We're excited that you will be taking a Statistics course at Amherst! If you placed out of Introductory Statistics or took Stat 111 or are transitioning from Psyc 122 and are planning to take a second 200-level applied course from the Department, we recommend the following:

Preparation for Additional Courses: Students who complete Stat 111, Psyc 122, or who have successfully placed out of Stat 111/135 who intend to pursue additional courses in statistics (such as Stat 230, Stat 231, Stat 240) are required to review the material in an “Introduction to Multiple Regression” chapter and are strongly recommended to find a time to meet with a member of the Statistics faculty prior to undertaking additional statistics courses. This material is covered in Stat 135 and is assumed background for statistics electives.

We also know some students may want to learn the software used in our statistics courses. This page is intended to provide resources for statistical content and the software for students entering our 200-level applied courses who did not take Stat 135.


Resources are divided into two broad categories: statistical content for regression and learning the software.


For a review of simple linear regression and exposure to multiple linear regression content, you might look at:

  • OpenIntro Statistics' Chapter 7 - An Introduction to Linear Regression and Chapter 8 - Sections 8.1-8.3 on Multiple Regression. This is a textbook with free pdf download available here.
  • Modern Data Science with R also has an appendix that reviews Linear Regression. A free pdf download of that Appendix is available here. Sections E.1-E.4 are the relevant sections.
  • The textbook Stats: Data and Models (4th edition) has chapters on Simple Linear Regression and Multiple Regression. The textbook is on reserve in the Science Library when classes are in session. Relevant chapters include Chapters 6-8, 25, and 28 (see companion R materials at https://nhorton.people.amherst.edu/sdm4).

Bear in mind that courses such as Stat 230 will have some review of simple linear regression and spend quite a bit of time with multiple linear regression, so you would be expected to have some familiarity with simple linear regression and exposure to multiple linear regression, before taking the course, but you are not expected to have mastered those concepts before the class.


If you are new to the software R, the interface RStudio, and working with RMarkdown files, there are a variety of resources available to you so that you can learn a bit about the software before taking a Statistics course. Even if you learn some about the software before the course begins, you should expect to spend the first few weeks of the class getting up to speed with the software in order to succeed in the course.

R, RStudio, and RMarkdown at Amherst

Professor Horton has put together some resources about Getting Started with R, RStudio, and RMarkdown at Amherst which are available here. In particular, you might want to look at the first few Getting Started Videos (up through the sample homework video). Amherst runs an R Studio server, so you can login to the software wherever you have access to a browser. 

Learning R

To learn more about R generally, there are many resources available on the web. Many of our instructors have been making use of Datacamp courses to help with knowledge of the software. The 'Intro to R' Datacamp course and first chapters of other courses are free, so you could explore them before even signing up for a Statistics course. Once you have signed up for a Statistics course, your instructor may have you complete other courses using an Educational Group, which will give you access to the relevant Datacamp courses for your Statistics course. Check with your instructor about relevant courses or watch for an email about this from your instructor.

Learning RMarkdown via Examples

We expect to make available several example RMarkdown files for students to download and practice with, so that you can see some actual files from our courses. This section is still under development.