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R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics

dc.contributor.author Baumer, B
dc.contributor.author Cetinkaya-Rundel, M
dc.contributor.author Bray, A
dc.contributor.author Loi, L
dc.contributor.author Horton, NJ
dc.date.accessioned 2014-02-27T16:39:55Z
dc.date.issued 2014
dc.identifier http://www.escholarship.org/uc/item/90b2f5xh
dc.identifier.issn 1933-4214
dc.identifier.uri http://hdl.handle.net/10161/8374
dc.description.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.
dc.relation.ispartof Technology Innovations in Statistics Education
dc.title R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics
dc.type Journal article
pubs.author-url http://www.escholarship.org/uc/item/90b2f5xh
pubs.issue 1
pubs.organisational-group Duke
pubs.organisational-group Statistical Science
pubs.organisational-group Trinity College of Arts & Sciences
pubs.publication-status Published
pubs.volume 8


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