Problem 6 - Judgement And Decision Making

Question 1

Judgement

Answer 1

• involves decising on the likelihood of various events using incomplete information.
• accuracy matters

Question 2

Decision making

Answer 2

• involves selecting one option from several possibilities.
• important matters

Question 3

Problem solving

Answer 3

• generate own solutions rather than choose

Question 4

Decision quality

Answer 4

Consequences:
- a decision can be good given the information available at the time even if its consequences are poor

Question 5

Bayesian inference

Answer 5

• two possible subjective beliefs and new data changes the subjective probability of each hypothesis being correct.
• probability of observing the data, D, if hypothesis A is correct: p(D/HA)

Question 6

Neglecting base rates

Answer 6

• individuals should take into account the base-rat information (relative frequency of an event for a population) but its usually ignored.

Question 7

Heeding base rates

Answer 7

• causal knowledge allows us to make accurate judgements using base rate information sometimes.
• people use base rate when motivated to do so.

Question 8

Heuristics

Answer 8

• strategies that ignore part of the information, with the goal of making decision quickly, frugally and/or accurately.
• reduces effort associated with cognitive tasks

Question 9

Availability heuristic

Answer 9

• the frequencies of events can be estimated by how easy/hard it is to retrieve the event from memory
• based on own experiences (media, affect heuristics (emotions) etc).
• typically accurate as long as its correlated with true, objective frequency.

Question 10

Availability heuristic: factors that can bias availability

Answer 10

1. Recency and vailability: recent events more available.
2. Familiarity and availability: familiar events distorts the frequency estimation.

Question 11

Availability heuristic: overcoming the biases

Answer 11

• using system 2 processing/thinking

Question 12

Availability heuristic: consequences

Answer 12

Illusory correlations:
- deceptive/unreal correlation of two variables that doesn’t exist.

Question 13

Representativeness heuristic

Answer 13

• deciding an object or person belongs to a category because its typical of that category.
• we judge according to similarity and generation of salient features
• its used because it easy, works, relies on anecdotal evidence and doesn’t understand the concept of base rates.

Question 14

Availability heuristic VS representativeness heuristic

Answer 14

• Availability: we are given a category => we must recall the specific example
• Representativeness: we are given an example => we must decide if its similar to the general category it represents.

Question 15

Anchoring-and-adjustment heuristic

Answer 15

• initial estimate (anchor) is used and adjusted to produce final estimate (the adjustment is usually insufficient).
• leads to reasonable answers
• people rely too heavily on the anchor and make small adjustments.
• top-down processing
• powerful
• anchor restricts relevant information in memory.

Question 16

Satisficing heuristic

Answer 16

• consider options one by one, then select the one we find satisfactory.
• when limited working-memory sources, satisficing heuristic is increased.

Question 17

Framing heuristic

Answer 17

• the way information is presented influences the selection of an option
• strong effect

Outcome based on
1. Background context of the choice
2. Framing: risk aversion (saving or losing), certainty

Question 18

Elimination by aspects

Answer 18

• eliminating alternative by focusing on each aspects of each alternatives at a time

Question 19

Evaluation of heuristics

Answer 19

Limitations
- vaguely defined
- limited approach
- inaccurate judgements are not necessarily due to biased processing (small, biased sample, exposure)
- emotional and motivational factors influence judgements and rarely studied
- artificial setting of lab research

Question 20

Biases

Answer 20

• mental shortcuts
• limit and distort our ability to make rational decisions
• centered around estimations of probabilities

Question 21

Biases: illusory correlations

Answer 21

• predisposed to see events going together when they do not.

Question 22

Overconfidence

Answer 22

• over evaluation of own skills, knowledge and judgement
• leads to poor decisions

Reasons:
- unawareness
- we look for examples that confirm our hypotheses
- we cannot recall the other possible hypotheses
- we do not treat the other hypotheses seriously
- education to the public is limited about overconfidence.

Question 23

Hindsight bias

Answer 23

• looking at a situation retrospectively
• we believe we see all the signs leading up to a particular outcome
• hinders learning (cant compare the expectations with the outcome)

Question 24

Belief-bias effect

Answer 24

• rely too heavily on our own beliefs

Question 25

Confirmation bias

Answer 25

• confirm our current hyptheses rather than finding a way to reject it.
• congruency

Question 26

Fallacies: gamble’s fallacy

Answer 26

• mistaken belief that a probability of a random event is influenced by previous random events

Question 27

Fallacies: hot hand effect

Answer 27

• the belief that a certain course of events will continue.

Question 28

Fallacies: conjunction fallacy

Answer 28

• the availability heuristic leads to this
• higher estimate is given for a subset of events than for the larger set of events containing the subset.

Question 29

Fallacies: sunk-cost fallacy

Answer 29

• the decision to continue to invest in something simply because one has invested in it before and one hopes to recover one’s investment

Question 30

Expected utility (normative approach)

Answer 30

We make decisions based on:
- unexpecte utility of the outcomes
- their respective probability

Question 31

Violations of the expected utility theory

Answer 31

• normative description
• assumes humans are rational decision makers
• prediction: choices should show invariance (choice should not depend on how its presented).

Limitations:
- preference rehearsal phenomenon demonstrate inadequacy of the model
- doesnt explain how
- it suggests we make decision through weighting pros and cons but there no way to know all cons with certainty.

Question 32

Prospect theory (descriptive approach)

Answer 32

• kahneman and tversky
• descriptive model - how we make decision and why
• decisions are not based on the absolute value of the end result but on the amount of gain/loss from what we have right now.
• gains and losses are on different scales of value
• more value to gains (increases slowly as a function of the size of gain)
• losses are felt more acutely
• prediction: averse to loss and more individual differences depending on how alternatives are framed.

Question 33

Prospect theory: risky decision making in the brain

Answer 33

• frontal and pareital regions involved (immediate memory and mental imagery)
• framed as gain => prone to risk taking
• framed as losses => look for certainty

Question 34

Prospect theory: psychological accounting

Answer 34

• decisions made depending on how the outcome is felt or perceived
• the difference that harms your mental wellbeing.
• emotions lead to system 1 thinking (often leads to errors)