R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics
dc.contributor.author | Baumer, Ben | |
dc.contributor.author | Cetinkaya-Rundel, Mine | |
dc.contributor.author | Bray, Andrew | |
dc.contributor.author | Loi, Linda | |
dc.contributor.author | Horton, Nicholas J | |
dc.date.accessioned | 2014-02-27T16:39:55Z | |
dc.date.issued | 2014 | |
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.identifier | ||
dc.identifier.issn | 1933-4214 | |
dc.identifier.uri | ||
dc.relation.ispartof | Technology Innovations in Statistics Education | |
dc.title | R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics | |
dc.type | Journal article | |
duke.contributor.orcid | Cetinkaya-Rundel, Mine|0000-0001-6452-2420 | |
pubs.author-url | ||
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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