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Activity Number: 475
Type: Invited
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Defense and National Security
Abstract #318487
Title: Integrating Reproducibility into the Undergraduate Statistics Curriculum
Author(s): Mine Cetinkaya-Rundel*
Companies: Duke University
Keywords: reproduciblity ; rmarkdown ; github ; data science ; undergraduate ; computing

The issue of reproducibility often comes up in the context of published research and the need to accompany such research with the data, analyses, software/code necessary to recreate the results. As statistics educators who teach data analysis, we should be instilling best practices in students as early as possible. We advocate for teaching data analysis at all levels of the statistics curriculum using a completely reproducible framework so that the new researchers we train have no other workflow than a reproducible one. Additionally, as statisticians we should be marshaling efforts for promoting reproducible data analysis practices in other disciplines as well. While all this might sound like a tall order at first, modern tools for literate programming (e.g. R Markdown) and systems for version control (e.g. GitHub, Open Science Framework) paired with carefully designed curricula that integrate the use of these tools early and often make this goal easier to attain than ever before. In this talk we will share experiences from undergraduate courses and research experiences teaching and practicing reproducible data analysis. We will also discuss collaborative efforts with non-statistic

Authors who are presenting talks have a * after their name.

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