all models are wrong
All models are wrong; but some are useful
Anscombe's quartet – Four data sets with the same descriptive statistics, yet very different distributions Bonini's paradox – As a model of a complex system becomes more complete, it becomes less understandable Reification (fallacy) – Fallacy of treating an abstraction as if it were a real thing