Textbooks and Other Resources

This is not (yet…maybe one day who knows) a complete statistics textbook for statistics or R. It is a series of weekly exercises that could be used as labs in statistics courses for psychology students. They are aimed at initiating novice students into learning a programming environment for statistics like R, but also at using R as a teaching tool to aid conceptual understanding of statistics.

0.27 Statistics textbooks we are using

Students taking this course at Brooklyn College are also taking a separate series of bi-weekly lectures, so they arrive in lab after having discussions and digested some readings. At the beginning of each lab I refer to the readings that have been assigned to students, which come from three different textbooks:

1. Vokey & Allen⁸, pdf available online
2. Abdi, Edelman, Dowling, & Valentin⁹, portions may be downloadable from google scholar, otherwise try to find a printed copy somewhere.
3. Crump, Navarro, & Suzuki¹⁰, https://crumplab.github.io/statistics/, and some the lab manual for R https://crumplab.github.io/statisticsLab/

0.28 Other online textbooks

There are increasing numbers of excellent, free, and online resources for learning statistics and R, here are some:

1. Danielle Navarro’s Learning Statistics with R and website for learning R R for Psychological Science
2. Russell Poldracks’s Statistical Thinking for the 21st Century
3. Martin Speekenbrink’s Statistics: data analysis and modelling, and companion R book An R companion to Statistics: data analysis and modelling
4. Into python instead? Check out Todd Gureckis’ Lab in Cognition and Perception
5. Looking for stats videos, check out Erin Buchanan’s STATISTICS OF DOOM! on youtube: https://www.youtube.com/channel/UCMdihazndR0f9XBoSXWqnYg

0.29 A longeR list

• Hadley Wickham has written several fantastic and free booksv that I keep coming back to all the time, R for Data Science, ggplot 2: elegant graphics for data analyis, Advanced R, and R packages.
• R markdown and knitr are core libraries for using R to create all sorts of reproducible documents from pdfs to websites. Here are some excellent resources:
  • https://bookdown.org/yihui/rmarkdown/
  • https://bookdown.org/yihui/rmarkdown-cookbook/
• Github got you down? Jenny Bryan has a pick me up for you https://happygitwithr.com
• Googling R questions can often turn up an example of someone solving your issue or a closely related one. For example, you can copy error messages and google them, or ask “how to do X in R”.
• Stackoverflow is great, Google will often take you there because someone has already asked your question, and someone else has answered, usually many people have answered your question many ways.
• Danielle Navarro recently made this website for introducing R, it’s great, check it out (also made using this R markdown process): http://compcogscisydney.org/psyr/
• Check out my slightly older programming book that also introduces R https://crumplab.github.io/programmingforpsych/, actually don’t do that, it’s too old now and not worth it.
• Another solid and accessible resource for psyc stats using R https://ademos.people.uic.edu/index.html.
• https://cran.r-project.org/doc/contrib/Short-refcard.pdf This link takes you to a reference card, that shows a big long list of intrinsic r functions.
• A really great and really long list of resources for R! https://paulvanderlaken.com/2017/08/10/r-resources-cheatsheets-tutorials-books/
• There’s a bunch of R markdown tricks right here https://holtzy.github.io/Pimp-my-rmd/.