Be approximately right rather than exactly wrong.

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

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

The best thing about being a statistician is that you get to play in everyone's backyard.

The greatest value of a picture is when it forces us to notice what we never expected to see.

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

An approximate answer to the right question is worth far more than a precise answer to the wrong one.

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

There is no data that can be displayed in a pie chart, that cannot be displayed BETTER in some other type of chart.

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

To be able to say that "if we change our point of view in the following way ... things are simpler" is always a gain.

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

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

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.

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.

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.

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.

In a world in which the price of calculation continues to decrease rapidly, but the price of theorem proving continues to hold steady or increase, elementary economics indicates that we ought to spend a larger and larger fraction of our time on calculation.

In rating ease of description as very important, we are essentially asserting a belief in quantitative knowledge - a belief that most of the key questions in our world sooner or later demand answers to 'by how much?' rather than merely to 'in which direction?'

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.

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