Count the assumptions each explanation requires
When two explanations fit the facts, count how many unverified assumptions each one rests on.
Why it works
Each assumption in an explanation is an independent place the explanation can fail. An explanation with five assumptions has five places where the chain can break; one with two assumptions has two. Counting assumptions makes probability differences concrete — independent errors multiply, so the gap between explanations widens quickly.
How to do it
- Write out the competing explanations as explicit chains: "this is true IF A, B, and C."
- Count the unverified assumptions in each chain.
- Ask which assumptions are actually checkable with current evidence.
- Favor the explanation with fewer unverified steps while remaining open to update.
Evidence
The parsimony preference is foundational in philosophy of science (Sober, Quine) and is encoded in Bayesian probability: simpler models receive higher prior probability because they make fewer independent bets. The formalization is well established in statistical model selection (AIC, BIC penalize unnecessary parameters). Sober's Ockham's Razors distinguishes the several distinct justifications for parsimony, clarifying that assumption-counting is a defensible prior only under specific evidential conditions. (mechanistic)
Parsimony is a prior, not a guarantee. Nature is sometimes genuinely complex; simpler explanations can also be wrong. The razor guides starting points, not endings.
Sources
- Sober, Elliott (2015). Ockham's Razors: A User's Manual. Cambridge University Press.
- Schwarz, Gideon (1978). "Estimating the Dimension of a Model." The Annals of Statistics, 6(2), 461–464.
- Akaike, Hirotugu (1974). "A New Look at the Statistical Model Identification." IEEE Transactions on Automatic Control, 19(6), 716–723.
Common mistake
Treating simplicity as a trump card regardless of evidence — dismissing a complex but well-supported explanation because it feels complicated.
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More practices for Occam’s Razor: Prefer the Simpler Explanation
- Resist conspiracy escalation
When your explanation requires others to have coordinated secretly, apply the razor hard.
- Diagnose before elaborating
Check the common, simple explanation first before searching for rare or complex ones.
- Trim model complexity
Prefer the simplest model of a situation that still fits all the evidence.
- Know when not to apply the razor
Occam’s Razor is a tiebreaker, not a rule: when evidence clearly supports complexity, go there.
- Resist the single-cause trap
Simple doesn’t always mean one cause — sometimes the simplest honest answer is 'multiple contributing factors.'
- Apply parsimony to your own communication
Use the fewest words and concepts that carry the full meaning — not as brevity, but as clarity.
Related concepts
- Hanlon's Razor: Never Attribute to Malice What Stupidity Can Explain
The charitable-attribution heuristic and why it usually serves you better
- Thinking, Fast and Slow, Made Usable
Two systems, the biases they create, and when to slow down
- First-Principles Thinking, Made Usable
Reasoning up from fundamentals, with the mechanism behind why it beats analogy
- Anchoring Bias in Negotiation and Judgment
Why the first number wins — the mechanism, and how to set and resist anchors