Book:
Judgment under Uncertainty: Heuristics and Biases
Editors:
Kahneman, D., Slovic, P., & Tversky, A.
Type:
Category:
Pages:
414-421
Year:
1982
Publisher:
Cambridge University Press
Place:
New York
Abstract:
The approach presented here is based on the following general notions about forecasting. First, that most predictions and forecasts contain an irreducible intuitive component. Second, that the intuitive predictions of knowledgeable individuals contain much useful information. Third, that these intuitive judgments are often biased in a predictable manner. Hence, the problem is not whether to accept intuitive predictions at face value or to reject them, but rather how they can be debiased and improved.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education