Preface

I have taught BASV 316, Introductory Methods of Analysis, online for the University of Arizona in Sierra Vista since 2010 and enjoy working with students on research methods. From the start, I wanted students to work with statistics as part of our studies and carry out the types of calculations that are discussed in the text. As I evaluated statistical software I had three criteria:

  • Open Educational Resource (OER). It is important to me that students use software that is available free of charge and is supported by the entire web community.

  • Platform. While most of my students use a Windows-based system, some use Macintosh and it was important to me to use software that is available for all of those platforms. As a bonus, most OER software is also available for the Linux system, though I am not aware of any of my students who are using Linux. Finally, I occasionally have students who are not able to load software on their personal computers (think: Chromebook) so I needed an online capability.

  • Longevity. I wanted a system that could be used in other college classes or in a business setting after graduation. That way, any time a student spends learning the software in my class will be an investment that can yield results for many years.

R (just a single letter, R) met those objectives and that is the software I chose to use. This manual started as a series of six lab exercises using R but has grown over the years to the ten topics covered in this edition. Moreover, R is a recognized standard for statistical analysis and could be easily used for even peer-reviewed published papers. It is my hope that students will find the labs instructive and they will then be able to use R for other classes.

This lab manual is written with Bookdown tools in RStudio. It is published under a Creative Commons 0 Universal license, essentially “public domain,” (see [Creative Commons License]) with a goal that other instructors can modify and use it to meet their own needs. The source can be found at GITHUB and I always welcome comments. Finally, it was written with base R (R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.).

–George Self