index.Rmd

--- 
author: Dan Stich
title: The Worst Stats Text eveR
site: bookdown::bookdown_site
documentclass: book
bibliography: [book.bib, packages.bib]
biblio-style: apalike
link-citations: yes
description: ""
---

```{r, setup, include=FALSE, tidy=TRUE, message=FALSE, warning = FALSE}
  library(tidyverse)
```
# The Worst Stats Text eveR {-#title}

Dan Stich, PhD

*Biology Department and Biological Field Station, SUNY Oneonta*

<img src="images/roh.png" alt="alcohol molecule">

<p style="font-family: times, serif; font-size:.9em; font-style:italic">
Unskillful representation of an alcohol molecule where -OH is the functional group and R is the radical group, or "rest of the molecule", much like it is to modern statistics. This is funny, because R is a "functional" programming language that will drive you to drink (or perhaps undertake some other, healthier stress-reducing activity). Don't worry, I'll explain all of the jokes, and **most** of the code as we go, because this is</p>
**The Worst Stats Text eveR**.


# Preface {-#preface}

-----
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](https://rmarkdown.rstudio.com/), and now finally into an e-document (thanks to [bookdown](https://bookdown.org/home/about/)!) 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](https://github.com/danStich/worst-r). 

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](https://danstich.github.io/stich/classes/BIOL217/index.html) on the course website).

# About the author {-#author}
Dr. Dan Stich is Associate Professor of Biology at the State University of New York College at Oneonta. He teaches undergraduate and graduate courses in organismal biology, ichthyology, ecology, experimental design, lake management, and quantitative biology. He also teaches R workshops for various professional societies to which he belongs. His research focuses on the development and application of quantitative models to answer theoretical and applied questions related to fisheries and aquatic resource management and decision making. You can learn more about his teaching and research through his [website](https://danstich.github.io/stich/index.html).

Dan is not a programmer or a statistician. He is a fish scientist who went rogue with code and stumbled into population modeling as a graduate student. At some point it became as much a hobby as a work endeavor. He is an active user of R and Rstudio and delights in seeing others get hooked on it, too. He maintains and contributes to multiple R packages as part of his research. You can find some of these in his [GitHub repositories](https://github.com/danStich), where he spends much time talking to himself in his own online issue trackers.

```{r include=FALSE}
# automatically create a bib database for R packages
knitr::write_bib(c(
  .packages(), "bookdown", "knitr", "rmarkdown"
), "packages.bib")
```