5  Overview

In order to participate in this workshop, you must complete everything in this pre-workshop section and finish with completing the survey at the end. These tasks are meant to provide everyone with the necessary setup and a shared foundation for the workshop.

Depending on your prior knowledge and skills, these tasks could take between 3-5 hrs to finish, so we suggest planning some time to complete them. While many of the tasks are mostly readings, they are important in making sure you get the most out of the workshop.

Your institution might have special rules or policies around how and if you can install software on work computers. So you also might have to contact IT very early to make sure everything is properly installed and setup.

5.1 Summary of tasks

Here’s a quick overview of the tasks you need to do. Specific details about them are found as you work through the tasks. Most of the time spent on the tasks is on the reading tasks. We include these reading tasks to have you as aware and as well-prepared as we can before the workshop, so that we have a smoother start and so that you benefit more from the improved learning from the earlier and repeated exposure.

Important

Depending on your institution, the installation tasks may require IT approval. This can take some time, sometimes a few weeks even with reminder emails. We suggest starting the tasks early, especially the installation tasks.

Aside from waiting for IT approval, these tasks should take between 3-5 hrs to finish, so we suggest planning a full day to complete them.

1. Read the learning objectives in Section 5.2 for the pre-workshop tasks (below on this page).
2. Read about how to read this website in Section 5.3 (below on this page).
3. Do some reading tasks in Chapter 6.
4. Install the necessary programs and the right versions of those programs in Chapter 7. As mentioned in the callout block above, depending on your institution, this task can take the longest amount of time because you have to contact your IT to install these packages.
5. Read about and navigate R and RStudio in Chapter 8.
6. Install necessary R packages in Chapter 9.
7. Read some of the workshop sections on Git, configure Git on your computer, and create a GitHub account in Chapter 10 as well as run some checks to make sure everything is working. You’ll need to paste this output into the survey later on.
8. Read through the Code of Conduct in Chapter 11.
9. Complete the pre-workshop survey in Chapter 12. This survey is pretty quick, maybe ~10 minutes. There will be some bits from the tasks that you will need to paste into this survey.

5.2 Learning objective

Most of the description of the workshop is in the syllabus that is found in Chapter 1. While you may have signed up to this workshop to learn more about R, you should know that conducting reproducible research goes beyond R and RStudio. Which means we will be spending time using other tools that you will use with R so that you can improve the reproducibility of your research. This workshop is designed to introduce you to doing reproducible research while using R.

In general, these pre-workshop tasks are meant to help prepare you for the workshop and make sure everything is setup properly so the first session runs smoothly. While most of these pre-workshop tasks are meant to prepare you for the workshop, some of them are also designed for learning purposes to enable you to:

1. Describe what R is, how it fits within a research environment, and why researchers increasingly use it.
2. Navigate some of the basic uses and features of RStudio, as well as explain the difference between R and RStudio.
3. Explain the differences between R code, R functions, R scripts, and R packages, and how we will use each of them.
4. Become aware of the tidyverse set of packages, which we will be teaching mostly in this workshop.
5. Become aware of what version control is and what Git is.

5.3 How to read this website

We try to be consistent with the way to present certain information in this website. Specifically, we follow some conventions that you should be aware of:

• Folder names always end with /, for example data/ means the data folder.
• File names always end with their file extension, for example content.md means the file is a Markdown file.
• R variables are always shown as is. For instance, for the code x <- 10, x is a variable because it was assigned with 10.
• Functions always end with (), for instance mean() or read_csv().
• Sometimes functions have their package name appended with :: so that you run the code from the specific package, since we likely haven’t loaded the package with library(). For instance, to install packages from GitHub using the pak package we use pak::pak("user/package_name"). You’ll learn about this more later.

Throughout the many times we’ve taught this and other workshops we get asked a lot of questions. We have a Frequently Asked Questions page for keeping track of some of these questions. Check out this page, maybe your question has already been answered!

Tip

You will be taken through the pre-workshop tasks in order by clicking the arrow at the bottom of each page ➡️