The only way to know how a complex system will behave-after you modify it-is to modify it and see how it behaves.

Discovering the unexpected is more important than confirming the known.

For the theory-practice iteration to work, the scientist must be, as it were, mentally ambidextrous; fascinated equally on the one hand by possible meanings, theories, and tentative models to be induced from data and the practical reality of the real world, and on the other with the factual implications deducible from tentative theories, models and hypotheses.

Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.

One important idea is that science is a means whereby learning is achieved, not by mere theoretical speculation on the one hand, nor by the undirected accumulation of practical facts on the other, but rather by a motivated iteration between theory and practice.

Statisticians, like artists, have the bad habit of falling in love with their models.

All models are approximations. Essentially, all models are wrong, but some are useful. However, the approximate nature of the model must always be borne in mind.