# Heuristics & Bias

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- Created by: Chloe
- Created on: 26-04-15 23:14

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- Heuristics & Bias
- Availability Heuristic: People 'assess' the frequency of a class or the probability of an event by the ease with which instances or occurrences are bought to mind
- Representatives Heuristic: When judging the probability that A belongs to class B we make a judgement on how closely A resembles or is typical of something from class B.
- Prospect Theory, Kahneman & Tversky (1979): Prospect theory predicts over-weighting of small probabilities and under-weighting of medium and high probabilities.
- (1)Reference point – generally reflecting current state (although some work considers other counter factual reference points
- (3)Marginally diminishing utility – results in risk aversion in cases of gains (because a slightly larger risky gain isn’t worth much more than a smaller certain gain) and risk seeking in cases of loss (because a greater possible loss isn’t that much worse than a certain smaller loss).

- (2)Loss aversion - people dislike potential loss more than they like potential gain. So the curve is steeper for losses than for gains.
- (4)Non-linear probability weighting – EUT predicts a linear probability weighting.

- Prospect theory allows us to explain many phenomenon that cannot be explained by EUT: •Gambling on the lottery and taking out insurance are both explained by the overweighting of small probabilities. •Loss aversion. People reject a 50/50 chance of winning £200 versus losing £100 even though the potential gain is twice that of the potential loss (Tversky & Shafir 1992). •Preference reversal, e.g. the Allais (1988) paradox, explained by the subjective nature of the reference point.

- (1)Reference point – generally reflecting current state (although some work considers other counter factual reference points
- The Conjunction Fallacy: Failure to recognise the probability of a conjunction of two events cannot exceed the probability of either of the component events alone. (By the rules of probability, p(X & Y) ? p(X)}
- Anchoring & Adjustment Heuristic: People make judgement by starting with an initial value & then adjusting it to reach their final judgement.

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