
Contents
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Decisions from description and decisions from experience Decisions from description and decisions from experience
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Decisions from experience: heeding small samples' call Decisions from experience: heeding small samples' call
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Gambling in Smallville: why intuitive sampling may be destined to be frugal Gambling in Smallville: why intuitive sampling may be destined to be frugal
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The amplification effect: a simple proof The amplification effect: a simple proof
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The amplification effect: an analysis based on simulation The amplification effect: an analysis based on simulation
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How robust is the amplification effect? How robust is the amplification effect?
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How does more processing affect the amplification effect? How does more processing affect the amplification effect?
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Bayesian probability updating: will the amplification effect persist? Bayesian probability updating: will the amplification effect persist?
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Weighting of outcomes and probabilities: will the amplification effect persist? Weighting of outcomes and probabilities: will the amplification effect persist?
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Fine: small-sample choices are easier, but how competitive are they? Fine: small-sample choices are easier, but how competitive are they?
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If life is a gamble, then it is not one but many If life is a gamble, then it is not one but many
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Some potential benefits of small samples Some potential benefits of small samples
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Sample size and choice difficulty: empirical evidence Sample size and choice difficulty: empirical evidence
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The generality of our analysis The generality of our analysis
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Conclusion Conclusion
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Authors' note Authors' note
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References References
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10 The game of life: How small samples render choice simpler
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Published:March 2008
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Abstract
This chapter highlights the importance of simplicity, but in a different way — it argues that, where people sample statistical information from experience, they tend to rely on surprisingly small samples (e.g. focusing on a few recent events). It presents a formal analysis of possible reasons behind this reliance on small samples. Three key results emerge. First, small samples amplify the difference between the average earnings associated with the payoff distributions, thus rendering choices simpler. Second, people who use a simple choice heuristic or choose in accordance with prospect theory benefit from this amplification effect, whereas Bayesian updates do not. Third, although not providing a strictly veridical portrayal of the world, small samples can give rise to surprisingly competitive choices.
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