All models are wrong; some models are useful.

All models are wrong, many are useful, some are deadly.

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

All models are wrong. Some are lethal.

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

To quote the industrial statistician George Box: “Every model is wrong, but some are useful.

However, not every model is as reliable as gravity, and all models are flawed in some way.

All designs are wrong, it's just a matter of how wrong.

Modeling Principle: Models are not right or wrong; they are more or less useful.

All models rely on a small set of critical assumptions.

A good (simple) model uncovers them, while a bad (complicated) model obscures them.

When no idea seems right, the right one must seem wrong.

I view the work I've done related to statistics and economics as roughly speaking, how to do something without having to do everything. So economic models -- how any model by definition isn't right. When someone just says, 'Oh, your model is wrong.' That's not much of an insight. What you want to know is, is wrong in important ways or wrong in ways that are less relevant? And you want to know what does the data really say about the model?

All generalizations are inaccurate, including this one.

All predictions are wrong, that's one of the few certainties granted to mankind.