Online Books and Other Resources
My aim here is to periodically update this list of online books and resources so that I can go back and reference in the future. These have been helpful to me over the past several years augmenting teachings from my undergraduate and graduate courses.
Introduction to Statistical Learning
Gareth James, Daniela Witten, Trevor Hastie, Rob Tibshirani
Now on the second edition, but the first edition is where I learned R originally…amazing book and video series based on a course at Stanford. (Bonus: One of the four authors is a Husky :-)
R for Data Science
Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund.
The lead author, Hadley Wickham, is the Chief Scientist at Posit (the company behind RStudio), and considered a thought leader in the RStats community.
Not a book, but here is a paper written by Wickham about tidy data, the underpinnings of how we should all aim to clean and setup our data.
He is responsible for the following diagram explained in the book:
Forecasting: Principles and Practice (3rd ed)
Rob J Hyndman and George Athanasopoulos
Chapters 7-9 have great details on time series analysis…covers forecasting in depth…awesome book.
Introduction to Modern Statistics (2e)
https://openintro-ims.netlify.app/
Mine Çetinkaya-Rundel and Johanna Hardin
Text Mining with R
https://www.tidytextmining.com/
Julia Silge and David Robinson
An R-companion for Statistics for Business: Decision Making and Analysis
http://www-stat.wharton.upenn.edu/~stine/r_companion/_book/index.html
Robert Stine and Dean Foster
This is an on-line supplement to the textbook Statistics for Business by Robert Stine and Dean Foster.
Data Visualization: A Practical Introduction
Kieran Healy
Beyond Multiple Linear Regression
https://bookdown.org/roback/bookdown-BeyondMLR/
Paul Roback and Julie Legler