4 Work with R

logo R by Monceau and by Duncan C are licensed under CC BY-NC 2.0, by Marco Isler CC BY-ND 2.0, by Joanna Poe CC BY-SA 2.0

R is an open source language and environment for statistical computing and graphics [5], ranked by IEEE in 2020 as the 6th most popular programming language (Python, Java, and C are the top three) [6]. If you are new to R, some of its best features, paraphrasing Wickham [2], are:

  • R is free, open source, and available on every major platform.
  • R packages provide effective tools for data analysis and visualization.
  • More than 17,750 open-source R packages are available (Jul 2021). Many are cutting-edge tools.

RStudio, an integrated development environment (IDE) for R, includes a console, editor, and tools for plotting, history, debugging, and workspace management as well as access to GitHub for collaboration and version control [7].

4.2 Create a script

Launch your workshop project—workshop.Rproj or other name that you selected—to start the R session. Always work in an RStudio project environment.

Create a script by:

  • Use the pulldown menu, File > New File > R Script
  • File menu > Save As…
  • In the dialog box, navigate to your scripts directory, type a file name, for example, 01-R-basics.R (file names in R can start with numerals), and Save.

We suggest you start a new R script for each tutorial and save it to the scripts directory. For example, at the end of the workshop, your scripts directory might contain the following files:

        \scripts    
            \01-R-basics.R    
            \02-getting-started.R    
            \03-case-study-programs.R    
            \04-case-study-students.R     
            etc.

4.3 New to R?

Prerequisites should be completed before proceeding. By the end of the workshop, our R beginners will have made progress on two or possibly three tutorials:

If there is still time remaining, continue to any tutorial listed in the After the workshop section.

4.4 Familiar with R?

Prerequisites should be completed before proceeding. By the end of the workshop, our more experienced R users will have made substantive progress on two or possibly three tutorials:

If there is still time remaining, continue to any tutorial listed in the After the workshop section.

4.5 After the workshop

At his point, your learning is self-directed. Choose the skills you want to continue working on. We have tutorials for graph basics and data basics, for continuing the case study tour of midfieldr, and detailed vignettes for closer study of the midfieldr functionality and student unit record analysis.

4.5.1 R skills

The basic skills tutorials take about an hour each.

4.5.2 Case study

The case study is a quick tour of a typical workflow using Student Unit Record (SUR) data. This is a “big picture” development—functions are used without detailed explanations or development so that we can focus on the logic of the analysis.

4.5.3 Vignettes

Deep dive into the midfieldr functionality. The work flow follows the same general pattern as the quicker case study, but pauses to explore each function in more detail, exploring the arguments and strategies for use. In general, each tutorial is self-contained so you may enter at almost any point.


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