# Why R?

### Should I use the R statistical software in my introductory statistics
course?

I assume you know that statistics is done with software and that
learning a reputable software package should be a part of any applied
statistics course, so that the question is *which* software.

## Advantages

- R is free. In addition to helping your school's budget, this means no
whining for money, and immediate installation on any machine under your
control It also means students can take it home and install it on their
own machines. High school students can take the software to college with
them.
- R runs on Windows, Mac and Linux/Unix platforms, so it probably runs
on the hardware your school has, and the hardware your students have at
home.
- R is professional quality software used by professional
statisticians. This sets it apart from Excel and various education
programs.
- R includes a vast array of statistical procedures. Few of your
students will ever outgrow it no matter how many statistics courses they
take. This sets it apart from graphing calculators which are a terminal
technology supporting only the first course.
- R was written for advanced graphical data analysis and has
knock-out graphical output.

## Disadvantages

- The usual documentation for R assumes you already have a Ph.D. in
statistics and extensive programming experience. However, you do not
need that to
*use* R, only to read the documentation!-) I needed
11
handouts for my intro. course. You can use them to learn R or for
your own students.
- R has a command-line interface. There is an optional
graphical interface called R Commander. There are two
handouts I made for a statistical literacy course to help you
get started with R Commander, one for
measurement data and one for
categorical data. The presentation assumes you read them
in that order.
- There are not a lot of people using R in introductory courses so
R-specific resources may be few.

© 2006 Robert W. Hayden