Introduction to Reasoning Psychology 355: Cognitive Psychology Instructor: John Miyamoto 06/01 /2015: Lecture 10-1 This Powerpoint presentation may contain

Introduction to Reasoning

Psychology 355: Cognitive Psychology

Instructor: John Miyamoto

06/01/2015: Lecture 10-1

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Outline

• Deductive & inductive reasoning:

• The heuristics & biases research program

• The availability heuristic – What is it?♦ Examples of probability judgment based on the availability heuristic.

• The representativeness heuristic – What is it?♦ Examples of judgments based on the representativeness heuristic.

Psych 355, Miyamoto, Spr '15 2Definition - Deductive Reasoning

3Psych 355, Miyamoto, Spr '15

Deductive Reasoning

Deductive reasoning is reasoning ....

FROM: Premises that are assumed to be true

TO: Conclusions that are certain to be true

if the premises are true.

Examples of deductive reasoning:o Math problem solvingo Logic problemso Four Card Problem

Definition of Inductive Reasoning


Inductive Reasoning

Inductive reasoning is reasoning ....

FROM: Evidence

TO: Strength of belief with respect to one or more

conclusions (judged likelihood that a conclusion

is true)

Examples of inductive reasoning: o How likely is it that it will rain tomorrow in Seattle?o How likely is it that the defendant in a criminal trial is guilty? o What do the results of an experiment imply about a hypothesis

that is tested in the experiment?o Economic forecasts: How likely is a recession in Europe during 2015/2016?

Why Psychologists Are Interested in Inductive Reasoning


Why Psychologists Are Interested in Inductive Reasoning

• Most real-world questions involve uncertainties.

How do people make decisions when faced with risk and uncertainty?

• Rational decision model: Expected utility theory o Bayesian decision theoryo Central assumption of economic theory & business decision making:

Rational decision makers obey the Bayesian decision theory.

----------------------------------

• Heuristics & biases research:

Cognitive critique of the rational agent model.

• Modern behavioral economics

• General issue of how humans acquire knowledge from uncertain

information.Risk and Judgments of Likelihood

Risk & Judgments of Likelihood

• How do people make decisions when faced with risk and uncertainty?♦ Example: Deciding whether to buy a house.

Deciding which house to buy among the available choices.

♦ Example: Deciding what medical treatment is best for a given patient (maybe yourself; maybe for someone else).

• How do people judge the likelihood of events?♦ Example: How likely is it that North Korea will sell nuclear technology

to terrorists?

♦ Example: How likely is it that you will find a good job if you pursue a career in X, e.g., marketing?

• How do people judge how much they like or dislike particular possibilities? How do people predict their future preferences?

Psych 355, Miyamoto, Spr '15 6Rational Decision Model & JDM

Rational Decision Model & JDM

• Rational decision model: Expected utility theory ♦ Bayesian decision theory

♦ Central assumption of economic theory & business decision making: Rational decision makers obey the Bayesian decision theory.

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• Judgment & Decision Making (JDM) – a branch of cognitive psychology; generally critical of the rational decision model

♦ Human cognitive processes lead to counterproductive (suboptimal)judgments and decisions

• Heuristics & biases research: Cognitive critique of the rational agent model.

♦ Heuristics & biases research program is a major part of JDM research.

Psych 355, Miyamoto, Spr '15 7Definition - Heuristic Reasoning Strategies


Heuristic Reasoning Strategies

Heuristic reasoning strategies – reasoning strategies that are useful

because they are easy and generally effective, even though they can

sometimes lead to errors.

Main Claims of the Heuristics & Biases Movement


Main Claims of the Heuristics & Biases (H&B) Movement

• Human cognitive processes do not follow the pattern

of a rational model. o (Rational model = expected utility theory & Bayesian decision model)

• Human decision making uses heuristic strategies

that are useful, but they can lead to systematic errors.

• Heuristic reasoning strategies ....o .... are often fast and effective, o .... place low demands on cognitive resources.o .... but they can lead to errors in particular situations.

• Behavioral economics – the application of cognitive psychology

to the analysis of economic behavior.

Heuristic Reasoning Strategies - Definition


Some Heuristics in Inductive Reasoning

• Availability

• Representativeness

• Anchoring & Adjustment

• Confirmation bias

• Focusing illusion

• Framing effects

• Mental accounting

• More heuristics that have been proposed than are listed here.

Availability Heuristic



• Availability heuristic – events are judged more probable

if similar events are easy to recall or easy to imagine. o In general, frequently encountered events are easier to recall. o The availability heuristic exploits the converse of this relationship:

Events that are easy to recall are thought to be frequent in occurrence. o Availability heuristic causes biased probability judgments when other factors

that influence availability are not taken into account.

Frequency of Experience

Other Factors

Availabilityof Memoryfor an Event

Learning


Judged Frequency

of Experience

Judgment

Same Slide Without Emphasis Rectangles



Availability: Lists of Famous & Non-Famous Names


Other Factors


Learning


Judged Frequency

of Experience

Judgment

• Availability heuristic – events are judged more probable if similar events are easy to recall or easy to imagine. o In general, frequently encountered events are easier to recall. o The availability heuristic exploits the converse of this relationship:

Events that are easy to recall are thought to be frequent in occurrence. o Availability heuristic causes biased probability judgments when other factors

that influence availability are not taken into account.

13

Availability Bias Due to Ease of Encoding Famous/Non-Famous Names x Male/Female

• Subjects saw a list of names, one at a time, that mixed famous males with non-famous females, or vice versa. There were 18 famous and 19 non-famous names in the list.

Psych 355, Miyamoto, Spr '15

Condition I:Famous Male

Non-Famous Female

Bill ClintonTom Hanks

Michael Jordan........

Mary BrooksAndrea ForbusLeanne Faris

.......

Condition II:Famous Female

Non-Famous Male

William HaleMurray JencksLionel Worley

........

Michelle ObamaAngelina Jolie

Sarah Palin........

Next: Same Slide with No Barriers & Results

14

Results: Famous/Non-Famous Names x Male/Female

Results:

• Subjects reported more males if the males were famous;

• Subjects reported more females if the females were famous.

• Availability influences perceived frequency.


Condition I:Famous Male

Non-Famous Female

Bill ClintonTom Hanks

Michael Jordan........

Mary BrooksAndrea ForbusLeanne Faris

.......

Condition II:Famous Female

Non-Famous Male

William HaleMurray JencksLionel Worley

........

Michelle ObamaAngelina Jolie

Sarah Palin........

Reminder of Link to Memory Model



“Other Factors” that influence availability of a memory

• Famous names are easy to encode and easy to retrieve.

• Non-famous names are harder to encode and harder to retrieve.


Other Factors


Learning


Judged Frequency

of Experience

Judgment

Studies of Solo Status

16

Egocentric Bias (Example of Availability Heuristic)

• Egocentric bias: People overestimate the proportion of the total work

that they have contributed to a project.

• Ross & Sicoly (1979): Subjects were 37 married couples.

• Working separately, husband and wife rated self and spouse for their work on 20 activities: making breakfast; cleaning dishes; cleaning house; making important

decisions; ... ; causing arguments between themselves; making the house messy; irritating spouse .

primarily primarilyhusband wife

Psych 355, Miyamoto, Spr '15 Predicted Response Pattern If No Bias Existed

17

Rating Procedure in Egocentric Bias Study

• Husband and wife rated self and spouse for their work on 20 activities


• Subjects rated their responsibility on a line as shown above.♦ Husband's rating measured as distance from the right end;

wife's ratings measured as distance from the left end.

♦ If husband and wife have accurate perceptions of responsibility, the sum of their ratings should equal the length of the line.

Psych 355, Miyamoto, Spr '15 Predicted Response Pattern If No Bias Existed

Wife's Mark Husband's Mark

Husband's RatingWife's Rating

18

Example: Suppose that Husband & Wife's Ratings Are Consistent With Each Other

• Husband and wife agree as to contribution of each to a task like washing dishes:


• If husband and wife were not egocentric, the couple's ratings would sum to +100.


▐ + 25 in husband's scoring▐ + 75 in wife's scoring _________________________

+100 total of husband & wife

Predicted Response Pattern If Egocentric Bias Exists

19

Example: Suppose that Husband & Wife's Ratings Are Inconsistent With Each Other

• Husband and wife disagree about their contributions to washing dishes.


• If husband and wife are egocentric, the couple's ratings would sum to more than 100.


▐ + 48 in husband's scoring▐ + 75 in wife's scoring _________________________

+123 total of husband & wife

Results for Egocentric Bias Study

20

Results for Egocentric Bias Study

• The inconsistent pattern is typical: On many activities, ....

• Ratings consistently summed to number greater than +100 across many activities, showing an excessive attribution of credit or blame to the self.

• The result holds for both good things (wash the dishes) and bad things (buy unnecessary things).


Husband’s Rating + Wife’s Rating > 100

Conclusion re Egocentric Bias – Relation to Availability


Conclusion re Egocentric Bias

• Egocentric bias is probably due to the greater availability of self-

actions than partner actions

Other Examples: o Self versus supervisor focus in attributing responsibility for BA thesis work. o Basketball players attributing responsibility for win or loss. o People generally overestimate the frequency of dramatic, newsworthy events

relative to the frequency of mundane but serious diseases or accidents.

Sampling Bias in Everyday Media


Sampling Bias in Everyday Media

Things we all know:o TV ads do not give an accurate picture of the value of products.o Political spin doctors are trying to manipulate our beliefs.o TV news is emphasizes dramatic events; it ignores undramatic events.o The portrayal of men/women, black/whites, rich/poor, gay/straight,

on TV is not a representative presentation of these groups.o Our own experiences are not typical of everybody’s experience.o Etc.

• We all know that these information sources are biased, but can

we really correct for these biases when forming beliefs? Doubtful.

Return to the Diagram of the Availability Heuristic & List of “Other Factors”

{Biases∈¿ InformationSources } { Biases∈¿ Availability } {Biases∈¿ Perceived Likelihood

of Events }

Psych 355, Miyamoto, Spr '15 23

Monday, June 01, 2015: The Lecture Ended Here


“Other Factors” that Influence the Availability of Events

Examples of

“Other Factors”

• Egocentric bias.

• Dramatic events seem more common than non-dramatic events.

• Biases in the media create biases in the availability of stereotypes.

• Recent events seem more common than earlier events.

• Anything that makes events easier to encode or retrieve can make

the events seem more frequent than they are.

Summary re the Availability Heuristic

Summary re the Availability Heuristic

• Judging probability in terms of availability is a heuristic.♦ I.e., it is generally a reasonable way to estimate likelihood, but it can lead

to certain systematic errors.

• Factors that are not related to experienced frequency can makemake particular events very available.

♦ E.g., the perceived probability of being killed by a random crazy person will tend to be exaggerated.

Psych 355, Miyamoto, Spr '15 25Introduction to the Representativeness Heuristic

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Introduction to Reasoning Psychology 355: Cognitive Psychology Instructor: John Miyamoto 06/01 /2015: Lecture 10-1 This Powerpoint presentation may contain