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

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.

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

I know of no person or group that is taking nearly adequate advantage of the graphical potentialities of the computer.

Visualization is often used for evil - twisting insignificant data changes and making them look meaningful. Don't do that crap if you want to be my friend. Present results clearly and honestly. If something isn't working - those reviewing results need to know.

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