Title
R markdown: integrating a reproducible analysis tool into introductory statistics
Contributors
Creator: Horton, Nicholas J. (Amherst College. Department of Mathematics and Statistics)
Creator: Baumer, Benjamin (Smith College)
Creator: Çetinkaya-Rundel, Mine (Duke University)
Creator: Bray, Andrew (Smith College)
Creator: Loi, Linda (Smith College)
Creator: Baumer, Benjamin (Smith College)
Creator: Çetinkaya-Rundel, Mine (Duke University)
Creator: Bray, Andrew (Smith College)
Creator: Loi, Linda (Smith College)
Genre
Publication Information
Published Version
Date Issued
2014
Note
Final published version appeared in Technology Innovations in Statistics Education.
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.
Subject
Language
English
Files referenced in this Digital Object
- Download Horton_2014_rmarkdown.pdf
- Download Horton_2014_rmarkdown.pdf
- Download Horton_2014_rmarkdown.pdf
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