“All models are wrong. Some models are useful.” — George Box

(Image courtesy of the Damien Garcia.)

As a statistician and quant, I’ve thought hard about that oft-cited Boxism. I’m not sure I agree. It’s not that there is such a thing as a perfect model, or correct model, whatever in the world that would mean, but it is that whatever is appealed to in our heads or “gut” when we look at a model and find it wanting is, well, just another model. Frankly, after a lot of practice, I think models get a bad rap: I don’t think it makes any sense at all to look at observations without having at least an informal model in mind. Observations are necessary but rarely can they stand on their own; not and have a chance of being generalized, anyway. That’s because we really can’t see something, let alone understand, unless it’s abstracted away, beyond details.

(Image courtesy of the Open Motion Planning Library.)

I like this other quote, from physicist Arthur Eddington:

It is also a good rule not to put overmuch confidence in the observational results that are put forward until they are confirmed by theory.

About ecoquant

See https://wordpress.com/view/667-per-cm.net/ Retired data scientist and statistician. Now working projects in quantitative ecology and, specifically, phenology of Bryophyta and technical methods for their study.
This entry was posted in abstraction, American Association for the Advancement of Science, astronomy, astrophysics, mathematics, model-free forecasting, numerics, perceptions, physical materialism, physics, rationality, reason, reasonableness, science, spatial statistics, splines, statistics, the right to know, theoretical physics, time series. Bookmark the permalink.

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