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R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics

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Date
2014
Authors
Baumer, Ben
Cetinkaya-Rundel, Mine
Bray, Andrew
Loi, Linda
Horton, Nicholas J
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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.
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Journal article
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https://hdl.handle.net/10161/8374
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Scholars@Duke

Cetinkaya-Rundel

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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