Software for teaching High School Statistics


One can argue that there is a tradeoff in statistical software between its "ease of learning" and its "power".  Typically, those packages that are easy to learn are menu-driven and point-and-click driven.  Some even have features designed soley for pedagogical purposes.  On the other hand, other packages are designed to provide a great number of powerful and fast statistical tools as well as data management capabilities.  

Warning: this page is by no means intended to be comprehensive.  Merely a reflection of my own experience.

High Scorers on the "Ease of Use" scale:

Fathom -- this is predominantly a teaching tool, but in recent years has been expanded to included multiple regression and other useful tools.   Easy-to-use simulation is provided with animation, should one care to slow the calculation to view the animation. (And this is quite useful, maybe even necessary, when demonstrating a simulation to a class.)  This contains many features that make this possibly the first-choice for classroom demonstrations.  Runs on PC and Mac.

DataDesk -- this probably wins on both the "Ease" and "Power" scales.  This offers a wide variety of tools, some fairly sophisticated, and is fairly easy to learn.  Still, the learning curve is slightly steeper than Fathom, and the animation capabilities, while fairly extensive, are harder to use than Fathom's.  Supports multiple regression and ANOVA.
Runs on Macs and PC.  

    DataDesk can also be bundled with ActivStats, in which case it becomes a fairly complete textbook/software package.  ActivStats is a wonderful reference book/self-guided learning tool. 

Tinkerplots -- I'm not sure whether this is easy to use or not.  The target audience is middle school, and middle school students seem to find this easier to use than adults, particularly adult statisticians.  Tinkerplots is designed for graphics and exploratory analysis.  Built ontop of a Fathom platform, it has a radically different design philosophy than other software.  Roughly, you could say that other packages are designed assuming you want to create, say, a histogram, and then make it easy for you to create a histogram.  Tinkerplots is designed to let students construct their own graphics, and then is designed for teachers help students transition from their initial graphics to more formal and, one hopes, precise representations.  Runs on PC and Mac.

High Scorers on the "Power" scale:

SAS -- a very popular package in the professional world.  Everything and the kitchen sink.  Command-driven; you type the right phrase to invoke the appropriate package, and it provides output.  Powerful data management capabilities.  Difficult to learn.  (In fact, for all of the packages in this category, it's fair to say that people usually take classes just to learn these software packages.  UCLA, for example, teaches Stats 130B "Statistical Analysis with SAS" and also 130A "Statistical Analysis with STATA.")  Doesn't run on Macs.  

Splus or R -- These are both statistical programming languages.  Certain fundamental "objects" and operations make it easier to "roll your own" analysis routines.  Common routines (say, regression) are pre-programmed, and there is a large on-line library of routines that can be downloaded.  Great graphics capabilities, and hands-on control. For people who prefer stick-shifts to automatic transmissions.  (Actually, for people who prefer shifting the gears themselves, without the clutch.)  Splus costs money, R is free and runs on the Mac (classic and OSX) as well as PC.

Stata -- Stata is more like SAS than Splus.  It runs on Macs and PCs and is slightly easier to learn than SAS.   Runs on Macs  and PC.  UCLA ATS supports some nice Stata teaching modules. Browse a little on the ATS support pages.  You'll find help for teaching Stata and SAS, should you need it.  Considerably less expensive than SAS.  Also includes an even less expensive student version.

Xlispstat -- xlispstat is very much like Splus or R, except that it's  LISP.  If you are a fan of LISP, you will be overjoyed. Otherwise, you might not be convinced until you have seen the graphics  (even inter-active graphics) that can be produced.  Still, it does mean a heavy dependence on the parentheses keys.  Best of all: its free!  

Middle-Ground


Arc -- Arc runs as a "front-end" to xlispstat and as such is a user-friendly (i.e. menu-driven) package and also gives you all of the (considerably less user-friendly) flexibility of xlispstat.  ARC does one thing very, very well:  linear regression.  In fact, more of linear regression than you probably thought existed.  It was developed to support a book: Applied Regression Including Computing and Graphics, R. Dennis Cook and Sanford Weisberg, 1999 John Wiley & Sons.  This is a wonderful book, but somewhat beyond the High School level. Still, you might enjoy it.  The software is free and runs on PCs and Macs (but not OSX).

Minitab -- I have no direct experience with this myself.  However, I'm told it's fairly easy to learn and fairly comprehensive.  It has been around for awhile and so has an established track record. It can also be bundled with ActivStats.  Not sure whether it runs on Macs, though.

SAS also publishes JMP , which is more user-friendly, I'm told. I have no experience with it.  Runs on Macs (not OSX) and PC.

SPSS  is used primarily by social scientists, although I have no personal experience with it.

Forget about it

Excel:   As Paul Velleman (developer of DataDesk) put it once:  you can also use Excel as a word processor, but you don't,  do you?  A fine spreadsheet, a really lousy statistical package.  And, yes, I do know about the statistical "tools" add on.  Still, why struggle trying to turn your Excel bar graph into a histogram when other packages do it easily and quickly (and correctly the first time) and let you change the number of bins?  Yes, I know your school already has Excel; so if you want to teach them Excel, then use it.  If you want to teach them Statistics, use something else.  I would also point out that Excel is not nearly as easy to use as even some of the more difficult to use statistics packages.  This is often overlooked by Excel-as-statistics proponents because they already know how to use Excel.  If you already know how to use Excel, then admittedly it is easy enough to learn how to operate the statistics add-ons.  But if you don't, you will find yourself puzzled and perplexed and aggravated at having to rely on an annoyingly chipper animated robot for assistance.

Here is one nice analysis of Excel's statistical shortcomings, and Paul Velleman has a nice explanation on the Math Forums.