The base rate fallacy is a cognitive bias where individuals overvalue specific information and ignore the general prevalence (base rate) of an event, leading to misjudgments about likelihoods. It suggests people overlook how common or rare something is, favouring new, seemingly relevant details. This phenomenon has been extensively studied, notably by Kahneman and Tversky, who attributed it to heuristics like representativeness. Critics, such as Gigerenzer, argued that experimenters failed to present uncertainty in understandable forms, specifically natural frequencies. Koehler's work re-examined the fallacy, noting that base rates are almost always used, and their influence depends on task structure and representation. The discussion extends to areas like media credibility and scientific realism.

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