1.Suppose I conduct a study and publish my findings. Which of the following is an example of a replication of my study?
1 point
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.
I take my own data, analyze it again, and publish new findings.
An investigator at another institution conducts a study addressing a different scientific question and publishes her findings.
2.Which of the following is a requirement for a published data analysis to be reproducible?
1 point
The data analysis is conducted using R.
The analysis is conducted on a variant of the Unix operating system.
The full computer code for doing the data analysis is made publicly available.
The investigator’s final publication is made available free of charge.
3.Which of the following is an example of a reproducible study?
1 point
The study’s original authors re-run their computer code on their analytic data and confirm publicly that the findings match those of the published results.
The study’s analytic data are publicly available, but the computer code is not.
The study’s analytic data and computer code are not publicly available, but the study was simple enough to be repeated by an independent investigator.
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.
4.Which of the following is a reason that a study might NOT be fully replicated?
1 point
The original study had null findings.
The original study was published in a high impact journal and is considered authoritative.
The original study was conducted by a well-known investigator.
The original study was opportunistic in its timing and it would be difficult to find a similar context in which to repeat it.
5.Which of the following is a reason why publishing reproducible research is increasingly important?
1 point
New technologies are increasing the rate of data collection, creating datasets that are more complex and extremely high dimensional.
The statistical methods for most studies can be accurately described using plain language.
Computing power is limited today, making it difficult to apply sophisticated statistical methods.
Most studies today are small-scale and easily replicated.
6.What is the role of processing code in the research pipeline?
1 point
It conducts the statistical analysis of the primary outcome.
It transforms the measured data into analytic data.
It transforms the computational results into figures and tables.
It transforms the analytic data into computational results.
7.Which is a goal of literate statistical programming?
1 point
Ensure that data analysis documents are always exported in PDF format.
Separate figures and tables from other data analytic summaries.
Combine explanatory text and data analysis code in a single document.
Require that data analysis summaries are always written in LaTeX.
8.What does it mean to weave a literate statistical program?
1 point
Transform a literate program from R to python.
Compress the literate program so that it takes up less space.
Transform the literate program into a human readable document.
Transform the literate program into a machine readable code file.
9.Which of the following is required to implement a literate programming system?
1 point
A web server for publishing documents.
A Unix-based computer system.
A program that views PDF files.
A programming language like R.
10.What is one way in which the knitr system differs from Sweave?
1 point
knitr was developed by Friedrich Leisch.
knitr is written in python instead of R.
knitr lacks features like caching of code chunks.
knitr allows for the use of markdown instead of LaTeX.
Related Questions & Answers:
Module Review (Quiz-1) Module Review >> Google Cloud Platform Big Data and Machine Learning Fundamentals TOTAL POINTS 5 1.What are the common ... Read more...
Module Review (Quiz-2) Module Review >> Google Cloud Platform Big Data and Machine Learning Fundamentals TOTAL POINTS 7 1.Complete the following: ... Read more...
Module Review (Quiz-3) Module Review >> Astronomy: Exploring Time and Space TOTAL POINTS 5 1.Which of the below are the core services ... Read more...
Module Review (Quiz-4) Module Review >> Google Cloud Platform Big Data and Machine Learning Fundamentals TOTAL POINTS 2 1.Relational databases are a ... Read more...
Module Review (Quiz-5) Module Review >> Google Cloud Platform Big Data and Machine Learning Fundamentals TOTAL POINTS 1 1.If you have an ... Read more...
Week 2 Quiz Week 2 Quiz >> Reproducible Research TOTAL POINTS 5 1.Who created Markdown? 1 point Hadley Wickham John Gruber Robert ... Read more...