The concepts behind limited-clue inference, in plain language. For the method itself, see Method; to try it, go to the bench.
Entities should not be multiplied beyond necessity: when two explanations fit the available clues, prefer the one with fewer assumptions and better testability. It is not "the simplest answer is always right".
Inferring the most likely explanation for an observation — the formal name for detective-style reasoning. Unlike deduction it only gives "most likely", and it can always be overturned by new evidence.
From general premises to a necessary conclusion: if the premises are true and the reasoning valid, the conclusion must be true. It guarantees validity but creates no new knowledge.
From specific observations to a general rule. The conclusion is "probably true", never guaranteed, and is sensitive to sample bias.
A statement that can be supported or refuted by observation or experiment. Good inference tells you how to test it, rather than just asserting a conclusion.
A claim that cannot be refuted under any circumstance carries little information. Science favours statements that could be shown false.
Update a judgement with new evidence: first ask how common the thing is, then how strong the evidence is. Formally, posterior ∝ prior × likelihood.
How likely an explanation was before seeing the current evidence. Usually driven by base rates.
The updated probability after seeing the evidence — the prior adjusted by the strength of the evidence.
How probable the observed clues would be if the explanation were true. High likelihood means the evidence supports it strongly.
Being carried away by a vivid story while ignoring how rare the thing actually is. A plausible-sounding explanation can still be very unlikely.
Expressing uncertainty as "roughly 60–75%" rather than a single number — more honest when clues are limited.
The first explanation that comes to mind drags later judgement toward it. Counter it by enumerating possibilities before evaluating any of them.
Seeking evidence that supports what you already believe and ignoring the rest. Counter it by asking what would refute the hypothesis.
Seeing only the samples that survived and missing the silent failures, which makes a method look better than it is.
Two things occurring together does not mean one causes the other: it may be coincidence, reversed, or driven by a third factor.
Attribute to oversight or misunderstanding what can be explained that way, rather than to malice. Often used alongside Occam's razor.
Stopping at the first plausible explanation and ignoring alternatives — the most common error in abductive reasoning.