This is the course page for the Summer 2021 iteration of the REAL R Short Course. Here, we will share all of the course materials and information in a central location.
We will meet synchronously via Zoom on Wednesdays from July 21 through September 8 (for a total of 8 sessions).
Eastern time: 1PM - 2PM
Central time: 12 noon - 1PM
Mountain time: 11AM - 12 noon
Pacific time: 10AM - 11AM
First, we will work on Getting Started, and will walk through computer set-up preliminaries.
Second, we will work through R, RStudio, and RMarkdown, where we'll take our first foray into R.
Together, these two parts will serve as a starting point and foundation for the rest of our work together, and will set us up for discussions of graphing in Days 2 and 3!
Here is the Github location of the Day 2 Prep Work - the file you need is named Day2PrepWork.Rmd - this is an RMarkdown document. If you are using Github Desktop and have cloned the class repository (REALshortcourse_Summer2021), you should be able to find this within the new Day2PrepWork folder. You'll want to open this file in RStudio, and then edit/run code within the document itself. The document provides the instructions needed as you go. Have fun, and don't hesitate to reach out if you are running into difficulties!
Major topic - plotting in R
We will work through the Day 2 lesson together - which will cover the importing of data from external files, all the way through using ggplot2 to build scatterplots and barplots.
It is unlikely that we'll get to the Day 2 activity during our synchronous time, but it is here for your reference even if we don't!
Here is the Github location of the Day 2 homework - the "Day2Homework" folder contains both this RMarkdown file as well as the .csv file with the necessary data. Happy plotting!
Major topic - plotting in R, continued
We will work through the Day 3 lesson together. We'll review our initial plotting skills from last week's session, explore new ways to manipulate our data as we plot, and learn how to customize our plotting outputs.
Here is the Github location of the Day 3 homework / Day 4 prep work - with both a RMarkdown file and a .csv data source. Good luck!
Major topic - data manipulation using dplyr
We will work through the dplyr_part_1 activity as a group.
In the Day 4 folder in Github, there is an activity titled dplyr_superhero - you may not be able to fully complete it without the material planned for Day 5, but feel free to get started on the questions relating to what you learned in Day 4!
In addition, we are hoping to hear from you about what is working well and not as well for you as members of the learning community - please complete this short survey when you have a chance!
Major topic - data manipulation using dplyr, continued
We will work through the dplyr_part_2 activity as a group. (Note that this activity is found in the Day 4 folder!)
In the Day 4 folder in Github, there is an activity titled dplyr_superhero - you should now be equipped to tackle this activity!
Major topic - data transformation using mutate() and summarize()
We will work through the mutate_summarize activity as a group - .rmd file here.
You should attempt to complete the practice problems found at the end of the Day Six lesson.
Major topic - working with categorical data in factors with forcats
We will work through the categoricalvariables activity as a group - .rmd file here.
Major topic - Linear Regressions and Modeling
We will work through the regression activity as a group - .rmd file here.
Congratulations - you've made it through the short course!!
Here, we will provide information about the members of the learning community, so you can get to know your colleagues.
The REAL Steering Committee has 8 members - listed here:
Abha Ahuja - Minerva Schools at KGI (abha@minerva.kgi.edu)
Christine Booth - University of Nebraska - Lincoln (cbooth2@unl.edu)
Natalia Caporale - University of California - Davis (ncaporale@ucdavis.edu)
Robert Erdmann - University of Minnesota Rochester (rerdmann@r.umn.edu)
Robert Furrow - University of California - Davis (refurrow@ucdavis.edu)
Joel Ledford - University of California - Davis (jmledford@ucdavis.edu)
Kelsey Metzger - University of Minnesota Rochester (kmetzger@r.umn.edu)
Emily Weigel - Georgia Institute of Technology (emily.weigel@biosci.gatech.edu)
An important attribution note - many of the lessons that we are using in this short course are lightly modified versions of lessons originally developed by steering committee member Joel Ledford for his "Data Science for Biologists" course (BIS 15L at the University of California - Davis).