judgement & decision making

Question 1

6 Forms of Thinking

Answer 1

• problem solving
• decision making
• judgement
• inductive reasoning
• deductive reasoning
• informal reasoning

Question 2

Define Judgement

Answer 2

• “An assessment of the probability of a given event occurring based on incomplete information” (Eysenck & Keane, 2015)
• deciding on likelihood of various events using incomplete info
• what matters in judgement is accuracy

Question 3

Define Decision Making

Answer 3

• “Making a selection from various options; if full information is unavailable, judgement is required” (Eysenck & Keane, 2015)
• selecting one option from several possibilities
• factors involved in DM depend on importance of the decision

Question 4

Define Problem Solving

Answer 4

Cog activity that involves moving from the recognition of a problem through a series of steps to the solution

Question 5

Define Deductive Reasoning

Answer 5

• deciding what conclusions follow necessarily
• provided that various statements are assumed true
• a form of reasoning that’s supposed to be based on logic
• something is true if it follows a rule/fact
• begins with a theory, supports it with observation and eventually arrives at a confirmation
• e.g. if beverages can be drank through straws, then soup is a beverage

Question 6

Define Inductive Reasoning

Answer 6

• deciding whether certain statements or hypotheses are true on the basis of the available info
• used by scientists & detectives
• not guaranteed to produce valid conclusions
• something is true if it follows a patten/trend
• begins with an observation, supports it with patterns and then arrives at a hypothesis or theory
• e.g. everyone is eating soup, so soup must be tasty

Question 7

Define Informal Reasoning

Answer 7

• evaluating the strength of arguments by taking account of one’s knowledge & experience

Question 8

Iowa Gambling Task

Answer 8

• One interesting outcome: how often people decide on the “high-risk” decks (A/B) or the “low-risk” decks (C/D)
• Another interesting outcome: how long it took people to decide before they made a low or high-risk decision

Question 9

What it’s used for

Bayes’ Theorem

Answer 9

Rev Thomas Bayes:
* used in situations with two possible beliefs or hypotheses (e.g. X is lying vs X is not lying)
* shows how new info/data change probabilities of each hypothesis being correct

Question 10

What is the formula?

Bayes’ Theorum Formula

Answer 10

p(Ha/D) = p(Ha) x p(D/Ha)
(over) . (over) . (over)
p(Hb/D) . p(Hb) . p(D/Hb)

1 probabilties we want to calculate
2 prior odds
3 data given hypothesis

Question 11

Bayes’ Theorum: 2 things that need to be done

Answer 11

• assess relative probabilities of the 2 hypotheses before the data are obtained (prior odds)
• need to calculate relative probabilities of obtaining the observed data under each hypothesis (likelihood ratio)

Question 12

Bayes’ Theorum: What Does it Evaluate?

Answer 12

The probability of observing the data (D), if hypothesis A is correct, written as p(D/Ha), and if hypothesis B is correct, written p(H/Db)

(a & b = smaller & lower)

Question 13

Bayes’ Theorum: What is it Expressed as?

Answer 13

An odds ratio

Question 14

Bayes’ Theorum: What each Part of the Formula Means

Answer 14

1 (left):
* relative probabilities of hyp A & B in light of the new data
* probabilities we want to calculate

2 (middle):
* prior odds of each hyp being before the data were collected

3 (right):
* likelihood ratio based on probability of the data given each hyp

relative probs = prior odds x likelihood ratio

Question 15

What is Base-rate Information?

Answer 15

The relative frequency of an event within a given population

Question 16

What is the Taxi Cab Problem?

Answer 16

(Kahneman & Tversky, 1972):
* taxi cab in hit & run
* eye witness claims cab was blue
* city has 2 taxi companies: blue (15%) & green (85%)
* EW correctly identifies blue cab 80% of the time (but wrong 20%)
* what’s the probability the taxi was blue?

Question 17

What did the Taxi Cab Problem Find?

Answer 17

(Kahneman & Tversky, 1972):
* shows how the base rate is neglected (i.e. prior odds)
* most ppts ignored the base-rate info about the relative numbers of green & blue cabs
* ppts only considered the witness’s evidence
* ppts concluded an 80% likelihood the taxi was blue rather than green

Question 18

Calculate the Taxi Cab Problem using Bayes’ Theorum

Answer 18

0.15 x 0.80 = 0.12
(over) (over) (over)
0.85 . 0.20 . 0.17

odds ratio = 12.17
chance taxi is blue = 41% (12/29)
chance taxi is green = 59%

Prior odds:
p(Ha) = 0.15 (probability cab is blue)
p(Hb) = 0.85 (probability cab is green)

Data given the hypothesis:
p(D|Ha) = 0.8 (probability cab is blue when it is blue)
p(D|Hb) = 0.2 (probability cab is green when it is blue)

Bayes’ Theorem:
0.15 x 0.8 = 0.12 = 0.41 (41%) (probability cab was blue)
0.85 0.2 0.17

Question 19

Heuristics Definition (Tversky & Kahneman, 1974)

Answer 19

Most people use heuristics (rules of thumb) in judgement tasks

Question 20

Heuristics Definition (Eysenck & Keane, 2010)

Answer 20

Rules of thumb that are cognitively undemanding & often approximate accurate answers

Question 21

Representiveness Heuristic: 2 Definitions & 1 Reason for Usage

Answer 21

Kahneman & Tversky (1973):
The assumption that an object/individual belongs to a specified category because it’s representative (typical) of that category

Kellogg (1995):
“Events that are representative or typical of a class are assigned a higher probability of occurrence”

Used for:
Can be used as an alternative strategy when participants show base-rate neglect

Example:
* Jack is a 45-year-old man. He is married & has 4 children. He is generally conservative, careful, & ambitious. He shows no interest in political & social issues & spends most of his free time on his many hobbies, which include home carpentry, sailing, & numerical puzzles
* 70 such descriptions are of lawyers; 30 of engineers- Is Jack a Lawyer or Engineer?

Question 22

Define Conjuction Fallacy

Answer 22

(Tversky & Kahneman, 1983)

Eysenck & Keane (2015):
“The mistaken assumption that the probability of a conjunction of two events (A & B) is greater than the probability of one of them (A or B)”

Example: (Manktelow, 2012):
* Linda is 31 years old, single, outspoken, & very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination & social justice, & also participated in anti-nuclear demonstrations
* how would you best describe Linda: - a feminist- a bank teller- a feminist & a bank teller?
* most ppts believed it more probable that Linda was a feminist & a bank teller rather than a feminist or a bank teller

Question 23

Define Availability Heuristic

Answer 23

Tversky & Kahneman (1974):
* the rule of thumb that the frequences of events can be estimated accurately by the subjective ease with which they can be retrieved
Lichenstein et al. (1978):
* asked ppts to judge relative likelihood of different causes of death
* causes that attract more publicity (murder) were judged more likely than those that don’t (suicide) - the opposite is the case
* findings suggest people use the availability heuristic

Question 24

Follow up Research into ‘Judged Likelihood of Causes of Death’

Answer 24

Pacher et al (2012):
3 ways of explaining people’s judged probabilities/frequencies of various causes of death:
1.) may use availability heuristic based on their own experiences
2.) may use availability heuristic based on media coverage & own experiences
3.) may use affect heuristic

Results:
* availability based on recall of direct experiences was the best predictor of judged frequences of different causes of death
* judged risks also predicted by the affect heuristic
* availability based on media coverage was the least successful predictor

Affect Heuristic:
* using one’s emotional responses to influence rapid judgements or decisions
* “gauge your feeling of dread that Risk A and Risk B evoke and infer that risk to be more prevalent in the population for which the dread is higher”

Question 25

Heuristics & Biases Approach: Support

Answer 25

+much research evidence for the use of heuristics in different context
+demonstrates that individuals are prone to errors, including experts
+the approach has influenced psychology, economics, philosophy & politics
+heuristics Minimise ‘cognitive load’ (Kool et al, 2010; Fiedler & von Sydow, 2015)

Question 26

Heuristics & Biases Approach: Criticisms

Answer 26

-the term heuristic is used widely & may lose real meaning
-ppts may misunderstand the problem rather than make errors of judgement: e.g. many ppts believe “Linda is a bank teller” implies she is not an active feminist
-availability heuristic may be explained by media coverage rather than faulty thinking
-correct or accurate judgements cannot be explained by this approach
-research is artificial & lacks ecological validity

Question 27

Fast & Frugal Heuristics

Answer 27

Gigerenzer & Gaissmaier (2011):
* heuristics are often very valuable
* central focus on F&F heuristics involving rapid processing of little info
* we possess an “adaptive toolbox” consisting of several heuristics

Question 28

What is the Best Fast & Frugal Heuristic?

Answer 28

Goldstein & Gigerenzer (2002):
‘Take-the-best Strategy’
* (take the best, ignore the rest)
3 Components:
1.) search rule: search cues (e.g. name recognition)
2.) stopping rule: stop after finding discriminatory cue
3.) decision rule: choose outcome

Question 29

Study on the ‘Take-the-best’ Strategy

Answer 29

Goldstein & Gigerenzer (2002):
* ppts given pairs of cities from home county (Germany or USA)
* asked which city has largest population
* ppts performed worse on home country cities because they couldn’t use recognition heuristic

Question 30

Define Recognition Heuristic

Answer 30

Using the knowledge that only 1 out of 2 objects is recognised as the basis for making a judgement

Question 31

Fast & Frugal Heuristics: Support

Answer 31

+research evidence for the use of fast & frugal heuristics
+allows individuals to make immediate judgements when under cognitive or time constraints

Question 32

Fast & Frugal Heuristics: Criticisms

Answer 32

-heuristics used less than predicted (Newell et al., 2003; Oppenheimer, 2003)
-heuristics may not be as simple as implied e.g. take-the-best involves hierarchical organisation of cues
-does not explain complex decision-making e.g. who should I marry?
-lack predictive & explanatory power

Question 33

What is the Dual-Process Model?

Answer 33

Kahneman (2003):
* people rely on heuristics as they’re rapid & effortless
* however, sometimes complex cog processes can be used
* probability judgements depend on processing within 2 systems:

System 1:
Judgements are:
* fast, automatic, effortless
* implicit (not open to introspection)
* often emotionally charged
* difficult to modify/control
* most heuristics involve S1

System 2:
Judgements are:
* slower, serial, effortful
* likely to be consciously monitored & deliberately controlled
* relatively flexible & potentially rule-governed

S1 vs S2:
* S1 rapidly generates intuitive answers to judgement problems which are monitored/evaluated by S2, which may correct them
* however, we may make little or no use of S2

Question 34

Research (2) into the Dual-Process Model

Answer 34

De Neys (2006):

Study 1.) Linda problem
* ppts with correct answer (presumably used S2) took almost 40% longer than ppts only using S1
* results consistennt with assumption it takes longer to use S2

Study 2.) Conjunction Fallacy:
* compared performance on same problem, performed on their own or with a demanding secondary task requiring use of central executive
* Exp 1: used CF problems
* Exp 2: used CF problems & tapping sequence (CE task)
* ppts performed worse on problems with secondary task
* Exp 1: 17% correct
* Exp 2: 9.5% correct
* results as predicted as S2 involves use of cognitively demanding processes

Question 35

Dual-process Model: Support

Answer 35

+research evidence supports two judgement processes
+most data suggests judgements are made using S1 Dual-process models are proposed in other areas & are supported

Question 36

Dual-process Model: Criticisms

Answer 36

-assumes ppts rely more on S1 than S2; De Neys & Glumicic (2008) suggests ppts can use S2
-model is not explicit about processes involved in making judgements
-suggests serial processing, S1 -> S2; Evans (2007) suggests S1 & S2 could operate in parallel

Question 37

Utility Theory

Answer 37

von Neumann & Morgenstern (1944):

Utility: the subjective value of we attach to an outcome

Formula:
(subjective) expected utility = (probability of a given outcome) x (utility of the outcome)

Question 38

What are Normative Theories?

Answer 38

Theories focused on how people should make decisions rather than how they actually make them

Question 39

Example of a Normative Theory

Answer 39

Utility Theory (von Neumann & Morgenstern, 1944)

Question 40

Prospect Theory

Answer 40

Kahneman & Tversky (1979, 1984):
* theory to explain paradoxical findings
2 Assumptions:
1.) individuals identify reference point generally representing current state (RP is where the lines intersect)
2.) individuals are more sensitive to potential losses than potential gains (loss aversion)
.
* a cognitive bias that describes why, for individuals, the pain of losing is psychologically twice as powerful as the pleasure of gaining
* positive values increase slowly as gains become greater; winning £200 instead of £100 does not double subjective value
* negative values increase rapidly as losses become greater

Question 41

Define Loss Aversion

Answer 41

Kahneman & Tversky (1979, 1984):
The greater sensitivity to potential losses than potential gains shown by most people engaged in decision making

Question 42

What is the Framing Effect?

Answer 42

Kahneman & Tversky (1981):
The findings that decisions can be influenced by situational aspects (e.g. problem wording) irrelevant to good decision making

Question 43

What is the Sunk-cost Effect?

Answer 43

• a phenomenon resembling loss aversion
• “a tendency for people to pursue a course of action even after it has proved to be suboptimal, because resources have been invested in that course of action (Braverman & Blumenthal-Barby, 2012)
• “a greater tendency to continue an endeavour once an investment in money, effort or time has been made” (Arkes & Ayton, 1999)

Question 44

Prospect Theory: Support

Answer 44

+provides a psychological account of decision-making compared to normative theories
+the value function (more weight given to losses than gains) explains many phenomena

Question 45

Prospect Theory: Criticisms

Answer 45

-there is no rationale for the value function
-does not include social & emotional factors on decision making
-theory de-emphasises individual differences

Question 46

Complex Decision-making:
Multi-attribute Utility Theory

Answer 46

Wright (1984):
Stages:
1.) identify attributes relevant to the decision
2.) decide how to weight those attributes
3.) list all options under consideration
4.) rate each option on each attribute
5.) obtain a total utility & select the one with the highest weighted total

Question 47

Complex Decision-making: Bounded Rationality

Answer 47

Simon (1957):
* decision making is ‘bounded’ (restricted) by environmental constraints (e.g. info costs) & by cog constraints (e.g. limited attention)
* people are as rational as the constraints of the enviro & the mind permit
* unbounded rationality: the view that all relevant info is available for use to the decision-maker

Question 48

Complex Decision-making: What Does Bounded Rationality Lead to?

Answer 48

Simon (1957):
Satisficing:
* the strategy of choosing the first option that satisfies the individual’s minimum requirements
* not guaranteed to produce the best decision
* useful when options become available at diff times (e.g. potential romantic partners)
* word is formed from the words ‘satisfactory’ and ‘sufficing’” (Eysenck & Keane, 2010)

Question 49

Elimination-By-Aspects Theory

Answer 49

Tversky (1972):
* eliminate options by considering one relevant attribute/aspect after another
* e.g. when choosing a house, eliminate houses over price budget (attribute)

Question 50

Elimination-By-Aspects Theory: Criticism

Answer 50

• the option selected varies as a function of the order in which the attributes are considered
• as a result, the choice made may not be the best one

Question 51

Elimination-By-Aspects Theory: Modified Version

Answer 51

Kaplan et al. (2011):
2 stage theory:
1.) options meeting criteria are retained (reduces options to manageable number)
2.) detailed comparisons of the patterns of attributes of the retained options (often only feasible with small no. of options)

Question 52

Elimination-By-Aspects Theory: Evidence

Answer 52

Payne (1976):
* had ppts decide which apartment to rent using various attributes (presented on cards)
* initial decisions used simple strategies (satisficing & elimination-by-aspects)
* when a few apartments remained, the final decision was made using a more complex strategy (multi-attribute utility theory)

Question 53

Naturalistic Decision-making

Answer 53

Galotti (2002):
* considered real-life decision-making
* theory based on naturalistic studies where ppts are making real-life decisions

5 phases of the decision-making process:
1.) setting goals
2.) gathering information
3.) structuring the decision (options + criteria / attributes)
4.) making a decision
5.) evaluating the decision
.
* phases are flexible: may return to prev stages if struggling to make a decision
* info considered is limited (no. of options and attributes)

Question 54

Method, Findings (6), Conclusions

Naturalistic Decision-making:
Galotti (2007):

Answer 54

• discussed 5 studies on students choosing their college & main subject
  Findings:
  1.) constrained amount of info they considered (focused on 2-5 options at any given time)
  2.) no. of options considered decreased over time
  3.) no. of attributes at any given time considered was between 3-9
  4.) no. of attributes did not decrease over time (sometimes it increased)
  5.) individuals of higher ability and/or more education considered more attributes
  6.) most real-life decisions were assessed as good

Conclusions:
1.) ppts limited amount of info (options & attributes):
* consistent with Simon’s (1957) Bounded Rationality
* inconsistent with Multi-attribute Utility Theory

2.) no. of options considered decreased over time
* consistent with Tversky’s (1972) Elimation-by-aspects Theory