A Series of R Workshops

by Melinda Higgins, Ph.D.

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This "book" is the assembly of the materials compiled for the "Series of R Workshops" held Spring 2016 at Emory University - School of Nursing. These workshops were led by Melinda Higgins, Ph.D., associate research professor and senior biostatistician.

The Series for Spring 2016 is currently planned to have 4 workshops - each 2 hours long with a focus on hands-on learning using R and RStudio. These workshops will be introductory and provide skills necessary to begin to be comfortable working with R and RStudio performing data analysis and writing research reports. R is a wonderful programming language for Data Analysis, Graphics and much more.

"However, with great power comes great responsibility!"

R has a steep learning curve. It was not designed to have a point-and-click menu driven interface with canned procedures. Instead it is a rich language for data manipulation and analysis with statistical functions and methods embedded in it's core. The rewards are definitely worth the effort. PLUS, IT IS FREE and is supported by literally hundreds of thousands of users and developers worldwide. No other widely-used software can make these claims.

Four R Workshops and Projected Goals

  1. 1/22/2016 (and makeup 02/17/2016) "Introduction to R, RStudio and Working in the R Environment"

    • Goal 1: Be able to open and work with R and RStudio on your own computer (or one you have access to) - initial familiarization with R, RStudio interface and R Environment
    • Goal 2: Initial understanding of what "packages" are, how to load them and use them
    • Goal 3: Initial understanding of where and how to get help

  2. 2/19/2016 "Introductory Data Management, Statistical Analyses, and Graphics with R"

    • Goal 1: Further improvement of skills for working with R, the RStudio interface and configuring your R Environment
    • Goal 2: Read data into and Save data and results out of R/RStudio
    • Goal 3: Run simple statistical summaries and analyses and make simple plots

  3. 3/25/2016 "Reproducible Research with R (combining data + analysis + documentation seamlessly)

    • Goal 1: Initial understanding of what Reproducible Research practices are and why they are important
    • Goal 2: Initial understanding of RMarkdown and how to use it to create HTML, PDF or Microsoft WORD formatted reports
    • Goal 3: Initial understanding of "cloud-based" repositories for interacting with and storing data, statistical results, and associated documentation.

  4. 4/22/2016 "Getting Started with Statistical Modeling with R"

    • Goal 1: Initial understanding of primary data structures and objects within R
    • Goal 2: Initial understanding of running descriptive univariate and bivariate statistics
    • Goal 3: Initial understanding of simple statistical tests such as t-tests, chi-square tests and linear regression models