All models are wrong
All models are wrong but some are useful (though, on the other hand, some are useless).
A group of wealthy investors wanted to be able to predict the outcome of a horse race. So they hired a group of biologists, a group of statisticians, and a group of physicists. Each group was given a year to research the issue. After one year, the groups all reported to the investors.
The biologists said that they could genetically engineer an unbeatable racehorse, but it would take 200 years and $100bn.
The statisticians said that they could predict the outcome of any race, at a cost of $100m per race, and they would only be right 10% of the time.
Finally, the physicists reported that they could also predict the outcome of any race, and that their process was cheap and
simple. The investors listened eagerly to this proposal. The head physicist reported, “We have made several simplifying
assumptions: first, let each horse be a perfect rolling sphere… “