Basic Concepts: Difference between revisions
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==Probability Judgment== | ==Probability Judgment== | ||
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===The Methods of Behavioral Economics=== | |||
*They define themselves, not on the basis of the research methods that they employ, but rather their application of psychological insights to economics. | |||
===Heuristic Mechanism=== | ===Heuristic Mechanism=== | ||
*Availability heuristic | |||
**people may judge the probabilities of future events based on how easy those events are to imagine or to retrieve from memory" </b> | |||
*Hindsight bias | |||
**"Because events which actually occurred are easier to imagine than counterfactual events that did not, people often overestimate the probability they previously attached to events which later happened" | |||
*Curse of Knowledge bias | |||
**"people who know a lot find it hard to imagine how little others know | |||
*Representativeness | |||
**"People judge conditional probabilities like P(hypothesis|data) or P(examples| class) by how well the data represents the hypothesis or the example represents the class. | |||
**<b> Law of Small Numbers </b> | |||
*** "Small samples are thought to represent the properties of the statistical process that generate them" | |||
Revision as of 01:52, 2 May 2007
Basic Concepts
Probability Judgment
The Methods of Behavioral Economics
- They define themselves, not on the basis of the research methods that they employ, but rather their application of psychological insights to economics.
Heuristic Mechanism
- Availability heuristic
- people may judge the probabilities of future events based on how easy those events are to imagine or to retrieve from memory"
- Hindsight bias
- "Because events which actually occurred are easier to imagine than counterfactual events that did not, people often overestimate the probability they previously attached to events which later happened"
- Curse of Knowledge bias
- "people who know a lot find it hard to imagine how little others know
- Representativeness
- "People judge conditional probabilities like P(hypothesis|data) or P(examples| class) by how well the data represents the hypothesis or the example represents the class.
- Law of Small Numbers
- "Small samples are thought to represent the properties of the statistical process that generate them"
