Problem 5 - decision making

Question 1

neglecting base rate

Answer 1

• base rate info: relative frequency with which an event occurs or an attributer is present in the population
• > often people ignore base rate info

Question 2

heuristics and biases

Answer 2

-cognitively undemanding ad can be used very rapidly

Question 3

fast and frugal heuristics (3)

Answer 3

1) representativeness
2) recognition
3) availability

Question 4

Availability heuristics

Answer 4

• 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

Question 5

Availability-by-recall mechanism

Answer 5

• actually recalling stuff

- certain number of instances for example

Question 6

fluency mechanism

Answer 6

• judging something by deciding how easy it would be to bring relevant instances to mind
• NOT actually retrieving them

Question 7

representativeness heuristic

Answer 7

• 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

Question 8

example representativeness heuristic

Answer 8

• 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

Question 9

conjunction fallacy

Answer 9

• 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

Question 10

recognition heuristic

Answer 10

• 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

Question 11

example recognition heuristic:

Answer 11

• 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

Question 12

take-the-best strategy

Answer 12

• 3 components
  1) search rule: search cues
  2) stopping rule: stop after finding a discriminatory cue
  3) decision rule: choose outcome

Question 13

Biases (5)

Answer 13

1) hindsight bias

Question 14

Biases (5)

Answer 14

1) hindsight bias
2) overconfidence
3) confirmation bias
4) omission bias
4) anchoring

Question 15

Confirmation Bias

Answer 15

-tendency to search only for information that confirm one’s initial beliefs or hypotheses

Question 16

Anchoring

Answer 16

-relying too much on an initial piece of information offered

Question 17

overconfidence

Answer 17

• rejecting any help
• weighting own intuitions more heavily than objective information
• people’s impression of their own accuracy inflated

Question 18

framing (key word) effect

Answer 18

-the influence of irrelevant aspects of a situation (e.g. wording of the problem) on decision making

Question 19

loss aversion

Answer 19

-individuals are much more sensitive to potential losses than to potential gains

Question 20

illusionary correlation

Answer 20

• falsely associated variables

- often due to prior associations in people’s minds

Question 21

Sunk Cost Effects

Answer 21

-tendency to continue something one has already invested time, money and effort into , even though that doesn’t affect the likelihood of future success

Question 22

phases of decision making (5)

Answer 22

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

Question 23

phases of decison making (5)

Answer 23

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

Question 24

descriptive models (5)

Answer 24

1) bounded rationality - thaler
2) image theory
3) prospect theory- kahneman
4) recognition-primed decision making
5) constructivist approach

Question 25

descriptive models (5)

Answer 25

1) bounded rationality - Thaler 2) image theory 3) prospect theory- Kahneman 4) recognition-primed decision making 5) constructivist approach

Question 26

Prospect Theory - Kahneman | -key word

Answer 26

- 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

Question 27

utility models (2)

Answer 27

- 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

Question 28

satisficing

Answer 28

- 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

Question 29

nudging

Answer 29

- steer people in particular direction while still allowing them to go their own way - alter 'choice architecture': the background against which choices are made

Question 30

simon, kahneman, thaler

Answer 30

-key names

Question 31

Expected utility model - Bernoulli

Answer 31

- normative model of decision making - explains why most people are risk adverse - based on the assumption that everyone is rational - dominance principle

Question 32

how to calculate expected outcome - expected value

Answer 32

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)

Question 33

expected utility -calculation

Answer 33

-EU= (pixui) -not all decisions involve monetary outcomes (values) but are rather useful for people (happiness, success etc) => utility of an outcome

Question 34

prospect theory - people don't make their choices based on their expected gains because : (2)

Answer 34

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)

Question 35

how uber influences drivers

Answer 35

- nudging - internalized motivation - loss aversion

Question 36

normative models

Answer 36

-ideal performance under ideal circumstances

Question 37

prescriptive models

Answer 37

-how we ought to make decisions, provide guidance about how to do the best we can, even in non-ideal situations

Question 38

descriptive models

Answer 38

-detail what people actually do when making decisions

Question 39

dominance principle

Answer 39

?

Question 40

Gambler's fallacy/ Monte Carlo fallacy

Answer 40

-mistaken belief that, if something happens more frequently than normal during a given period, it will happen less frequently in the future

Question 41

image theory - beach & Mitchell

Answer 41

- 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

Question 42

3 images - image theory

Answer 42

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

Question 43

omission bias

Answer 43

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