For review of the fundamental concepts of statistics, see OpenIntro: Introductory Statistics with Randomization and Simulation (2014), by Diez, Barr and Çetinkaya-Rundel, available in three formats: pdf, tablet-friendly pdf, and paperback edition. The textbook is free and open-source. For general concepts of data and inference, see chapters 1 and 2. For regression, see chapters 5 and 6.
If you’re new to R or need a refresher, there are some short free online courses that can be helpful. I recommend Datacamp: Intro to R. There is also a free online reference book for the fundamentals of the R languaged called Cookbook for R.
Once you’re up and running, it can be helpful to have the most important information distilled into one sheet of paper. RStudio puts out several great ones including the Visualization Cheatsheet (ggplot2) and the Data Wrangling Cheatsheet (dplyr).
If you imagine yourself using R and RStudio after this course and after Reed, you should get it setup on your own machine. This tutorial will walk you through all the downloading, installing, and configuration.
R Markdown is a very important tool to enable data analysis that is completely transparent and easily reproducible. These slides walk through the motivation and basic structure of R Markdown while this video is a good walkthrough to making your first R Markdown document.
For all the important ideas summarized into a single place, you can use the R Markdown cheatsheet.