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The Carpentries teach foundational coding, and data science skills to researchers worldwide. This GitHub repository generates the Software Carpentry lesson website "Introduction to R for non-programmers using inflammation data." The lesson website can be viewed here. Making changes in this GitHub repository allows us to change the content of the lesson website.
The following people are maintainers for this lesson, and are responsible for determining which changes to incorporate into the lesson:
- Rohit Goswami (@haozeke)
- Hugo Gruson (@Bisaloo)
- Isaac Jennings (@isaac-jennings)
Alumni:
- Daniel Chen (@chendaniely)
- Diya Das (@diyadas)
- Katrin Leinweber (@katrinleinweber)
The goal of this lesson is to teach novice programmers to write modular code to perform a data analysis. R is used to teach these skills because it is a commonly used programming language in many scientific disciplines. However, the emphasis is not on teaching every aspect of R, but instead on language agnostic principles like automation with loops and encapsulation with functions (see Best Practices for Scientific Computing to learn more). This lesson is a translation of the Python version, and is also available in MATLAB.
The example used in this lesson analyzes a set of 12 data files with inflammation data collected from a trial for a new treatment for arthritis (the data was simulated). Learners are shown how it is better to create a function and apply it to each of the 12 files using a loop instead of using copy-paste to analyze the 12 files individually.
We value your contributions. How to contribute to this lesson is outlined in CONTRIBUTING.md. If you have questions about our contributing guidelines, please create a new issue in the issues tab and one of the maintainers will respond.
Please see https://github.com/carpentries/lesson-example
for instructions on formatting, building, and submitting lessons,
or run make in this directory for a list of helpful commands.
If you have questions or proposals, please send them to the r-discuss mailing list.