Judgment under Uncertainty: Heuristics and Biases (Anchoring)
Amos Tversky & Daniel Kahneman · 1974
"When estimating an unknown quantity, people rely heavily on the first number they're exposed to, the anchor, and adjust insufficiently away from it — even when that anchor is arbitrary, irrelevant, or explicitly randomly generated."
In one of the paper's experiments, participants spun a wheel rigged to land on either 10 or 65, then were asked to estimate the percentage of African countries in the United Nations. Despite knowing the wheel was random, people who saw 65 gave estimates almost double those who saw 10 — the arbitrary number contaminated an unrelated factual judgment.
Tversky and Kahneman explain this through insufficient adjustment: people don't ignore the anchor and reason from scratch, they start from it and adjust toward what feels right, but typically stop adjusting too early, leaving the final estimate biased toward the starting point. This is why anchoring shows up powerfully in negotiations, where the first number stated tends to pull the final agreed price toward it, and in pricing, where an inflated original price makes a discount look larger, even if the discounted price is still unreasonable.
What did Tversky and Kahneman's wheel-spinning experiment demonstrate about anchoring?
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The explanation above is written with AI assistance. These are the originals — go to them to check it.
- Judgment under Uncertainty: Heuristics and Biases (full paper)Tufts University
Judgment under Uncertainty: Heuristics and Biases (Availability)
"People estimate how frequent or likely something is by how easily examples come to mind — which means vivid, recent, or heavily-reported events get judged as far more common than they actually are, while common but unremarkable events get systematically underestimated."