JSM 2019 Continuing Education Course, Biometrics Section, 2019-07-27 8:30 am - 5 pm

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Reproducible Computing


Success in statistics and data science is dependent on the development of both analytical and computational skills.

This workshop will cover:

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.


Time Activity Slides
08:30 - 09:00 Welcome html, pdf
09:00 - 09:40 Literate programming html, pdf
09:40 - 10:15 Naming & Organization html, pdf
10:15 - 10:30 Coffee break  
10:30 - 12:30 Version control with Git and GitHub html, pdf
12:30 - 14:00 Lunch break  
14:00 - 14:30 Scaling reproducible projects html, pdf
14:30 - 15:15 Introduction to make html, pdf
15:15 - 15:30 Coffee break  
15:30 - 16:30 make in action  
16:30 - 17:00 Parting remarks html, pdf

Topic Details

Welcome, literate programming, and naming

Organization and version control with Git and GitHub

Scaling reproducible projects + Make

Computing requirements

An R + RStudio computing environment will be provided for all students via RStudio Cloud. All that will be needed the day of the event is a laptop and a Google Account that can be used for authentication.


Colin Rundel - University of Edinburgh, Duke University

Colin recently started as a Lecturer in the School of Mathematics at the University of Edinburgh. Prior to this position he was an a Assistant Professor of the Practice in the Department of Statistical Science at Duke University. He has developed and taught a number of Statistical Computing courses for undergraduate, master’s and Ph.D. levels students. His pedagogical and research interests are in the area of statistical computing, data science, and spatial statistics.



Materials in this repository are licensed under CC Attribution 4.0 International.