# Textbooks

#### Required

Diez, D.M., Barr, C.D., & Çetinkaya-Rundel, M. (2019). *OpenIntro Statistics (4th Ed).*

This is an open source textbook and can be downloaded in PDF format here, from the OpenIntro website, or a printed copy can be ordered from Amazon.

Navarro, D. (2018, version 0.6). *Learning Statistics with R*

This is free textbook that supplements a lot of the material covered in Diez and Barr. We will use the chapter on Bayesian analysis. You can download a PDF version, Bookdown version, or visit the author’s website at learningstatisticswithr.com.

#### Recommended

OpenStax.org is a great resource for free textbooks. The following books will be helpful to have as a reference and to supplement, and get an alternative explanition, for many of the topics covered in this course:

- Statstics
- Calculus - We will very briefly explain the concepts of limits, derivatives, and integrals that underlie some important statistical concepts. This books will provide much more detail.
- College Algebra - For those who need a refresher in algebra, this is a good resource.

Wickham, H., & Grolemund, G. (2016) *R for Data Science*. O’Reilly.

Most of this books is available freely online at r4ds.had.co.nz/ but can be purchased from Amazon.

Wickham, H. *Advanced R.* Baca Raton, FL: Taylor & Francis Group.

Most of this book is available freely online at adv-r.had.co.nz but can be purchased from Amazon.

Kruschke, J.K. (2014). *Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan (2nd Ed)*. London: Academic Press.

This book can be purchased from Amazon, but also check out the author’s webiste (doingbayesiandataanalysis.blogspot.com/) for additional resources.