What is R?

R is a programming and analysis environment for statistical computing and graphics. It is based on an ever-expanding set of analytical packages that perform specific analytical, plotting, and other programming tasks. R itself is freeware. On the positive side, it has wonderful analytical and plotting capabilities, and moderate data management capabilities. On the negative side, you get what you pay for, and since R and its associated packages are free there are many curious idiosyncrasies found in R you will experience.

How Does R - and baseR as a Class - Relate to You and Your Academic Goals?

R has become the primary tool for data analysis in the broadly defined fields of natural resources, conservation, and ecology, as well as other fields. Many state and Federal agencies, NGOs, private consulting firms, and others, now use R for analysis of their data. If you are performing research, R is the statistical tool most likely to be employed in the analysis of your personal data.

Thus, instruction in R meets at least two goals related to your academic tenure:

• Employers increasingly use it, making competency in R a valuable tool for employment opportunities; and
• It is now the statistical foundation for achieving your personal research goals.

What are the Course Objectives of baseR?

This online course does not teach specific statistical analyses. Instead, it introduces you to R as an analytical platform, with specific emphasis on the management and manipulation of data in R. Understanding how to manage and manipulate data in R is a necessary precursor to analyzing data in R; the two are inextricably linked.

Thus, course objectives are to:

• Introduce the R computational environment;
  
• Show how R can be used to manage and manipulate data, and
• Prepare data for analysis.

How is baseR Structured?

baseR is an self-paced, online course. Thus, successful completion of the course requires a large degree of personal motivation. There are no lectures. Instruction consists principally of PowerPoints, and a web-based delivery system.

baseR consists of an Introduction and three Modules related to:

• The R Environment;
• Data Management, and
• Data manipulation (see syllabus for Module details).

There are 18 exercises spread across the three Modules.

Timing of the course coincides with Fall and Spring semesters each academic year, meaning that course requirement must be completed within the designated period for each academic year’s semesters.

Analysis with groups of 2-3 of your peers will be strongly encouraged. It is actually one of the best ways to learn R.

How am I - the Student - Evaluated?

The 18 exercises constitute 100% of your grade.

Exercises are scored as 1 or 0. A 1 (one) means you have successfully completed the exercise, including any changes I request after I and/or the course grader review your code. Exercises with errors will be returned for correction, and then re-submitted for re-evaluation. A 0 (zero) means you either did not bother to submit the exercise or you failed to meet the exercise deadline.

All of this means there is no reason you should not obtain an A unless you consistently fail to meet exercise submission deadlines. You can expect about 1 exercise a week (see syllabus for specific exercise deadlines).

baseR is an Online Course - Where do I Find Help if Needed?

Two weekly 1-hr “office labs” are offered, where students can meet with me and /other students for detailed discussion on design and analysis topics and use of R to achieve desired research results. Software such as Google hangouts will be used for interactions with students requiring hands-on help and who are not in residence on the Logan campus.

However, an important part of the baseR instructional package is to teach you how efficiently use the web to find answers to sticky R questions. What I have done personally is develop a “Zen and the Art of R” sense that allows me to rapidly find clues for how to resolve a data management or statistical issue in R. This can only be learned by experimentation on your part; there is no “spoon-fed” answer to any aspect of R.

Are there any Pre-Requisites?

There are no formal pre-requisites, just a personal interest in learning how to use R.

Are There Any Student Required Tools?

All students must have their own portable computer with access to the USU WiFi network. baseR (as well as R as a freeware tool) is designed around individually configured, student-owned and controlled personal computers. Students can thus establish personal profiles, create their own library of R packages, work with whatever R GUI interface (e.g., RStudio, RCommander) they desire, and use a MAC, Windows, or Linux OS; in short, it’s your CPU, and your personal analytical environment. Moreover, office interactions are based on students bringing their CPU and work to my office or a designated meeting location.

Questions?

Feel free to contact me directly via email or stop by my office, NR 126, if you have any questions.

Thomas Edwards, Research Ecologist and Professor, USGS Utah Cooperative Fish and Wildlife Research Unit, and Wildland Resources t.edwards@usu.edu