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Topic: probability assessment

topics > science > Group: psychology



Topic:
models of reality
Topic:
probabilistic and randomized algorithms
Topic:
probability
Topic:
problem solving
Topic:
random number generation
Subtopic: insufficient knowledge up

Quote: people must act without sufficient knowledge
Quote: people use a limited number of heuristic principles to assess probabilities and predict values [»tverA9_1974]

Subtopic: misperception of random sequence up

Quote: no evidence for 'hot hand' or 'streak shooting' in basketball; misperception of random sequences [»giloT7_1985]
Quote: chance is commonly viewed as a self-correcting process. In fact, deviations are merely diluted [»tverA9_1974]

Subtopic: anchoring up

Quote: anchoring: people estimate unknown value by insufficient adjustment from some initial value; e.g., 8x7x6... vs. 1x2x3... [»tverA2_1974]
Quote: subjective probability distributions are overly narrow, due to anchoring; better if don't use best estimate [»tverA2_1974]

Subtopic: overestimate compound events up

Quote: people overestimate the probability of conjunctive events
Quote: people, even when trained, tend to overestimate compound probabilities; polynomial in choices per stage, exponential in stages [»coheJ1_1972]
Quote: people overestimate conjunctive events and underestimate disjunctive ones; explain by anchoring [»tverA2_1974]
Quote: undue optimism about success and scheduling because everything must succeed (conjunction anchoring) [»tverA2_1974]
Quote: undue optimism about risks because any event can fail (disjunctive anchoring) [»tverA2_1974]
Quote: the fallacy of abundance: in a large information retrieval system, it is hard to write reasonable queries that do not retrieve at least some relevant documents [»blaiDC1_1996]

Subtopic: misperception of sample size up

Quote: in judging probabilities, people ignore sample size since no effect on similarity; yet has a major effect on probability [»tverA2_1974]
Quote: people expect than random properties hold in small samples, e.g., HTHTTH vs. HHHHTH or gambler's fallacy [»tverA2_1974]
Quote: experienced research psychologists tend to view small samples as highly representative of populations; leads to overgeneralization [»tverA2_1974]
Quote: similarity, ease of recall, and starting values are good heuristics for subjective probabilities, but people miss sample size and prior probability [»tverA2_1974]
Quote: people fail to learn about the effects of sample size and prior probability because most events are not evaluated statistically
Quote: people predict on the basis of a description even though a prediction is unjustified; e.g., 5 year predictions on inadequate evidence [»tverA9_1974]

Subtopic: deviation towards the mean up

Quote: deviation towards the mean: consider variables X and Y with the same distribution; the extremes of X will be less extreme in Y [»tverA9_1974]

Subtopic: misperception due to recall up

Quote: people estimate risk by ease of imagining problems; may underestimate if miss possible dangers [»tverA2_1974]
Quote: people estimate probability by the ease of recalling instances; e.g., 'r' as 1st vs. 3rd letter, or pairs in 10 elements vs. 8's [»tverA2_1974]
Quote: availability heuristic: people judge probability by the ease of recalling instances or events; can lead to errors [»tverA9_1974]

Subtopic: misperception due to similarities up

Quote: to answer probabilistic questions, people typically look for similarities between choices and ignore prior probabilities [»tverA2_1974]
Quote: people typically assess membership probability by the representativeness heuristic; i.e., is object A representative of class B [»tverA9_1974]
Quote: people ignore prior probability when using representativeness to assess membership probability [»tverA9_1974]
Quote: cue validity is a predictor that an attribute corresponds to a category [»roscE7_1976]


Related Topics up

Topic: models of reality (33 items)
Topic: probabilistic and randomized algorithms (11 items)
Topic: probability (21 items)
Topic: problem solving (32 items)
Topic: random number generation
(29 items)

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