Wednesdays from May 1 - June 12, 2019
9:00 am - 12:30 pm
Instructors: Harshpreet Chandok, Sue McClatchy, Neil Kindlon, Samir Amin, Preeti Bais, Ravi Pandey, Pariksheet Nanda, Lucas Lochovsky
Helpers: Annat Haber
This intermediate R series follows R for Data Science by Hadley Wickham and Garrett Grolemund of RStudio. This series will teach you how to do data science with R. You’ll learn how to transform, visualize and model your data. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. If you have already taken our R for Reproducible Scientific Analysis workshop, you meet the prerequisite for this course.
This series is open to those from UCHC, UConn, and JAX who meet the prerequisite for competence with R.
Where: UCHC Center for Quantitative Medicine, 195 Farmington Ave, Farmington CT. Get directions with OpenStreetMap or Google Maps.
When: Wednesdays from May 1 - June 12, 2019. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They should have a few specific software packages installed (listed below).
Code of Conduct: Everyone who participates is required to conform to the Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email susan.mcclatchy@jax.org for more information.
Please be sure to complete these surveys before and after the workshop.
| 9:00 | Welcome and introductions |
| 9:15 | Introduction to Data Exploration |
| 9:55 | Data Visualisation |
| 10:45 | Coffee |
| 11:00 | Data Visualisation (continued) |
| 12:25 | Wrap-up |
| 12:30 | End |
| 9:00 | Workflow: basics |
| 9:30 | Data Transformation |
| 10:45 | Coffee |
| 11:00 | Data Transformation (continued) |
| 12:25 | Wrap-up |
| 12:30 | End |
| 9:00 | Workflow: scripts |
| 9:30 | Exploratory Data Analysis |
| 10:45 | Coffee |
| 11:00 | Exploratory Data Analysis (continued) |
| 11:25 | Workflow: projects |
| 11:40 | Wrap-up |
| 11:45 | End |
| 9:00 | Introduction to Data Wrangling |
| 9:45 | Tibbles |
| 10:00 | Data Import |
| 10:45 | Coffee |
| 11:00 | Tidy Data |
| 12:25 | Wrap-up |
| 12:30 | End |
| 9:00 | Relational Data |
| 10:15 | Strings |
| 10:45 | Coffee |
| 11:00 | Strings (continued) |
| 12:25 | Wrap-up |
| 12:30 | End |
| 9:00 | Factors |
| 10:15 | Dates and Times |
| 10:45 | Coffee |
| 11:00 | Introduction to Programming |
| 11:30 | Pipes |
| 12:00 | Functions |
| 12:25 | Wrap-up |
| 12:30 | End |
| 9:00 | Vectors |
| 10:20 | Iteration |
| 10:45 | Coffee |
| 11:00 | Introduction to Modelling |
| 11:30 | Model Basics |
| 12:00 | Model Building |
| 12:25 | Wrap-up |
| 12:30 | End |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
To participate in a workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager (e.g. for Debian/Ubuntu
run sudo apt-get install r-base and for Fedora run
sudo dnf install R). Also, please install the
RStudio IDE.