explanatory power

{{Short description|Ability of a theory to explain a subject}}

{{about|explanatory power in the context of the philosophy of science|a statistical measure of explanatory power|Explanatory power (statistics)}}

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Explanatory power is the ability of a hypothesis or theory to explain the subject matter effectively to which it pertains. Its opposite is explanatory impotence.

In the past, various criteria or measures for explanatory power have been proposed. In particular, one hypothesis, theory, or explanation can be said to have more explanatory power than another about the same subject matter{{cn|date=November 2021}}

• If more facts or observations are accounted for;
• If it changes more "surprising facts" into "a matter of course" (following Peirce);
• If more details of causal relations are provided, leading to a high accuracy and precision of the description;
• If it offers greater predictive power (if it offers more details about what should be expected to be seen and not seen);
• If it depends less on authorities and more on observations;
• If it makes fewer assumptions;
• If it is more falsifiable (more testable by observation or experiment, according to Popper).
• If it can be used to compress encoded observations into fewer bits (Solomonoff's theory of inductive inference)

Recently, David Deutsch proposed that theorists should seek explanations that are hard to vary. A theory or explanation is hard to vary if all details play a functional role, i.e., cannot be varied or removed without changing the predictions of the theory. Easy to vary (i.e., bad) explanations, in contrast, can be varied to be reconciled with new observations because they are barely connected to the details of the phenomenon of question.