Reasoning uses information and relationships to form conclusions, explanations or decisions. Deductive reasoning asks what follows from stated premises, while probabilistic reasoning evaluates uncertain possibilities. The format of a problem can change performance without changing its underlying numerical relationships: expressing information as natural frequencies can make conditional relationships easier to track. This separates a person’s knowledge from the processing demands imposed by a representation. [ref]
Drawing a conclusion after comparatively limited evidence under a specified task. A beads task measures information sampling under particular demands, not a direct readout of every real-world belief process.
An information-sampling task in which observations from a source are used to infer which source generated them. Decisions about when to stop sampling can investigate reasoning tendencies, with comprehension and task incentives affecting interpretation.

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