I am not trying to write a statistics textbook! There are already lots of them and many are very good. I am not even trying to write an online statistics textbook. There are a bunch of them, too. Besides, writing comes hard to me, as those notes will demonstrate.

My aim is to describe, for better or worse, what I do rather than simply present theory and methods as they appear in standard textbooks. This is about statistical practice--what happens when a statistician (me) deals with data on a daily basis. There will be topics where some readers may disagree with my approach. This is true of any type of practice. I welcome all comments, advice, brickbats, love letters, and complaints.

This is very much a work in progress. It seems to take 3 or 4 drafts to figure out how to eliminate unnecessary technical detail. Perhaps it's more correct to say it takes 3 or 4 drafts to figure out what's unnecessary!

Not all of the examples are ideal, I hope to find better examples for those cases where where a dataset doesn't illustrate a technique as well as I or a reader might like. Time constraints sometimes cause me to adapt what I have at hand rather than search for something more suitable. Once the drafts are posted, I can fill them in with new examples as they cross my path.

These notes are being prepared as I teach Nutrition 209/309, Statistical Methods for Nutrition Research, a one-year first and last course in statistical methods required of most bench science and policy students in the Gerald J. & Dorothy R. Friedman School of Nutrition Science and Policy at Tufts Univeristy. I plan to have them reflect my lectures as closely as possible and, perhaps, use them in place of a textbook.

I intend to stay current with my lectures, so these notes will be sketchy and incomplete in some places depending on how much time I have to devote to them. With any luck, there will be no errors of fact. All corrections and requests for clarification are appreciated. I plan to fill in gaps and polish things up with successive iterations.