Hey everyone, I'm the author of this guide. It's come full circle -- I posted it a week ago in a "what are you working on?" Ask HN post, someone posted it to Metafilter and reddit, and it made its way to Boing Boing and Daily Kos before coming back here. I'm currently working on expanding the guide to book length, and considering options for publication (self-publishing, commercial publishers, etc.). It seems like a…
One thing that is missing is like a Summary/Checklist chapter that tells you what you SHOULD do, in a few common scenarios to avoid all the mistakes presented in the previous chapter. I know its not that simple, and it depends a lot on how you are testing and what you're actually trying to achieve, but a few examples wouldn't hurt.
For example: I have two sets of measurements, and I want to know: * is there a statistically significant difference between them * if yes, how much is the difference
A somewhat simplistic way I'd do that is to do a two-sample t-test for question #1, and to compute statistics for the difference between the samples (mean, median, confidence intervals), but doing just that I might've already committed some of the mistakes that your site warns about, for example I completely disregarded the power of the test.
FWIW I like parts of this book on statistics which focuses on statistics in the domain of computer systems / network, although it is rather too long: http://perfeval.epfl.ch/