https://github.com/EEOB-BioData/R-Data-Skills

R section of the EEOB/BCB 546X class
https://github.com/EEOB-BioData/R-Data-Skills

Last synced: about 1 month ago
JSON representation

R section of the EEOB/BCB 546X class

• Host: GitHub
• URL: https://github.com/EEOB-BioData/R-Data-Skills
• Owner: EEOB-BioData
• License: other
• Created: 2017-01-18T23:40:54.000Z (almost 8 years ago)
• Default Branch: 2016.06
• Last Pushed: 2017-10-11T18:04:28.000Z (about 7 years ago)
• Last Synced: 2024-08-02T11:22:26.028Z (4 months ago)
• Language: HTML
• Homepage: https://eeob-biodata.github.io/R-Data-Skills/
• Size: 30.1 MB
• Stars: 0
• Watchers: 4
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Citation: CITATION
  • Authors: AUTHORS

Awesome Lists containing this project

• awesome-bacteria - R-Data-Skills - R for Reproducible Scientific Analysis (2016). (Educational resources / R & RStudio)

README

        
R for Reproducible Scientific Analysis

======================================

An introduction to R for non-programmers using the [Gapminder][gapminder] data.

Please see  for a rendered version of this material,

[the lesson template documentation][lesson-example]

for instructions on formatting, building, and submitting material,

or run `make` in this directory for a list of helpful commands.

The goal of this lesson is to teach novice programmers to write modular code

and best practices for using R for data analysis. R is commonly used in many

scientific disciplines for statistical analysis and its array of third-party

packages. We find that many scientists who come to Software Carpentry workshops

use R and want to learn more. The emphasis of these materials is to give

attendees a strong foundation in the fundamentals of R, and to teach best

practices for scientific computing: breaking down analyses into modular units,

task automation, and encapsulation.

Note that this workshop focuses on the fundamentals of the programming

language R, and not on statistical analysis.

A variety of third party packages are used throughout this workshop. These

are not necessarily the best, nor are they comprehensive, but they are 

packages we find useful, and have been chosen primarily for their 

usability.

Maintainers:

* [Tom Wright][wright_tom]

* [Naupaka Zimmerman][zimmerman_naupaka]

[gapminder]: http://www.gapminder.org/

[wright_tom]: http://software-carpentry.org/team/#wright_thomas

[zimmerman_naupaka]: http://software-carpentry.org/team/#zimmerman_naupaka