contents
Reproducible Research Week 01 Quiz Answers
Q1. Suppose I conduct a study and publish my findings. Which of the following is an example of a replication of my study?
Explanation: A replication of a study involves an independent investigator repeating the original study with their own data collection, analysis, and results.
Answer: An investigator at another institution conducts a study addressing the same question, collects her own data, analyzes it separately from me, and publishes her own findings.
Q2. Which of the following is a requirement for a published data analysis to be reproducible?
Explanation: For a study to be reproducible, the full computer code used to analyze the data must be publicly available so others can rerun the analysis and verify the results.
Answer: The full computer code for doing the data analysis is made publicly available.
Q3. Which of the following is an example of a reproducible study?
Explanation: A reproducible study ensures that the analysis can be independently verified by others by making the data and code publicly available, allowing anyone to replicate the results.
Answer: The study’s analytic data and computer code for the data analysis are publicly available. When the code is run on the analytic data, the findings are identical to the published results.
Q4. Which of the following is a reason that a study might NOT be fully replicated?
Explanation: Replication can be hindered by several factors, such as lack of funding, reluctance to share data, or other barriers.
Answer: The original investigator does not want to make the analytic data available.
Q5. Which of the following is a reason why publishing reproducible research is increasingly important
Explanation: With the increase in complex and high-dimensional data, and advancements in technology, reproducible research allows others to verify, improve, and build upon findings.
Answer: New technologies are increasing the rate of data collection, creating datasets that are more complex and extremely high dimensional.
Q6. What is the role of processing code in the research pipeline?
Explanation: Processing code converts raw data into a structured form that can be analyzed, creating the analytic data.
Answer: It transforms the measured data into analytic data.
Q7. Which is a goal of literate statistical programming?
Explanation: Literate statistical programming combines code and explanatory text into one document, making the analysis both reproducible and understandable.
Answer: Combine explanatory text and data analysis code in a single document.
Q8. What does it mean to weave a literate statistical program?
Explanation: “Weaving” a literate statistical program involves transforming it into a human-readable document, which includes both code and narrative.
Answer: Transform the literate program into a human-readable document.
Q9. Which of the following is required to implement a literate programming system?
Explanation: Literate programming systems rely on a documentation language, such as LaTeX, for formatting the text and code together into a readable document.
Answer: A documentation language like LaTeX.
Q10. What is one way in which the knitr system differs from Sweave?
Explanation: Knitr is an R package that can also use markdown for formatting, making it more flexible than Sweave, which requires LaTeX.
Answer: knitr allows for the use of markdown instead of LaTeX.
Reproducible Research Week 02 Quiz Answers
Q1. Who created Markdown?
Explanation: Markdown is a lightweight markup language created by John Gruber. It is used for formatting text and has been widely adopted for its simplicity.
Answer: John Gruber
Q2. When writing a document in R Markdown, how do you denote the beginning of an R code chunk?
Explanation: In R Markdown, R code chunks are denoted by triple backticks () with `{r}` specifying the language, which in this case is R.
Answer: {r}
Q3. When using knitr, how do you indicate the height and width of a plot created in a code chunk?
Explanation: In knitr, plot dimensions like height and width are set using the fig.height and fig.width options within the code chunk.
Answer: Set the ‘fig.height’ and ‘fig.width’ options for the code chunk
Q4. With some code chunks, we may not want the output generated by the chunk to be rendered into HTML but would prefer to print the output verbatim. How can we specify this preference for a given code chunk?
Explanation: To prevent knitr from rendering the output and instead show it as verbatim, you can set the results = "asis" option in the code chunk.
Answer: Set the option results = “asis”
Q5. When using knitr and R Markdown and producing output in HTML, why should you never edit the resulting HTML file?
Explanation: The HTML file generated by knitting is automatically created from the R Markdown document, and any manual edits will be overwritten the next time the file is knitted.
Answer: Every time you knit() the R Markdown file, the HTML file will be overwritten
Frequently Asked Questions (FAQ)
Are the Reproducible Research quiz answers accurate?
Yes, these answers have been carefully verified to ensure they align with the latest course content and best practices for reproducible research.
Can I use these answers for both practice and graded quizzes?
Absolutely! These answers are designed for both practice quizzes and graded assessments, helping you prepare thoroughly for all evaluations.
Does this guide cover all modules of the course?
Yes, this guide provides answers for every module, ensuring complete coverage of the entire course content.
Will this guide help me implement reproducible research practices?
Yes, beyond providing quiz answers, this guide reinforces key concepts such as version control, using RMarkdown, sharing reproducible code, and documenting your analysis for transparency and reproducibility.
Conclusion
We hope this guide to Reproducible Research Quiz Answers helps you understand the importance of transparency and reproducibility in research, ensuring your findings are both reliable and verifiable. Bookmark this page for quick reference and share it with your peers. Ready to improve the reproducibility of your research and ace your quizzes? Let’s get started!
Sources: Reproducible Research
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