Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise.

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

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

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

Numerical quantities focus on expected values, graphical summaries on unexpected values.

When communicating results to non-technical types there is nothing better than a clear visualization to make your point.

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.