R Software Recommendations

The R software is an OpenSource language for statistical analysis. It sets a high standard for being comprehensive (via an extensive array of packages for many specific applications), correct, and easy to use. It is generally considered the standard solution for a broad range of statistical applications. In addition to the software itself, I also highly recommend the IDE RStudio. It provides a highly functional work environment that makes it easy for the statistical to develop and test code, read and organize data, create visual analyses, and to fit a broad range of statistical models. Finally, I recommend that statisticians become familiar with and use the collection of tools for managing and dealing with data that is include in the collection of packages called The Tidyverse.

* R: www.r-project.org
* RStudio: www.rstudio.com
* `tidyverse`: www.tidyverse.com

Keep your software up to date. New releases are made periodically. Features are added and bugs are fixed. Remember that packages in R may change releases independently of R itself. Use the `update` feature under the `Packages` tab in RStudio to manage packages and be sure you are up to date.

`tidyverse` is a collection of packages that provide a unified and comprehensive approach to working with data. If you learn how to use `tidyverse` your code will be clearer and more efficient. You will be using best practices for data management. You will be part of a larger data science community that is continuously brings new technology to its members.

Use one of the two main notebook formats in RStudio; R Markdown or Quarto. This will allow you to write readable and reproducible code.