Introduction to R

COURSE SESSION

Target Audience:

Biologists who collect and analyze data.

Summary and Objectives:

R is a free software environment for statistical computing and graphics. R is an ever-expanding set of analytical packages that has become the primary tool for data analysis in the broadly defined fields of ecology and conservation, as well as others. This online course provides self-paced instruction comprising five sections that introduce you to:

  1. Introduction to baseR [3 modules]
  2. The R Environment [8 Modules]
  3. Basics of Data Management [9 Modules]
  4. Data Manipulation in R [9 Modules]
  5. Basic Graphs in R [7 Modules]

Materials consists of PowerPoints linked with video instruction and an eBook entitled "A Primer on the Management and Manipulation of Ecological Data Using R." Example data sets and code are provided. Twenty-two (22) exercises completed in R Markdown are associated with the course. On completion of the course, students will be well situated to begin advanced statistics courses that rely on R.

Course Structure:

There is a required orientation webinar during the first week. Otherwise, there are no mandatory virtual sessions. Online office hours occur each Friday and attendance is optional. Despite the independent coursework, there are quarterly milestones that participants must meet. Expect to spend approximately 4 - 5 hours per week to complete assignments.

Upon completion of this course, participants will be able to:

  • Find and install R.
  • Use GUI interfaces (e.g., RStudio).
  • Install and use packages in R.
  • Follow data management principles to manipulate data in R (e.g., data preparation, creation/elimination of variables, and data organization to useable forms).
  • Produce basic graphs (scatter plots, line plots, bar charts, histograms) to summarize data.
  • Produce homework reports in R Markdown.
  • Manage and manipulate data in R to help achieve the goals of a broad- based analytical strategy.
Course Short Name
FWS-CSP4201
Course Type
Blended
Training Tuition Cost
$1990.00
Duration
80 hours
Training Credit Hours
8.00
Semester Hours
0.00

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