I haven’t posted much lately because I’ve been hard at work on my new book. It’s titled Understanding Statistics, and I expect to finish in a week or two. I’ll be sure to post here when I do, hoping that lots of you will buy it. Even if you don’t need one for yourself, you might know somebody who would enjoy and make good use of it. Who knows, maybe 20 of you will send a copy to Anthony Watts. Maybe he would learn something from it. Irony of the richest kind.
It’s written at an introductory college level for non-math majors, those who haven’t studied calculus. There are some notable differences from the usual such text. For one thing, there’s much more emphasis on theory than is usual. Too many texts amount to little more than a cookbook, with recipes for statistical procedures and gobs of examples but little or no exposition of why it works the way it does, not just how.
That’s fine, students learn well that way and usually do well on their tests — they even feel good about it. But five years later when they actually need to use it, all is forgotten. So they have to go back to the book and start over from scratch. My experience is that when you learn the “why,” it sticks. The “how” will be forgotten in five years, but if the need arises, you won’t have to re-learn it from square one. Something about understanding the “why” reaches the core of your brain and makes the re-learning so much easier and faster, and so much less likely to go wrong. Truly understanding something stays with you forever.
Often, theory is omitted because it’s considered too difficult for non-math majors. That’s an idea I find both unflattering, and mistaken. My experience is that students, even those who hate and fear math, have more than enough intellect to get it — really understand — if it’s presented clearly enough. That’s the writer’s job and the teacher’s job, so when students find a smattering of theory too difficult, I don’t blame them — I blame the teacher.
Another difference is that I’ve included some “case studies.” These aren’t just data sets used to illustrate a particular method. They’re data sets which I analyze the shit out of. That’s the way statistics often is, and often should be, done. It’s true that there are many circumstances in which data are collected to anwer a specific question and you know ahead of time exactly how they’ll be studied and what tests will be applied. But there are surprisingly many situations in which data are acquired and nobody has a clue what they mean. That’s a case in which the “cookbook” approach falls on its face. By showing how to explore data and put it under the microscope from multiple angles, I hope to give readers much more power over the data they wrestle with.
Yet another difference is that I’ve left out problem sets and computer instructions. Those will be put into a study guide which will be released in a few months so that teachers who wish to use it for a formal course can do so. By separating these functions I hope to make the base text more readable, and I’m a firm believer that books should be written so as to be read. The study guide will have to change rapidly to keep up with changes in how data are acquired and made available and how computer tools evolve. I hope that the base text will be considerably more “timeless.”
I probably won’t post much in the upcoming week. But when the new year arrives I’ll be back with a vengeance. Stay tuned.