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Activity Number:
218187 - Reproducible Computing (ADDED FEE)
Type: Professional Development
Date/Time: Saturday, July 27, 2019 : 8:30 AM to 5:00 PM
Sponsor: ASA
Abstract #308032
Title: Reproducible Computing (ADDED FEE)
Author(s): Colin Rundel*
Companies: Duke University

Success in statistics and data science is dependent on the development of both analytical and computational skills. This workshop will cover:

- Recognizing the problems that reproducible research helps address. - Identifying pain points in getting your analysis to be reproducible. - The role of documentation, sharing, version control, automation, and organization in making your research more reproducible. - Introducing tools to solve these problems, specifically R, RStudio, RMarkdown, git, GitHub, and make. - Strategies for scaling these tools and methods for larger more complex projects.

Workshop attendees will work through several exercises and get first-hand experience with using relevant tool-chains and techniques, including R/RStudio, literate programming with R Markdown, automation with make, and collaboration and version control with git/GitHub.

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

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