• When? Friday’s @2:30 - 3:30pm
  • Where? MacLaurin Building room D110
  • What to prepare? Please bring your laptop computer! Also, install R and RStudio prior to the course and following the instructions below on ‘To do before lab 1’.
  • Office hours: My “office hours” will immediately follow lab each week until 5:00pm in MacLaurin Building D110 (assuming there is no class after us). I encourage you to stay and work on the practice problems with your peers and I can answer any questions you have regarding the lab material, assignments, working with your own data etc. during this time.

Facilitators

Marissa Dyck
University of Victoria
School of Environmental Studies
Email: marissadyck@uvic.ca

Jason Fisher
University of Victoria
School of Environmental Studies
Email: fisherj@uvic.ca

Contributors

This workshop is based on content from an R Bootcamp run by Dr. Kevin Shoemaker at University of Nevada Reno (https://github.com/kevintshoemaker/R-Bootcamp)

Kevin Shoemaker
University of Nevada Reno
Department of Natural Resources and Environmental Science
Email: kshoemaker@cabnr.unr.edu

About

The statistical programming software ‘R’ is one of the fundamental tools for modern data exploration and is a useful tool for data processing, statistical analysis, and production of high-quality figures.

This workshop is designed for beginner to intermediate R users and will focus on increasing comfort and familiarity with using R and RStudio, R syntax, and troubleshooting code. We will begin with the basics (what is R? How to install R and RStudio? Navigating and understanding the layout of Rstudio) and continue onto data manipulation and formatting, visualizing data, working with packages, and troubleshooting code. The main goal of the workshop is to ensure participants have enough proficiency and confidence with data operations and programming in R to engage in productive, self-directed learning and problem-solving.

All code will be available as scripts that you can download from this website (at the top of each module page on this website) and load up in RStudio. That way you won’t need to constantly copy and paste from the web!

Course Schedule

Course schedule

To do before lab 1

Please complete the following tasks BEFORE the first lab on Friday January 12th. We have a lot of material to cover in a short time and completing the following tasks will save time at the start of lab and ensure everyone is ready.

Install R and RStudio

Before we dig in and get started with the modules, you should install R and RStudio. Even if you have installed R and RStudio before you should ensure you have the latest version, if you aren’t sure how to check use the links to install the programs again just to be sure and we will cover how to check your version during the workshop. Here are some links to help you get started:

Download and install R
Download and install RStudio (use free version!)

Download cheat sheets

Also, it can be very helpful to print out R ‘cheat sheets’ and bring that with you or save them as PDFs to your hard drive. We will try to have some physical copies available during lab. Here are some links:

Base R cheatsheet
R reference card
Various R cheatsheets (I recommend the following 3: ‘Data tidying with tidyr’, ‘Data transformation with dpylr’, ‘Apply functions with purrr’, and ‘Data visualization with ggplot2’ cheat sheets for this course)

Download data

To ensure we maximize time in lab please also download the data files for this course from the Data tab and save this in a folder on your hard drive. We will move these to a specific folder for the course when we cover folder organization on the first day of lab

Right click (or command-click for MAcs) each file. The .txt files will open in a viewer window and you will need to right click to save them. The .csv files should download directly in your downloads folder and you can move them where you want to save them. Important DO NOT change the file names.

Take pre course survey

Once you’ve downloaded R, RStudio, and the associated cheat sheets and data for this course please complete the pre-course survey. This will act as an indicator that you have completed the necessary tasks to prepare for the first lab and help me gauge everyone’s experience level and the effectiveness of this course later on.

pre-course survey

Go to first lab

Okay, now we’re ready to go!

–go to first lab module

Post course survey

Please return and complete this post course survey at the end of the semester

Before you leave today please take a few moments to complete the post-course survey.