Be approximately right rather than exactly wrong.

In a single sentence the moral is: admit that complexity always increases, first from the model you fit to the data, thence to the model you use to think about and plan about the experiment and its analysis, and thence to the true situation.

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization.

If we are going to make a mark (key 21), it might as well be a meaningful one.

An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.

All we know about the world teaches us that the effects of A and B are always different-in some decimal place-for any A and B. Thus asking "are the effects different?" is foolish.

It's better to solve the right problem approximately than to solve the wrong problem exactly.