Professor Gelman has a nice list of statistical definitions, educational like nearly everything he does or writes:

- The Folk Theorem: When you have computational problems, often there’s a problem with your model.
- Second-Order Availability Bias: Generalizing from correlations you see in your personal experience to correlations in the population.
- The “All Else Equal” Fallacy: Assuming that everything else is held constant, even when it’s not gonna be.
- Scaffolding: Understanding your model by comparing it to related models.
- Ockhamite Tendencies: The irritating habit of trying to get other people to use oversimplified models.