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# DSS Computing Bootcamp

This is a 3 hour computing bootcamp for incoming PhD and MS
students to the Department of Statistical Science at Duke University.

The workshop will cover the following topics:

## Introduction to the department computing eco-system

- Account activation and access to departmental servers.
- Discussion of how to responsibly use distributed computing resources.

## Introduction to Reproducible Research

- Recognize the problems that reproducible research helps address, featuring brief discussion of case studies case studies of (lack of) reproducibility gone wrong.
- Identify pain points in getting your analysis to be reproducible.
- The role of documentation, sharing, automation, and organization in making your research more reproducible.
Introducing some tools to solve these problems, specifically R/RStudio/RMarkdown.

## Organizing your project to facilitate Reproducible Research

- Organize projects and folders to enable reproducibility and reusability
- Understand the structure of data files and the importance of documenting all changes made
- Using these practices, create a reproducible project workflow using R/RStudio/RMarkdown.

## Version control

- Introduction to git/GitHub as a version control tool.
- Practice initiating a project directory, making / committing / pushing changes, and creating a pull request to someone else's remote repository.
- Discuss the role of version control in reproducibility of one's own project as well as in collaborative projects.

## Acknowledgments 

- [Reproducible Science Curriculum Hackathon](https://github.com/Reproducible-Science-Curriculum/Reproducible-Science-Hackathon-Dec-08-2014)

- [GitHub's ssh help pages](https://help.github.com/categories/56/articles)

- [Software Carpentry Project](http://software-carpentry.org/)

- Karl Broman - [Wisc's Tools4RR](http://kbroman.org/Tools4RR/)

- Karl Broman - [Reproducible Research](https://www.biostat.wisc.edu/~kbroman/presentations/repro_research_withnotes.pdf)

- Grolemund and Wickham - [R for Data Science](http://r4ds.had.co.nz/)

- Case studies:
    - Science retracts gay marriage paper without agreement of lead author, http://news.sciencemag.org/policy/2015/05/science-retracts-gay-marriage-paper-without-lead-author-s-consent
    - Seizure study retracted after authors realize data got "terribly mixed", http://retractionwatch.com/2013/02/01/seizure-study-retracted-after-authors-realize-data-got-terribly-mixed/
    - Bad spreadsheet merge kills depression paper, quick fix resurrects it, http://retractionwatch.com/2014/07/01/bad-spreadsheet-merge-kills-depression-paper-quick-fix-resurrects-it/