Base Rate
The underlying probability of an event before considering specific evidence or conditions.
Also known as: Prior probability, Background rate, Base rate fallacy
Category: Concepts
Tags: statistics, probabilities, cognitive-biases, decision-making, thinking
Explanation
The base rate is the underlying probability of an event occurring in a population before considering any specific evidence. Base rate neglect (or base rate fallacy) is the tendency to ignore this background probability when evaluating new information. Classic example: if a disease affects 1 in 10,000 people and a test is 99% accurate, a positive result still only means ~1% chance of having the disease (because false positives vastly outnumber true positives when the base rate is low). Base rates matter for: medical diagnosis (rare diseases), hiring decisions (success rates in roles), predictions (frequency of events), and risk assessment (actual probability of outcomes). To use base rates properly: start with the background probability, update based on evidence (Bayesian reasoning), and recognize when specific information should override base rates versus when it shouldn't. Base rate neglect occurs because: specific information is vivid and compelling, base rates are abstract, and we're drawn to narratives over statistics. For knowledge workers, base rate thinking helps: make better predictions, evaluate claims realistically, and avoid overreacting to specific but statistically weak evidence.
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