Cognition 7e, Margaret MatlinChapter 12 Cognition Deductive Reasoning and Decision Making Chapter...

Cognition 7e, Margaret Matlin Chapter 12

CognitionCognition

Deductive Reasoning and Deductive Reasoning and Decision MakingDecision Making

Chapter 12Chapter 12


IntroductionIntroduction

Thinking

deductive reasoning—given some specific premises, decide whether those premises allow you to draw a particular conclusions, based on the principles of logic

decision making—assessing and choosing among several alternatives


Deductive ReasoningDeductive Reasoning

conditional reasoning (propositional reasoning)—tell us about the relationship between conditions; "if . . . then . . ."; judged as valid or invalid

syllogism—two statements that we must assume to be true, plus a conclusion; "all, none, some . . ."; judged as valid, invalid, or indeterminate



An Overview of Conditional ReasoningAn Overview of Conditional Reasoningthe propositional calculusantecedentconsequent



An Overview of Conditional ReasoningAn Overview of Conditional ReasoningFour conditional reasoning situations (Table 12.1)

1. Affirming the antecedent means that you say the “if…” part of the sentence is true. This kind of reasoning leads to a valid, or correct, conclusion.

2. The fallacy (or error) of affirming the consequent means that you say the “then…” part of the sentence is true. This kind of reasoning leads to an invalid conclusion.



An Overview of Conditional ReasoningAn Overview of Conditional ReasoningFour conditional reasoning situations (Table 12.1)

3. The fallacy of denying the antecedent means that you say the “if…” part of the sentence is false. Denying the antecedent also leads to an invalid conclusion.

4. Denying the consequent means that you say the “then…” part of the sentence is false. This kind of reasoning leads to a correct conclusion.


The Propositional The Propositional CalculusCalculus



An Overview of Conditional ReasoningAn Overview of Conditional ReasoningJonathan Evans's heuristic-analytic theory



Difficulties with Negative InformationDifficulties with Negative Information• people take longer to evaluate problems that

contain negative information• people more likely to make errors on these

problems• working memory strain



Difficulties with Abstract Reasoning Difficulties with Abstract Reasoning ProblemsProblems

people are more accurate when they solve reasoning problems that use concrete examples rather than abstract, theoretical examples



The Belief-Bias EffectThe Belief-Bias Effectrole of background knowledgebelief-bias effect—when people make judgments

based on prior beliefs and general knowledge, rather than on the rules of logic

people tend to make errors when the logic of a reasoning problem conflicts with their background knowledge (i.e., with what they “know” is correct)

e.g., “don’t confuse me with the facts”



How do we know when we are wrong?How do we know when we are wrong?

What does it feel like?What does it feel like?

• Kathryn Schulz: On being wronghttp://www.ted.com/talks/kathryn_schulz_on_being_wrong.html

http://www.ted.com/talks/kathryn_schulz_on_being_wrong.html

http://www.ted.com/talks/kathryn_schulz_on_being_wrong.html



The Confirmation BiasThe Confirmation BiasThe Standard Wason Selection Task

confirmation bias—people would rather try to confirm a hypothesis than try to disprove it

Variations on the Wason Selection Tasksubtle wording changesclear, detailed instructions in conditional

reasoning strategiesreal-world situations



Confirmation BiasConfirmation BiasVariations on the Wason Selection Task (continued)

Griggs and Cox (1982)—drinking age example

If a person drinks an alcoholic drink, then they must be over the age of 21 years old.


Decision MakingDecision Making

no established rulesno "correct" decision

heuristicsKahneman and Tversky

• proposed that a small number of heuristics guide human decision making

• the same strategies that normally guide us toward the correct decision may sometimes lead us astray



The Representativeness HeuristicThe Representativeness Heuristicrespresentativeness heuristic—we judge that a

sample is likely if it is similar to the population from which it was selected

we believe that random-looking outcomes are more likely than orderly outcomes

this heuristic is so persuasive that we often ignore important statistical information that we should consider


The Representativeness The Representativeness HeuristicHeuristic

Sample Size and RepresentativenessSample Size and Representativeness• a large sample is statistically more likely to reflect

the true proportions in a population than a small sample

• small-sample fallacy



Base Rate and RepresentativenessBase Rate and Representativenessbase rate—how often an item occurs in the populationbase-rate fallacy—emphasize representativeness

and underemphasize important information about base rates



Base Rate and RepresentativenessBase Rate and RepresentativenessKahneman and Tversky—engineers and lawyers

studyBayes' theorem—judgments should be influenced by

two factors: the base rate and the likelihood ratiolikelihood ratio—whether the description is more

likely to apply to Population A or Population B



Representativeness and the Conjunction Representativeness and the Conjunction FallacyFallacy

Tversky and Kahneman—"Linda", bank teller, feminist problem



Representativeness and the Conjunction Representativeness and the Conjunction FallacyFallacy

conjunction rule—the probability of the conjunction of two events cannot be larger than the probability of either of its constituent events

conjunction fallacy—people judge the probability of the conjunction of two events to be greater than the probability of a constituent event

*** judge representativeness instead of statistical probability


Conjunction FallacyConjunction Fallacy

Figure 12.1 The Influence of Type of Statement and Level of Statistical Sophistication on Likelihood Rankings. Low numbers on the ranking indicate that people think the event is more likely an incorrect decision.



The Availability HeuristicThe Availability Heuristicavailability heuristic—estimate frequency or

probability in terms of how easy it is to think of relevant examplestrue frequency "contaminated" by recency and

familiarity


Availability HeuristicAvailability Heuristic


The Availability HeuristicThe Availability Heuristic

Recency and AvailabilityRecency and Availabilityjudge recent items to be more likely than they really

are

MacLeod and Campbell (1992)• when people were encouraged to recall pleasant events

from their past, they later judge pleasant events to be more likely in their future

• when people were encouraged to recall unpleasant events, they later judged unpleasant events to be more likely



Familiarity and AvailabilityFamiliarity and Availabilityjudge more familiar examples to be more likelydivorce ratesdiseasesmedia

violent eventspopulation estimatespoints of view

Tversky and Kahneman (1973)—famous and less famous names study



Illusory Correlation and AvailabilityIllusory Correlation and Availabilityillusory correlation—people believe that two

variables are statistically related, even though there is no real evidence for this relationship

StereotypesExample: People on unemployment are lazy

social cognition approach—stereotypes are the result of normal cognitive processes; motivational factors are less relevant


Illusory CorrelationIllusory Correlation



Additional examplesAdditional examples• A friend says that cigarette smoking is not unhealthy

because his grandfather smoked three packs of cigarettes a day and lived to be 100.

• Someone at a party says that drivers of red cars get more speeding tickets. The group agrees with the statement because a member of the group, "Jim," drives a red car and frequently gets speeding tickets.

• All Americans/Germans/Women/Men/Teenagers …



The Anchoring and Adjustment HeuristicThe Anchoring and Adjustment Heuristic• when making an estimate, we begin with a first

approximation (anchor) and then we make adjustments to that number on the basis of additional information

• people rely too heavily on the anchor and their adjustments are too small

Remembering Algorithms vs Remembering Algorithms vs Experts - Stereotypes and Experts - Stereotypes and

Problem-SolvingProblem-Solving

Experts use Schemas built from their experience

They evaluate about 6 pieces of information out of a much larger set of data.


The process is subject to:• Confirmation Bias• Representativeness • Availability• Anchoring and Adjustment


The Anchoring and The Anchoring and Adjustment HeuristicAdjustment Heuristic

Research on the Anchoring and Research on the Anchoring and Adjustment HeuristicAdjustment Heuristic

Multiplication study (p. 420)• if the first number was large, the estimates were higher

than if the first number was small• single-digit numbers anchored the estimates far too low

anchor may restrict the search for relevant information in memory



Applications of the Anchoring and Applications of the Anchoring and Adjustment HeuristicAdjustment Heuristic

making judgments about other peoplestereotypes and judging individualscourtroom sentences



Estimating Confidence IntervalsEstimating Confidence Intervalsconfidence interval—range within which we expect a

number to fall a certain percentage of the time• estimated confidence intervals tend to be too

narrow• anchor may be erroneous and adjustments too

small• people don't really understand confidence intervals• confidence intervals vs. estimated certainty



The Framing EffectThe Framing Effectframing effect—the outcome of a decision

can be influenced by: (1) the background context of the choice and (2) the way in which a question is worded

Huber and colleagues (1987)—"Is the pitcher half empty, or is the pitcher half full?”


The Framing EffectThe Framing Effect

Background Information and the Framing Background Information and the Framing EffectEffect

Kahneman and Tversky (1984)—lost ticket/lost $20 study



Question Wording and the Framing EffectQuestion Wording and the Framing Effectpeople distracted by surface structure of the

questionsTversky and Kahneman (1981)—"lives saved"/"lives

lost" study"lives saved" question led to more "risk averse" choices"lives lost" question led to more "risk taking" choices

prospect theory1. When dealing with possible gains (for example,

lives saved), people tend to avoid risks.2. When dealing with possible losses (for

example, lives lost), people tend to seek risks.



Consumer behaviorConsumer behavior Would this sign affect your decision to purchase a sweet soda?

“Contains 250 Calories”



Consumer behaviorConsumer behavior How about this sign?

“Will take 60 minutes of rigorous exercise to

burn off.”



In Depth: Overconfidence in DecisionsIn Depth: Overconfidence in Decisionsoverconfidence—confidence judgments are higher

than they should be, based on actual performance

illusory correlationanchoring and adjustment



In Depth: Overconfidence in DecisionsIn Depth: Overconfidence in DecisionsGeneral Studies on Overconfidence

occurs in a variety of situationsown decisions vs. statistically observable

measurementsfuture performancevariety of personal skills



In Depth: Overconfidence in DecisionsIn Depth: Overconfidence in DecisionsOverconfidence in Political Decision Making

war decisionsfailure to think systematically about the risks involvedeach side tends to overestimate its own chances of

successpoliticians overconfident that their data are accurateTactical Decision Making Under Stresscrystal-ball technique



In Depth: Overconfidence in DecisionsIn Depth: Overconfidence in DecisionsStudents' Overconfidence About Completing Projects on Time

planning fallacy—underestimate amount of time (or money) required to complete a project; also estimate the task will be relatively easy to complete

Shelley Taylor and colleagues (1998)student project studyprocess simulation vs. control

optimistic scenarioanchoring and adjustment



In Depth: Overconfidence in DecisionsIn Depth: Overconfidence in DecisionsReasons for Overconfidence

1. People are often unaware that their knowledge is based on very tenuous and uncertain assumptions and on information from unreliable or inappropriate sources.

2. Examples confirming our hypotheses are readily available, whereas we resist searching for counterexamples




3. People have difficulty recalling the other possible hypotheses, and decision making depends on memory. If you cannot recall the competing hypotheses, you will be overly confident about the hypothesis you have endorsed.

4. Even if people manage to recall the other possible hypotheses, they do not treat them seriously.




5. When people make decisions as a group, they sometimes engage in groupthink. Groupthink can occur when a cohesive group is so concerned about reaching a unanimous decision that they ignore potential problems, and they are overconfident that their decision will have a favorable outcome.



In Depth: Overconfidence in DecisionsIn Depth: Overconfidence in Decisionsmy-side bias—overconfidence that one's own view is correct in a confrontational situation; often results in conflict



The Hindsight BiasThe Hindsight Biashindsight—judgments about events that

already happened in the past

hindsight bias—judging an event as inevitable, after the event has already happened; overconfidence that we could have predicted the outcome in advance



The Hindsight BiasThe Hindsight BiasResearch About the Hindsight Bias

Carli (1999)—judgments about people; Barbara/Jack study

• happy vs. tragic ending• both groups confident that they could have predicted

ending• memory errors consistent with outcome

• "blame the victim”



The Hindsight BiasThe Hindsight BiasExplanations for the Hindsight Bias

anchoring and adjustmentmisremembering past events



Individual Differences: Decision-Making Individual Differences: Decision-Making Style and Psychological Well-BeingStyle and Psychological Well-Being

Maximizers—tend to examine as many options as possible (maximizing decision-making style)

Satisficers—tend to settle for something that is satisfactory (satisficing decision-making style)



Individual Differences: Decision-Making Individual Differences: Decision-Making Style and Psychological Well-BeingStyle and Psychological Well-Being

Schwartz and coauthors (2002)maximizer/satisficer scale and several other measuresmaximizers tended to experience more regret

following a choicemaximizers tended to experience more depressive

symptomsmore choices don't necessarily make a person

happier



Current Perspectives on Decision MakingCurrent Perspectives on Decision MakingGirgerenzer and colleagues

people are not perfectly rational decision makers, but people can do relatively well when they are given a fair chance

default heuristic—if there is a default option, people will choose ite.g., organ donor



Current Perspectives on Decision MakingCurrent Perspectives on Decision MakingKahneman and colleagues

attribute substitution—when asked to make a judgment, but you don't know the answer, substitute an answer to a similar but easier questione.g., relationship breakup during deployment



Current Perspectives on Decision MakingCurrent Perspectives on Decision MakingBoth approaches suggest that decision-making heuristics generally serve us well in the real world.We can become more effective decision makers by realizing the limitations of these important strategies.



Living with DecisionsLiving with Decisions• Kathryn Schulz: Don't regret regret

http://www.ted.com/talks/kathryn_schulz_don_t_regret_regret.html

• Sheena Iyengar: The art of choosinghttp://www.ted.com/talks/

sheena_iyengar_on_the_art_of_choosing.html



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