- I will remember that I didn't make the world and that it doesn't satisfy my equations.
- Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.
- I will never sacrifice reality for elegance without explaining why I have done so. Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.
- I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.
- From Mark Palko: "Our model only describes the data we used to build it; if you go outside of that range, you do so at your own risk."
- In case you like to think of your methods as nonparametric or non-model-based: "Our method, just like any model, relies on assumptions which we have the duty to state and to check."
I mentioned this subject a couple of times before. Simple reaction time data from Woodley et al.Bruce Charlton is the first person I know of to discuss the implications of the change in simple reaction time data in the paper by Woodley et al. Charlton claims the data shows
Geoff Canyon has a post about Google's tricky interview questions. Microsoft is also known for asking these kind of questions during interviews, and you can run into them anywhere in the technical world. Also known as Fermi problems or back-of-the-envelope calculations, I ran into these a lot during college because
A fun post exploring the differences between a number of statistical computation packages. As one of the commenters said, this is an awesome flame war! The comments are very informative, with all sorts of historical information explaining how and why certain packages turned out the way they are. I use