index bb99989..8eb0e41 100644
@@ -43,7 +43,7 @@ humans are pattern-recognition machines. we see faces in clouds, hear words in n
**when it fails**: seeing patterns in random noise. the "hot hand" debate in basketball raged for decades partly because humans are so eager to see streaks in random sequences. financial "technical analysis" finds patterns in stock charts that often aren't really there. conspiracy theories are pattern recognition run amok.
-the antidote is statistical thinking: asking "how likely would this pattern be by chance?" if you flip a coin 100 times, you'll almost certainly get a streak of 6 or 7 heads somewhere. that's not a pattern — it's expected randomness.
+the antidote is statistical thinking: asking "how likely would this pattern be by chance?" if you flip a coin 100 times, you'll almost certainly get a streak of 6 or 7 heads somewhere. that's not a pattern — it's expected randomness. this connects directly to [[immediate/probability-in-daily-life|probability]] — distinguishing signal from noise is fundamentally a probabilistic question.
## mental math tricks
@@ -61,4 +61,4 @@ some useful estimation heuristics:
estimation is where [layer 1](/wiki/immediate/counting-and-measurement) thinking meets [layer 3](/wiki/structural/the-organizational-lens) thinking. the act of estimating forces you to build a mental model: what are the relevant quantities? how do they relate? what's the structure of the problem?
-this is exactly what harrison means by "the organizational lens" — you're not just computing, you're *structuring your understanding* of a situation. a good fermi estimate reveals the key parameters of a system, which parameters matter most (sensitivity analysis), and which you can safely ignore. that's mathematical thinking at its most practical.
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+this is exactly what harrison means by "the organizational lens" — you're not just computing, you're *structuring your understanding* of a situation. a good fermi estimate reveals the key parameters of a system, which parameters matter most (sensitivity analysis), and which you can safely ignore. that's mathematical thinking at its most practical. pattern recognition itself is what [[structural/abstraction-as-power|abstraction]] formalizes — noticing that two different situations share the same structure is both the essence of estimation and the essence of abstract mathematics.
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