R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics
Abstract
Nolan and Temple Lang argue that “the ability to express statistical computations
is an es- sential skill.” A key related capacity is the ability to conduct and present
data analysis in a way that another person can understand and replicate. The copy-and-paste
workflow that is an artifact of antiquated user-interface design makes reproducibility
of statistical analysis more difficult, especially as data become increasingly complex
and statistical methods become increasingly sophisticated. R Markdown is a new technology
that makes creating fully-reproducible statistical analysis simple and painless. It
provides a solution suitable not only for cutting edge research, but also for use
in an introductory statistics course. We present experiential and statistical evidence
that R Markdown can be used effectively in introductory statistics courses, and discuss
its role in the rapidly-changing world of statistical computation.
Type
Journal articlePermalink
https://hdl.handle.net/10161/8374Collections
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Mine Cetinkaya-Rundel
Professor of the Practice of Statistical Science
I am a Professor of the Practice and the Director of Undergraduate Studies at the Department
of Statistical Science and an affiliated faculty in the Computational Media, Arts,
and Cultures program at Duke University. My work focuses on innovation in statistics
and data science pedagogy, with an emphasis on computing, reproducible research, student-centered
learning, and open-source education. I work

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