The base rate fallacy occurs when someone evaluates the probability of something by focusing on specific, vivid information while neglecting the base rate — the general frequency of that thing in the overall population. Because individuating details feel more relevant and memorable than dry statistics, people often overestimate how likely an unusual explanation is.
This matters because accurate reasoning requires combining both pieces of evidence: how well the case fits a description and how common that category is to begin with. Ignoring base rates leads to serious errors in medical testing, criminal profiling, risk assessment, and everyday judgments about people.
Example of Base Rate Fallacy
A disease affects 1 in 10,000 people, and a test for it is 99% accurate. Jamal tests positive and concludes he almost certainly has the disease — but because the disease is so rare, the vast majority of positive results are false positives, and his actual chance of being sick is under 1%.
This fallacy is closely related to the representativeness heuristic and the prosecutor's fallacy. It is a reasoning error about probability rather than a flaw in formal logical structure, which is why it is classified as informal.