College 3 Flashcards
heuristics
are cognitive shortcuts or rules of thumb employed in judgement and decision problems
- advantage: little processing effort, not time consuming, often sufficiently accurate
- disadvantage: systematic judgement distortions (“biases”) can occur
quasi-rational
within the parameters (time, effort, resources) of decision processes, behaviour is bounded by the individual’s cognitive capacity to process information. this makes behaviour rational to a certain degree.
bounded rationality
is a human decision-making process in which we attempt to satisfice, rather than optimize. In other words, we seek a decision that will be good enough, rather than the best possible decision.
representatitveness heuristic
how typical is the element for its specific category? Representativeness is used as basis for categorization and probability judgments
base rate fallacy
how we tend to rely more on specific information than we do statistics when making probability judgments.
Conjuction Fallacy
is a fallacy or error in decision making where people judge that a conjunction of two possible events is more likely than one or both of the conjuncts.
the hot hand phenomenon
belief that a player who scored twice or three times in a row is more likely to score again
gambler’s fallacy
refers to our belief that the probability of a random event occurring in the future is influenced by the past history of that type of event occurring.
availability heuristic
When assessing the frequency of an event, individuals often employ a strategy that is based on the ease (or difficulty) of information retrieval or generation from memory.
> “If I can easily imagine or recall it, I guess it is more probable to occur.”
anchoring & adjustment heuristic
When we make judgements, we often find an initial, rough starting point.
Individuals gauge numerical size by starting from an initial value (anchor) and adjust it during the subsequent course of judgement to arrive at their final judgement
prospect theory
Differences between small gains/losses weigh more than between big gains/losses (diminishing marginal utility)
* Wins and losses are weighted differently (loss aversion)
* Leading to a non-linear function of probability estimates