Chapter 1 Goals

This guide is written for students learning R in their introductory statistics class. It isn’t meant to teach you statistics or to teach you R programming (though there is some of that). It is meant to help you learn the things you’ll need to know in order to do that stuff.

Historically, intro stats courses were taken my math and stats majors as a gateway to more advanced statistics classes. Like most stats classes, they were taught like traditional math classes, using pen and paper. Over the last decade or more, we have seen two big shifts in intro stats.

First, more schools and programs are requiring an intro stats class or something similar as a gen ed or major requirement. This means that most students in intro stats don’t consider themselves “math people” or “statistics people.” It’s highly likely this will be the only statistics class they take.

Second, the availability of personal computing and statistical software has grown dramatically. We are now able to process in a matter of seconds, on our laptops or through a cloud server, complex computations that would have required past students to spend countless overnight hours in a highly regulated university computer lab. This development has provided an opportunity for into stats classes to go deeper into content, and in more varied directions, than they ever have before.

While these changes have been great - more people learning more statistics can’t be a bad thing, right? - it leaves us in a situation where students (probably already dreading their stats class) are learning a statistical programming language at the same time they are learning statistical calculations and concepts, which is often thought of as its own language itself. This creates a need for a gentle introduction to statistical computing for students with very little background in either statistics or computing. So far I have found very little comprehensive support for such students. I hope to provide that support here.

To Instructors

While this guide is written for students, I hope you are able to benefit as well. I put this guide together after years of working with students who are now its primary audience. By reading ahead, you may infer some of the difficulties your students will come up against in their work, some of which may surprise you if it is your first time teaching such a course. Hopefully you find it useful enough that you can refer your students to it as well, and their reading it can build a common starting point for your class and ease your workload of additional questions.

Some other views on teaching introductory R can be found below:

  • 6 Lessons I learned from teaching R to non-programmers by Albert Rapp [LINK]
  • Teach the tidyverse to beginners by David Robinson [LINK]. Also see his talk on the topic [LINK]
  • Teaching R in a Kinder, Gentler, More Effective Manner: Use Base-R, Not the Tidyverse by Norman Matloff [LINK]