The purpose of this course is to give "real life" experience to those who teach Statistics in the High Schools.  We will not cover pedogogical theory, nor talk about specific lesson plans or activities to do in class.  Instead, the activities we do should give the participants a more complete and comprehensive view of Statistics than is available in an introductory textbook, and this, in turn, should help them to better teach the subject to their students.

Contrary to the impression most of us probably got when first learning Statistics, Statistics is very different from mathematics.  We won't waste electronic ink on this here, but for those intererested in examining this further, I recommend reading David Moore's article
For our purposes, consider this fundamental difference.  Mathematics is deductive.  From a collection of axioms one derives a single inevitable conclusion (to grossly oversimplify!)  Statistics, though, is inductive.  From a collection of observations, one infers generalizations about a larger population.   Of course the tools required to do so are often mathematical, or at least cannot be fully understood without understanding some math.  But the application of these tools cannot be understood without, well, applying them yourself.

For this reason, this class will emphasize data, data, and more data.  We'll spend our time analyzing data sets, talking about alternative analyses, looking more closely at some tools.  Precisely what we cover and how much detail we go into is up to you.  We'll start slow and spend the first two weeks assessing our common ability level.  There will be only occaisonal lectures so that we can all be brought up to speed on certain techniques.  For the most part, we'll do our work during class, although occaisonally you might want to bring work home.

We will not ignore your own students completely.  We'll reserve some time each week for you to bring up issues that have arisen in your own teaching, and also to brainstorm about how the things we've covered in our class might be used for your students.

Textbook:

    There is no required text for this class.  However, if you want a "souvenir", read this list.  Also, you can contribute your own comments about these books.

Consulting Center:

The UCLA Statistical Consulting Center is working on a number of different projects.  I'll keep you posted on some of them to give you an idea of the utility of Statistics.  Because of confidentiality and proprietary concerns, these descriptions will sometimes be vague and usually will lack data.

Data Sets:

Look here for any data sets we discuss in class.

References:

Some papers referred to in class.

Handouts:

When possible, handouts from class are posted here.

Applied Statistics Books

There are no "perfect fits" when it comes to textbooks for this class.  But here is a compendium of candidates.  I hope this list grows over time as you contribute your suggestions and comments.