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. DataCamp Amherst College faculty have been utilizing modules and materials from DataCamp to help students learn these flexible and powerful tools.

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

Statistics 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/video.html.

Last updated August 26, 2018 by Nicholas Horton