R is a powerful open source environment for statistics and data science.  RStudio is an integrated development environment that facilitates the use of R by students and instructors. An RStudio server is available for members of the Amherst community at r.amherst.edu.

Student Guide and other R resources

The following additional resources may be helpful to those getting started with this system.

A Student's Guide to R and RStudio (note that a Spanish language translation is available here)

Getting started videos

Getting started with RStudio: logging in to the server

Getting started with RStudio: first steps in R

Getting started with RStudio: second steps in R

Getting started with RStudio: first steps with R Markdown

Getting started with RStudio: second steps with R Markdown

Getting started with RStudio: sample homework in markdown

Prezi presentation on R markdown

Getting started with RStudio: dealing with files

Getting started with RStudio: all about packages

Getting started with RStudio: other resources

Github and RStudio: getting started

Multiple regression

Multiple regression interpretation and diagnostics (Galton dataset)

Introduction to the mosaic package and other related resources

Minimal (1 page) guide to R for intro stats

Cheatsheets for R, data wrangling, markdown, and Shiny

Building precursors for data science in R

Textbooks and textbook-related resources

Intro Stats (De Veaux, Velleman, and Bock, fifth edition)

Using R for Data Management, Statistical Analysis, and Graphics (second edition)

Stats: Data and Models (fourth edition) examples in R

Webster 102 classroom

Changing monitor display in Webster 102

Mounting home folders

Users can mount their home folder (on the RStudio server) locally with the following instructions, which makes it a lot easier to move items back and forth, print them, etc.: https://www.amherst.edu/offices/it/knowledge_base/academic-resources/unix_servers/unix_network_space

Rosenblum Statistics and Data Science fellows

In case of questions, during the semester there are drop-in statistics hours each weeknight (7-9pm) coordinated with the Moss Quantitative Center. These drop-in hours normally take place in Science Center E208.

IS5 in R videos

These video overview of the chapters from Intro Stats (De Veaux, Velleman, and Bock) 5th edition provide additional guidance for the reader. The R companion resources can be found at https://nhorton.people.amherst.edu/is5/videos.html.

Last updated December 29, 2020 by Nicholas Horton