This lesson is in the early stages of development (Alpha version)

Introduction to The DiscovR Workshop

Overview

Teaching: 15 min
Exercises: 0 min
Questions
  • Who is the workshop for?

  • What will the workshop cover?

  • What else do I need to know about the workshop?

Objectives
  • Set expectations.

  • Meet each other.

  • Introduce the workshop goals.

  • Go over logistics.

DiscovR stands for “Data integration: strategies, concepts, and visuals in R”

Who is this workshop for?

This workshop is for data managers and others working with data who are interested in learning the foundations of data science and coding in R so you can use it in your own work. We believe everyone can learn to code, and that a lot of you will find it very useful for things such as data analysis and plotting.

This workshop is targeted to absolute beginners, and we expect that you have zero data science or coding experience coming in. That being said, you’re welcome to attend the workshop if you already have a coding background but want to learn more!

To provide an inclusive learning environment, we follow The Carpentries Code of Conduct. We expect that instructors, facilitators, and learners abide by this code of conduct, including practicing the following behaviors:

Introducing the instructors and facilitators

Now that you know a little about The Carpentries as an organization, the instructors and facilitators will introduce themselves and what they’ll be teaching/helping with.

Introducing participants

Introduce yourself with your preferred name, role, affiliation, work/research area, and Kenyan name and meaning.

What will the workshop cover?

This workshop will introduce you to exploratory data analysis and effective data visualiation, and how to implement these concepts using the R programming language.

While we will focus primarily on public health applications, what you learn here are programs that are used everyday in computational workflows in diverse fields: microbiology, statistics, neuroscience, genetics, the social and behavioral sciences, such as psychology, economics, and many others.

A workflow is a set of steps to read data, analyze it, and produce numerical and graphical results to support an assertion or hypothesis encapsulated into a set of computer files that can be run from scratch on the same data to obtain the same results. This is highly desirable in situations where the same work is done repeatedly – think of processing data from an annual survey. It is also desirable for reproducibility, which enables you and other people to look at what you did and produce the same results later on. It is increasingly common for people to publish scientific articles along with the data and computer code that generated the results discussed within them.

The programs we will use are:

  1. R: a statistical analysis and data management program,
  2. RStudio: a graphical interface to use R, and
  3. R Markdown: a method for writing reproducible reports.

We’ll use these tools to manage data, perform basic statistical analyses, and make pretty plots!

While the workshop won’t make you an expert, we hope to provide you with a foundational understanding in coding for data analysis and visualization, automating your work, and creating reproducible programs. We also hope to provide you with some fundamentals that you can incorporate in your own work.

At the end, we provide links to resources you can use to learn about these topics in more depth than this workshop can provide.

Asking questions and getting help

One last note before we get into the workshop.

If you have general questions about a topic, please raise your hand to ask it. The instructor will definitely be willing to answer!

For more specific nitty-gritty questions about issues you’re having individually, we use sticky notes to indicate whether you are on track or need help. We’ll use these throughout the workshop to help us determine when you need help with a specific issue (a facilitator will come help), whether our pace is too fast, and whether you are finished with exercises. If you indicate that you need help because, for instance, you get an error in your code (e.g. red sticky), a facilitator will come help you figure things out. Feel free to also call facilitators over through a hand wave if we don’t see your sticky!

Other miscellaneous things

If you’re in person, we’ll tell you where the bathrooms are! Also let us know if there are any accommodations we can provide to help make your learning experience better.

Key Points

  • We follow The Carpentries Code of Conduct.

  • Our fundamental goal is to become more comfortable exploring and working with data.

  • Our workshop goal is to write a sharable and reproducible report.

  • This lesson content is targeted to absolute beginners with no data science or coding experience.