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# modeling

notes on mathematical and conceptual modeling. [published on moonflowers.xyz](https://www.moonflowers.xyz/notes/mDl1nG_N0t3-on-modeling).

## the core idea

"all models are wrong, but some are useful." — George Box

models aren't truth. they're tools. the question isn't "is this model right?" but "is this model useful for what i'm trying to do?"

## examples across domains

- **anesthetics EEG model** — a simplified representation of brain activity that's useful for monitoring patients, even though it doesn't capture everything happening in the brain
- **data center environmental impact** — models that estimate carbon footprint, useful for decision-making even if imprecise
- **linear regression** — the simplest useful model. often good enough.
- **firefighting strategy** — models of fire spread that guide resource allocation
- **Maxwell's equations** — near the ground-truth end of the spectrum. physics-grade models that are both useful AND highly accurate.

## the spectrum

there's a spectrum from rough useful models to physics-grade ground truth. most real-world models sit closer to the rough end, and that's fine. the mistake is expecting ground truth from a rough model, or refusing to use a rough model because it's not ground truth.

## connection to narratives

a narrative is a model of your own story. and like all models, narratives are wrong but some are useful. choosing a better narrative (see [[confidence]]) is choosing a more useful model of yourself.

## modeling in research

when doing [[research-workflow]], modeling is often the core skill — taking a complex system and finding a representation that's simple enough to work with but accurate enough to be useful.