Preface

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This book is a compilation of teaching content and lab activities that I have amassed like a digital hoarder during my time teaching BIOL 217 (Quantitative Biology) and BIOL 678 (Advanced Quantitative Biology) at SUNY Oneonta. The book started as a collection of R scripts that I eventually converted into web-pages under the former course websites using rmarkdown, and now finally into an e-document (thanks to bookdown!) that is without doubt The Worst Stats Text eveR. I use Chapters 1 - 15 for the undergraduate class and the whole book in the grad-level class.

The purpose of this book is to provide a tutorial survey of commonly used statistical tools in R for undergraduate students interested in biology. On any given week, our focus will be to demonstrate one or more techniques in R and show how they might be applied to real-world data, warts and all. My hope is that students take away 1) why we use these tools, 2) how to use them (and how not to!), and 3) how we show what it means. Along the way, we’ll incorporate data management and exploration, statistical assumptions, and plotting.

To that end, certain ideas and language within this book are simplified for the target audience - apologies in advance if simplicity or informality jeopardize accuracy in any way. I am happy to receive constructive advice through the GitHub repository for this project located here.

This text and the course assume minimal starting knowledge of statistics or computer programming. We build on both during each chapter, and from one chapter to the next. Throughout the book, we will demonstrate statistical and biological concepts using real and simulated data sets from a variety of sub-disciplines within the biological sciences. My own academic interests are in quantitative aspects of applied ecology and fisheries management. Therefore, many of our examples have a fishy flavor, but I try to incorporate examples from other realms of biology.

The purpose of this book is not to serve as a stand-alone, citable reference document or a comprehensive guide to R even for students enrolled in my own classes. It is The Worst Stats Text eveR! Why would you cite a book with that name? The code and generally citation-free ranting contained herein are, however, extensively supplemented by targeted readings on each topic from the primary literature, published text supplements and discussions in class. The reader is strongly encouraged to seek out other learning resources appropriate to their comfort level (see Additional Resources on the course website).