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2021 Virtual Dates:
Week 1: April 19-22, 2021
Week 2: April 26-29, 2021

Optional Four-Part Workshop

"Scientific Data Analysis with R: A Workshop to Support the Use of R in Everglades Research"

Dates & Times

This eight-hour workshop is divided into four, two-hour sessions conducted via Zoom over a two-week period.

Instruction will be delivered sequentially, and data used in exercises build throughout each session, so you should plan to participate in all four parts. If you miss a session, you may continue participating in subsequent sessions, however, there is no fee reduction for missed portions. You must be a registrant of GEER to participate.

Monday, April 19, 2021 10:00am–12:00pm (Part 1 of 4)
1:00pm–3:00pm (Part 2 of 4)
Monday, April 26, 2021 10:00am–12:00pm (Part 3 of 4)
1:00pm–3:00pm (Part 4 of 4)
Attendance Limit 25 people
Cost to Participate $150/person (If registered and paid by March 5, 2021)
$195/person (If registered and paid after March 5, 2021)
Workshop Overview

The free R software environment and associated packages have become powerful and commonly used tools to organize, analyze and visualize environmental and ecological data. Learning how to use R is difficult despite the large amount of online training on the software and associated packages. In this workshop, the focus will be on an introduction to R emphasizing data that are typical of Everglades research. The workshop will not detail statistical analyses but rather seek to improve skills related to organizing and summarizing data, visualizing data, and making routine analysis tasks simpler. Additional videos will be available to provide supplementary details and information on other topics that might be of interest to workshop participants.

Benefits of Participating
  • Attendees will receive eight hours of personalized instruction by an R expert
  • Sessions are spread over two days with two sessions per day to prevent Zoom fatigue
  • Data sets similar to those arising in Everglades research will be used to illustrate methods
  • Attendees may use their own data although the primary focus will be on the data sets provided
  • Content will be delivered in short presentations followed by hands-on exercises
  • Attendance is limited to 25 people to maximize interaction with the instructor
  • Learn how to use R to create graphs and charts that communicate results and inform decision makers

This workshop provides a valuable opportunity to increase your problem-solving skills and if entering the job market, further enhance your marketability to prospective employers.

Requirements for Participating

Prior to the course, participants will download and install R and RStudio. In addition, participants will be asked to review several introductory videos that describe how to install the programs and R packages. Data files, scripts, and examples should be downloaded prior to the first day. The workshop will involve four modules over a two-day period. The instructor will be available at additional times during the conference to help participants with coding and analysis.

To maximize the benefits of participating, attendees need to:

  • Have a computer at their immediate disposal
  • Review several introductory videos that describe how to install the programs and R packages. Data files, scripts, and examples should be downloaded prior to the first day.
  • Download and install R and RStudio at and
  • Be available for all sessions (Parts 1-4) scheduled 10:00am – 12:00pm & 1:00pm – 3:00pm on Monday, April 19 & April 26
  • Log into each workshop Zoom session 10 minutes prior to start time for a tech run-through

Questions? Email Dr. Smith at:

About the Instructor
Dr. Eric Smith

Dr. Eric Smith, Professor

Virginia Tech, College of Science
Department of Statistics
Blacksburg, VA

All workshop sessions will be led by Dr. Eric Smith. He is a long-time user of R and has been teaching R in his graduate and undergraduate courses. Besides instruction at Virginia Tech, he has taught short courses for the U.S. Fish and Wildlife Service and USGS on study design and also on multivariate analysis of environmental data. His familiarity with Everglades research and data comes from several research projects with scientists at SFWMD and Florida Gulf Coast University. He has also served on the National Academy of Sciences, Engineering and Medicines’ panel that reviewed Everglades restoration progress.