Problem 5 - decision making Flashcards
neglecting base rate
- base rate info: relative frequency with which an event occurs or an attributer is present in the population
- > often people ignore base rate info
heuristics and biases
-cognitively undemanding ad can be used very rapidly
fast and frugal heuristics (3)
1) representativeness
2) recognition
3) availability
Availability heuristics
- estimating the frequencies of events on the basis of how easy/difficult it is to retrieve relevant information from LTM
- > availability-by-recall mechanism
- > fluency mechanism
Availability-by-recall mechanism
- actually recalling stuff
- certain number of instances for example
fluency mechanism
- judging something by deciding how easy it would be to bring relevant instances to mind
- NOT actually retrieving them
representativeness heuristic
- we estimate the likelihood of an event by comparing it to an existing prototype that already exists in our minds
- prototype=what we think is the most relevant or typical example of a particular event or object
-assumption that representative or typical members of a category are encountered more often
BUT: Just because an event or object is representative does not mean its occurrence is more probable
example representativeness heuristic
- you are given a description of an individual
- estimate probability he/she has a certain occupation
- > you would estimate probability in terms of similarity between individuals description and your stereotype of that occupation
conjunction fallacy
- mistaken belief that the probability of a conjunction of two events (A and B) is greater than the probability of one of them (A or B)
- seems to involve representativeness heuristics
recognition heuristic
- if one of two objects is recognized and the other is not
- > infer that the recognized object has the higher value with respect to the criterion
- using take-the-best strategy
example recognition heuristic:
- presenting 2 city names
- > deciding which one is larger
- we choose the city we know the name of as bigger even if we have no knowledge about the actual size
take-the-best strategy
- 3 components
1) search rule: search cues
2) stopping rule: stop after finding a discriminatory cue
3) decision rule: choose outcome
Biases (5)
1) hindsight bias
Biases (5)
1) hindsight bias
2) overconfidence
3) confirmation bias
4) omission bias
4) anchoring
Confirmation Bias
-tendency to search only for information that confirm one’s initial beliefs or hypotheses
Anchoring
-relying too much on an initial piece of information offered
overconfidence
- rejecting any help
- weighting own intuitions more heavily than objective information
- people’s impression of their own accuracy inflated
framing (key word) effect
-the influence of irrelevant aspects of a situation (e.g. wording of the problem) on decision making
loss aversion
-individuals are much more sensitive to potential losses than to potential gains
illusionary correlation
- falsely associated variables
- often due to prior associations in people’s minds
Sunk Cost Effects
-tendency to continue something one has already invested time, money and effort into , even though that doesn’t affect the likelihood of future success
phases of decision making (5)
1) set and revise goals
2) gathering info about options and consequences
3) decision structuring -> organizing all info and options
4) make final selection/ choice
5) evaluation -> good/bad processes of decision making
phases of decison making (5)
1) set and revise goals
2) gathering info about options and consequences
3) decision structuring -> organizing all info and options
4) make final selection/ choice
5) evaluation -> good/bad processes of decision making
descriptive models (5)
1) bounded rationality - thaler
2) image theory
3) prospect theory- kahneman
4) recognition-primed decision making
5) constructivist approach
descriptive models (5)
1) bounded rationality - Thaler
2) image theory
3) prospect theory- Kahneman
4) recognition-primed decision making
5) constructivist approach
Prospect Theory - Kahneman
-key word
- decisions based on the evaluation of potential value of losses and gains ( as utility theory)
- but includes individuals reference point ( emotions, framing point)
- using heuristics
utility models (2)
- based on dominance principle
1) expected utility theory
2) multi-attribute utility theory (MAUT) - > integrating different dimensions and goals of complex decisions
- > more complex than normal EUT
- > people don’t use MAUT when too much info and too many dimensions available
satisficing
- simon
- cognitive heuristic that entails searching through the available alternatives until an acceptability threshold is met
- considering various options one at a time
- select first one meeting minimum requirements
- aims for satisfactory or adequate results rather than the optimal solution
- > acceptability threshold
nudging
- steer people in particular direction while still allowing them to go their own way
- alter ‘choice architecture’: the background against which choices are made
simon, kahneman, thaler
-key names
Expected utility model - Bernoulli
- normative model of decision making
- explains why most people are risk adverse
- based on the assumption that everyone is rational
- dominance principle
how to calculate expected outcome - expected value
probability of each outcome x amount of money won/lost for that outcome
-> sum these values over all possible outcomes
EV (expected value) = (pi, probability of the ith outcome x vi, monetary value of the ith outcome)
expected utility -calculation
-EU= (pixui)
-not all decisions involve monetary outcomes (values) but are rather useful for people (happiness, success etc)
=> utility of an outcome
prospect theory - people don’t make their choices based on their expected gains because : (2)
1) individuals identify a reference point, that represents their current state (framing point)
2) individuals are much more sensitive to potential losses than to gains ( loss aversion)
how uber influences drivers
- nudging
- internalized motivation
- loss aversion
normative models
-ideal performance under ideal circumstances
prescriptive models
-how we ought to make decisions, provide guidance about how to do the best we can, even in non-ideal situations
descriptive models
-detail what people actually do when making decisions
dominance principle
?
Gambler’s fallacy/ Monte Carlo fallacy
-mistaken belief that, if something happens more frequently than normal during a given period, it will happen less frequently in the future
image theory - beach & Mitchell
- descriptive model
- people don’t follow structured decisions
- most decision making is done during ‘pre choice screening of options’ -> boil down number of options under active consideration
- > as weather plan/goal/alternative is compatible with 3 images
3 images - image theory
1) Value images - decision maker’s values, morals, principles
2) Trajectory images - goals & aspiration for the future
3) Strategic image - way in which decision makers plan to attain his/her goals
- > options judged incompatible with at least one of images -> dropped from further consideration
omission bias
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