国外社会心理学3课件3.ppt

Heuristics ShortcutsInsteadofNormativeDecisionMaking RepresentativenessHeuristic Wemakejudgmentsofprobabilitybasedonsimilarityanddonotconsiderotherrulesthatweshould Let slookattheevidence firstweignorebase rates ThenormativerulescomefromBayesTheoremwhichsoundsprettyconfusingbutbasicallysuggeststhatwhenwemakeadecisionweshouldtakepriorprobabilitiesintoaccountunlessweareabsolutelycertainaboutthedecision WhatisTomW sMajor TomW isofhighintelligence althoughlackingintruecreativity Hehasaneedfororderandclarity andforneatandtidysystemsinwhicheverydetailfindsitsappropriateplace Hiswritingisratherdullandmechanical occasionallyenlivenedbysomewhatcornypunsandflashesofimaginationofthesci fitype Hehasastrongdriveforcompetence Heseemstohavelittlefeelandlittlesympathyforotherpeopleanddoesnotenjoyinteractingwithothers Self centered henonethelesshasadeepmoralsense WhatisTomW sMajor Kahneman Tverskyasked3questionsWhatpercentageofpeopleinthedifferentmajors HowsimilarisTomW toeachmajor HowlikelyisTomW eachmajor TheyfoundestimatesofhowlikelyTomW isaparticularmajorarestronglyinfluencedbyhowsimilarheistotheirstereotypeaboutthemajor butunrelatedtothepercentageofpeopleinthedifferentmajors ThisviolatesBayesTheoremunlesstheyarecertainfromthedescriptionwhatmajorTomW iswhichtheyweren t IsJackaLawyeroranEngineer Jackisa45year oldman Heismarriedandhasfourchildren Heisgenerallyconservative careful andambitious Heshowsnointerestinpoliticalandsocialissuesandspendsmostofhisfreetimeonhismanyhobbieswhichincludehomecarpentry sailing andmathematicalpuzzles TheprobabilitythatJackisoneofthe30engineersinthesampleof100is IsDickaLawyeroranEngineer Dickisa30 year oldman Heismarriedwithnochildren Amanofhighabilityandhighmotivation hepromisestobequitesuccessfulinhisfield Heiswelllikedbyhiscolleagues TheprobabilitythatDickisoneofthe30engineersinthesampleof100is IsJack DickaLawyeroranEngineer K Tfoundthatpeople sratingsofwhetherJackwasaLawyeroranEngineerwerevirtuallyunaffectedbythebaserateinformationofwhethertherewere30 Lawyersor70 Lawyers Theyalsofoundthatpeoplepaidattentiontobase ratesiftheyweregivennoinformationaboutJackHowever Dickwasjudgedtobe50 likelytobeaLawyerregardlessofthebase rates ViolationsofLogicandtheRepresentativenessHeuristic IsJaneaBankTelleroraFeministBankTeller Lindais31yearsold single outspokenandverybright Shemajoredinphilosophy Asastudent shewasdeeplyconcernedwithissuesofdiscriminationandsocialjustice andalsoparticipatedinanti nucleardemonstrations Whichofthefollowingismoreprobable A LindaisabanktellerB Lindaisabanktellerandactiveinthefeministmovement SocialEffectsoftheRepresentativenessHeuristic ConsensusInformationandtheFundamentalAttributionError Nisbett Borgida 1975 SeizurestudyandattributionaboutatypicalstudentThosegiveninformationabouttheresultsofthisstudyignoreditTheDilutionEffectBasicEffect Nisbett etal 1981 ChildmolesterwithanIQof110 EffectofPseudo RelevantInformationandtrulyirrelevantinformation Fein Hilton 1989 Paulwhosehasasinglemother SocialEffectsoftheRepresentativenessHeuristic cont StereotypesandtheRepresentativenessheuristicLocksley sResearch peopleignorestereotypeslikebaserateswhengivenapersonaldescriptionButitisnotthatsimpleaswewillseelaterwhenwecoverstereotypesnote Representativenessinformationisoftenthestereotyperatherthanthebase rate GoalsandmotivationaffectstheseprocessesOtherresearchbyBiernatandhercolleaguescallsthisintoquestionClearbaseratesFuzzycategories QualificationsoftheOriginalFindings FocussingAttentiononChanceFactorsincreasesuseofbaseratesAskingpeopletodrawtheLawyerorEngineeroutofaBingoDrumdecreasesrelianceonrepresentativenessbyincreasingpeople suseofbaserates RulesofLanguageusemayexaggeratetheK TfindingsOrderofwhetherbase ratesandindividuatinginformationaffectspeople suseofbase rates Peopleusebase ratesmorewhenpredictingmultipleoccurrencesinthelongrun TakingaSingleInstanceasRepresentative ImplicationsforStatisticalReasoning NumericalPredictions Participantsreadashortdescription eitherareportorjustalistofadjectives aboutacollegefreshman K Tthenasked2questionsWhatpercentageofdescriptionsoffreshmandoyoubelievewouldimpressyoumore Whatisthepercentageoffreshmanwhowillobtainahighergradepointaverage Thenormativemodelsuggeststhatsincethesecondquestionismoreuncertainthanthefirstyoushouldpredictlesssuccessforthesecond Theresultssuggestthatpeoplemakethesamepredictionsforthesetwoquestions IgnoringStatisticalRules cont RegressiontotheMeanScoreonanIQtestPilotsandFeedbackIgnoringSampleSizeHospitalProblemInterviewsMisconceptionsofChanceInterpretationsofrandomevents gowithredorblack Beliefinthehothand ScoreonanIQTest Aproblemoftesting Arandomlyselectedindividualhasobtainedascoreof140onastandardizedIQtest SupposethatanIQscoreisthesumofa true scoreandarandomerrorofmeasurementwhichisnormallydistributed Pleasegiveyourbestguessaboutthe95 upperandlowerconfidenceboundsforthetrueIQofthisperson Thatis giveahighestimatesuchthatyouare95 surethatthetrueIQscoreis infact lowerthanthatestimate andalowestimatesuchthatyouare95 surethatthetruescoreisinfacthigher HospitalProblem Acertaintownisservedbytwohospitals Inthelargerhospital about45babiesareborneachday andinthesmallerhospitalabout15babiesareborneachday Asyouknow about50percentofallbabiesareboys However theexactpercentagevariesfromdaytoday Sometimesitmaybehigherthan50percent sometimeslower Foraperiodof1year eachhospitalrecordedthedaysonwhichmorethan60percentofthebabiesbornwereboys Whichhospitaldoyouthinkrecordedmoresuchdays A ThelargerhospitalB ThesmallerhospitalC Aboutthesame thatis within5percentofeachother StatisticalHeuristics FactorsthatAffecttheirUse Clarityofthesamplespace somethingsaremoreclearlystatisticalproblemsthanothers sportsandability yes personality noExperiencewiththedomain Domainswherechanceisemphasizedexpertsusestatisticalheuristicsmore Whydon ttryoutsmatchactualperformancePeoplecananswerhospitalproblemifitisjustchangedslightlyandresembleshowpeoplethinkaboutfamiliesStatisticalEducation statisticaltrainingcanleadpeopletousestatisticalreasoningmoreoftenRookieoftheYearProblem AvailabilityHeuristic WemakedecisionsbasedonhoweasythingscometomindratherwhenjudginghowcommonsomethingisAretheremorewordswith k asthefirstletteror k asthethirdletter Shouldwomenbemoreconcernedaboutbeingassaultedbyastrangerorafriend Whatcausestheavailabilityheuristic Isitthenumberofobjectsthatcometomindorhoweasyitisfortheobjectstocometomind Schwarzetal 1991study Listsixortwelveexampleswhenyouwereassertive orunassertive Nowtellmehowassertiveyouare What sBehindtheAvailabilityHeuristic HowEasyorHowMany ReasonsfortheAvailabilityHeuristic IgnoringbiasesinavailablesamplesandaccessiblecognitionsFalseconsensuseffect wethinkotherpeopleagreewithusanddothethingsthatwedomorethanisjustifiedTheeffectofmediacoverageOne s