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Complete Study Guide for Final

by: Mariana de la Maza

Complete Study Guide for Final PSYC2014

Marketplace > George Washington University > Psychlogy > PSYC2014 > Complete Study Guide for Final
Mariana de la Maza
GPA 3.8
Cognitive Psychology
James Higgins

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About this Document

This is a thorough, comprehensive study guide for Cognitive Psychology Final. This study guide covers lectures as well as book content from Chapters 9-13.
Cognitive Psychology
James Higgins
Study Guide
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This 20 page Study Guide was uploaded by Mariana de la Maza on Monday May 4, 2015. The Study Guide belongs to PSYC2014 at George Washington University taught by James Higgins in Winter2015. Since its upload, it has received 208 views. For similar materials see Cognitive Psychology in Psychlogy at George Washington University.


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Date Created: 05/04/15
Study Guide Cognitive Psychology Final Chapter 9 0 Concept 0 Mental glue 0 Mental representation of a class or individual 0 Meaning of objects 0 Building blocks of cognition I We organize concepts into categories 0 Examples of a particular concept 0 Process of categorization I Placing concepts in categories 0 Once me place an object in a category we know a lot about it 0 Functions of concepts 0 Classification reasoning and cognitive economy prediction understanding amp explanation building blocks for complex concepts communication 0 Definitional approach to categorization 0 The problem is not all have the same features 0 Classical View 0 All instances of a concept share common properties that are singly necessary and jointly sufficient I Must have ALL properties 0 Benefits I Efficient storage of concepts I Clear category boundaries and decisions 0 Problems I Failure to specify defining features I Typicality effects items either are or are not members I Many unclear cases I Monday March 0 Typicality Effects I Typical objects are more easily as being members of the target category I They have greater feature overlap with the summary representation of the category I The ability to judge prototypical objects more rapidly 0 Prototype 0 Summary representation including all the typical properties 0 Used to represent the concept classify new instances to reason 0 Proposed by Eleanor Rosch I Like birds 0 Category prototype O Probabilistic View 0 O Unitary representation that includes features USUALLY true of instances of an object Prototype and family resemblance I Things in a category resemble each other in a number of ways 0 Higher ratings for highprototypical items I To deal with the problem that definitions do not include all members of a category I Things in a particular category resemble one another in a number of ways 0 Allows for variation within a category I Prototype Best Example I Like extended families What determines typicality I A number of typical features Family resemblance and typicality Lacks context sensitivity I Doesn t take into account how frequently you see something in the world I Your representation of a bird might be a pigeon bc you don t live near robins example Positive I Unitary representation I Accounts for typicality Negative I Lacks context sensitivity I Not sensitive to many factors that people are sensitive to because I prototype is a unitary representation I Frequency of instances I Variability I Correlation of feature values I Predicts sensitivity to linear separability and people are not sensitive 0 Exemplar view 0 O 0 Representation consists of separate disjunctive descriptions of some of its exemplars No unitary description Explicitly disjunctive can use different representations to classify different Mini prototypes Each exemplar give you something to make judgments on what items in the world are All of these things are represent O O No unitary description more of a whole bunch of single prototypes Gives more exibility allows you to recognize colleague just as quickly as a cocker spaniel No unitary description You have a central representation then a bunch of categories where different animals that are more similar to each other are All accessed equally quickly Allows you to accomplish this in a better way I You can predict people s frequency and variability Items into the same category I I DOG collies or spaniels or Fido or Standard for this approach involves many examples I Each one is called an exemplar Exemplars I Members of he category that a person has encountered in the past I Explains the typicality effect exemplars classified more rapidly Advantage I Uses real examples so it takes into account atypical cases I Exemplars weighted by similarities I Can predict many prototypelike effects I Can predict in uences of frequency variability correlation of features I Realworld evidence physicians fires Problem I what about abstractions 0 Theories beyond similarities O O O O Similarities not enough Sometimes you need additionally explanatory power than images and similarities such as features Theory View 0 Theory View forces you to take a bunch of propositions but now you can add in functions beyond observable features 0 Ex Mutilated poodles 0 Know a theory for something test that theory 0 Heuristic guess 0 Things have different features 0 Not anything is what we see in the surface I Concepts organized by theories I NEED TO TAKE INTO ACCOUNT KNOWLEDGE I To decide if something is a member ask if it fits rather than look at features I If similarity and knowledge con ict go with knowledge Strengths O I Explains why items that seem dissimilar in feature may overlap in same category Weaknesses I Under specified Hierarchical organization 0 O O 0 Ross Quillian Larger more general categories are divided into smaller more specific levels of categories Rosh Experiment Superordinate level global and subordinate level specific 0 Basic level I Re ects everyday experiences I In order to categorize objects we need to understand the learning and experience of the people perceiving those objects Between category structure 0 0 Levels with setinclusion I Treemaple treesugar maple tree I Furniturechairrocking chair Property inheritance I Properties of higher levels inherited at lower levels more general in the top more specific at bottom I Properties of tree true of maple tree Semantic network approach 000000 How categories and concepts are organized in the mind Semantic network approach Proposes concepts are arranged in networks Computer model of human memory Nodes connected by links each node is a concept This is a hierarchical model because it consists of levels arranged into specificity Basic Level O 0000 Rosch Rosch compromise between maximizing information and minimizing effort informativeness and laziness Highest level at which entities share parts Chair apple Superordinate furniture Subordinate delicious red apple It is the first to be acquired by children Principles in naming Informativeness I Want as much useful information as possible better for prediction explanation I So lower level is better more specific 0 Laziness I Want as little effort as possible 0 Higher level is better 0 Therefore basic level is the best compromise I Proposes that going above basic we lose information and going below we gain too little information 0 Differentiation Hypothesis 0 2 principles I Specificity 0 Maximize information I Distinctiveness 0 Do not want it confused with like contrast categories 0 Basic level is usually the most distinctive I There are atypical subordinates where the most distinctive is not the basic penguin racing car 0 Implications O Basicness is not a property of entire level 0 Types of conceptual organization 0 Taxonomic 0 Thematic 0 Ad hoc satisfy some goal I We do deficitbased studies to study categories and their representations in the brain 0 Look at people with category deficits and relate areas damaged to type of deficit 0 Temporal lobe damage I Deficits in knowledge about biological categories but not about artifacts I Difficulty naming pictures or matching names and pictures 0 Parietal damage I Deficits in knowledge about artifact but not about biological 0 Different types of categories store in different types of the brain 0 Rely on different types of information 0 Biological visual features 0 Artifacts functional features I Not really categorydeficit Chapter 10 0 Mental imagery the ability to recreate the sensory world in the absence of physical stimuli or sensory input Visual imagery seeing in the absence of visual stimulus Useful because it provides a way of thinking that adds another dimension to verbal techniques Early ideas about imagery 0 Imageless thought debate I Proposed by Wundt I Said images were one of 3 basic levels of consciousness I Said studying images was a way of studying thinking I Debate as to whether thinking without images could exist Imagery and the cognitive revolution 0 Developed ways to measure behavior that could be used to infer cognitive processes Paivio 0 Linked behavior and cognition O Showed it was easier to remember concrete nouns that can be imagined than abstract nouns that cant be imagined I Due to pairedassociate learning 0 Memory for words that evoke mental image is better than those that do not 0 Conceptualpeg hypothesis Shepard and Meltzer 0 Mental chronometry 0 Inferred cognitive processes by determining the amount of time needed to carry out various cognitive tasks 0 How long it took to determine whether two objects were the same or different 0 Mentally rotating one of the views due to the different angles they were taken at 0 Applied quantitative methods to imagery 0 Suggested imagery and perception were same thing Imagery and Perception Kosslyn 0 Mental scanning subjects create mental images and then scan them in their minds 0 Idea that there is spatial correspondence between imagery and perception O Memorize picture of object focusing on one area of he boat then they were asked if they found another area I Reasoning was to see if imagery was spatial because if so then scanning across the image of the object 0 In image move from one part of the picture to another I Takes longer for participants to mentally move long distances I Like perception imagery is spatial Glen Lea 0 Proposed that as subjects scanned they may have encountered other interesting parts such as the cabin and this distraction may have increased reaction time I Kosslyn island with 7 locations 0 Took longer to scan between greater distances 0 Visual imagery is spatial I Representations of locations in space Is Imagery spatial or propositional 0 Spatial representation Kosslyn 0 Epiphenomenon 0 Something that accompanies real mechanism but is not actually part of it 0 Zenon Pylyshyn O Caused imagery debate 0 Imagery is propositional I Can be represented by abstract symbols 0 He says mental images indicate something is happening but not how 0 Propositional representation I Relationships represented by abstract symbols such as an equation 0 Depictive representation I Representations that are realistic of an object so part of representation correspond to part of the object O Said Kosslyn s results can be explained by using realworld knowledge unconsciously I Tacitknowledge explanation I Make their judgment based on unconscious use of knowledge about the world 0 Finke and Pinker 0 To counter the tacitknowledge explanation 0 Four dots on display whether the arrow was pointing to any of the dots they had just seen I Couldn t have used tacit knowledge 0 Longer reaction time when greater distance between arrow and dot as if they were mentally traveling 0 Not instructed to use visual imagery O No time to memorize no tacit knowledge 0 Kosslyn Relationship between viewing distance and ability to perceive details 0 When imagining moving closer to an object subjects who imagined a rabbit that filled their visual field responded quicker O Quicker to details on the larger object 0 Mental walk task I Move closr to small animals than to large animals I Images are spatial like perception 0 Perky O 0 Interaction between perception and imagery Asked his subjects to project visual images of uncommon subjects on screen and describe images 0 Farah s letter visualization experiment 0 O H or T The subject was more likely to guess correctly when thinking of the same letter that was ashed 0 Imagery neurons respond to both perceiving and imagining an object O O O Overlap in brain activation Visual cortex Based on physiological experiments 0 Kreiman and coworkers 0 O Studied patients with electrodes implanted in various areas in their medial temporal lobe in order to determine the source of epileptic seizures that could not be controlled by medication Found neurons responded to some but not others baseball and face Imagery neurons I Neurons worked differently when subject imagined a baseball Demonstrates a possible physiological mechanism for imagery because they responded differently when seeing and imagining 0 Le Bihan et al 0 Brain imaging demonstrated both perception and imagery activate visual cortex 0 Overlap in brain activation 0 Activity increases to presentation of a visual stimulus and increases when subjects imagining 0 Kosslyn 0 Larger images in front of brain and smaller in back 0 Ganis and coworkers 0 Complete overlap of activation by perception and imagery in front of the brain 0 Used fMRI to measure activation under perception and imagery 0 Only some differences near the back of the brain 0 Amir Amedi and coworkers 0 Showed overlap between imagery and perception 0 But also found that when subjects were imagining images some areas associated with nonvisual stimuli were deactivated hearing and touch 0 Deactivation of nonvisual areas of brain I Hearing touch 0 Mental images are more fragile less activation keeps other things from interfering 0 Brain activation in response to imagery O 0 May indicate something is happening May no cause imagery Transcranial Magnetic Stimulation TMS O Decreases brain functioning in a particular area of the brain for a short time 0 If behavior is disrupted the deactivated part of the brain is causing that behavior 0 Pylyshyn says that just because brain activity in response to imagery may indicate that something is happening might not have anything to do with imagery Kosslyn 0 Presented transcranial magnetic stimulation to subjects while they were carrying a task 0 Response time slower for both 0 Brain activity in visual area of brain plays a causal role for both perception and imagery O Concluded brain activation in response to imagery is not an epiphenomenon MGS patient 0 Did the mental walk task before and after having her occipital lobe removed 0 After the size of visual field was reduced and she could mentally approach only to within 35 feet of the horse before it over owed in her visual field Unilateral neglect O Damage to parietal lobes 0 Patient ignores objects in one half of visual field in perception and imagery 0 Eating food on one side of plat Guariglia 0 Patient whose brain damage has little effect on his ability to perceive but caused neglect in his mental images 0 Braindamaged person 0 Perceptions intact mental images impaired O Suffered damage to occipital and parietal lobes 0 Could draw accurate pictures in front of him 0 Could not draw accurate pictures of objects from memory imagery O Suffered from visual agnosia the inability to visually reorganized objects 0 Inability to name pictures of objects even his own drawings in front of him Inability to visually recognize objects 0 Could draw objects in great detail from memory using imagery I Unable to identify them afterwards 0 Evidence for double disassociation between imagery and perception O Indicated separate mechanisms 0 Also evidence for shared mechanisms 0 Behramm O Mechanisms overlap partially 0 Visual perception involves bottomup processing located at lower and higher visual centers 0 Imagery is a topdown process located at higher visual centers 0 Explains CK and RM but not MGS 0 Differences in experience 0 Perception is automatic and stable 0 Imagery takes effort and is fragile I Chalmers and Reisberg 0 Had participants create mental images of ambiguous figures 0 Difficult to ip from one perception to another while holding a mental image of it I Placing images at locations 0 Method of loci I Visualizing items to be remembered in different locations in a mental image of a spatial layout I Associating images with words 0 Pegword technique I Associate items to be remembered with concrete words I Pair each of these things with a pegword I Create a vivid image of things to be remembered with the object represented in the word Chapter 10 Language I Language system of communication using sounds or symbols 0 Express feelings thoughts ideas and experiences I Makes it possible to create new and unique sentences because it has a structure that is hierarchical and governed by rules 0 Hierarchical I Components that can be combined to form larger units 0 Governed by rules I Specific ways components can be arranged I The universality of language 0 Deaf children invent sign language that is all their own 0 All humans with normal capacities develop a language and learn to follow its complex rules 0 BF Skinner O Verbal behavior I Proposed that language is learned through reinforcement O Naom Chomsky I Syntactic Structures I Language is coded in the genes I Underlying basis of all language is similar I Children produce sentences they have never heard being reinforced I Criticized behaviorism Psycholinguistics 0 Discover psychological process by which humans acquire and process language 0 Comprehension 0 Speech production 0 Representation 0 Acquisition Lexicon where our knowledge of words is stored all words a person understands Phonemes shortest segment of speech that if changed changes the meaning odf the word 0 Sounds 0 Consonant or vowel of a language I The smallest unit of sound that affects the meaning of speech Morphemes smallest units of language that has meaning or grammatical function 0 Includes prefixes and suffixes O The word unbreakable has three morphemes un break able Phonemes and Morphemes are building blocks of words Phonemic restoration effect 0 Fill in missing phonemes based on context of sentence and portion of word represented O the filling in process was based on the context produced by the sentence and the word containing the phoneme topdown processing Percieving and understanding words 0 Speech segmentation I Ability to perceive words even though they are often no pauses between words in the sound signal I Context I Understanding of meaning I Understanding of sound and syntactic rules I Statistical learning Context also plays a role in perceiving written letters 0 Word superiority effect I Finding that letters are easier to recognize when they are contained in a word than when they appear alone or in a nonword I Reicher Lexicons words they know the meaning of O Lexical decision task I Read a list of words and nonwords silently I Say yes when you read a word 0 Word frequency effect I Respond more rapidly to highfrequency words 0 Eye movements while reading I Look at lowfrequency words longer 0 Lexical ambiguity 0 Words have more than one meaning 0 Context clears up ambiguity after all meanings of a word have been brie y accessed 0 Meaning dominance O The fact that some meanings of words occur at a higher frequency than others 0 Biased dominance I When words have two or more meanings with different dominance O Balanced dominance I When words have two or more meanings with about the same dominance I When a word has balanced dominance it activates both meanings and takes longer slow access I When a word is liked more than the other fast access 0 Components of language are not processed in isolation 0 Semantics 0 Meaning of words and sentences meaning 0 Syntax 0 Rules for combining words into sentences grammar 0 Eventrelated potential and brain imaging studies have shown syntax and semantics are associated with different mechanisms 0 Parsing 0 Mental grouping of words into sentence and phrases 0 Broca and Wernicke temporal lobe Wernicke area in charge of language comprehension Broca area frontal lobe in charge of language production 0 Eventrelated potential ERP 0 Electrical response recorded with small disc electrodes placed on a person s scalp 0 Measure the number of items placed in a working memory now used for language I Gardenpath sentences 0 Sentences that begin by appearing to mean one thing but hen end up meaning something else 0 Demonstrate Temporary ambiguity I When the initial words are ambiguous but the meaning is made clear by the end of the sentence I Syntaxfirst approach to parsing 0 State that as people read sentences their grouping of words into phrases is governed by a set of rules that ae based on syntax O Grammatical structure of sentence determines parsing 0 Late closure parser assumes new word is part of current phrase O Gardenpath model Interactionist approach to parsing O Semantics and syntax both in uence processing as one reads a sentence Tananhaus and coworkers 0 Visual word paradigm I Determining how subjects process information as they are observing a visual scene 0 Eye movements change when information suggests revision of interpretation of sentence is necessary 0 Syntactic and semantic information used simultaneously Coherence 0 Representation of the text in one s mind so that information from one part of the text can be related to information in another part of the text Making inferences O Inference readers create information during reading not explicitly stated in the text I Anaphoric connecting objectspeople I Instrumental tools or methods I Causal events in one clause caused by events in previous sentence Situation Model mental representation of what a text is about 0 Represent events as if experiencing the situation 0 Point of view of protagonist Understanding text and stories 0 Experiments showed faster response elicited by picture describing the matched situation 0 Movement as well Physiology of stimulations 0 Approximately the same areas of the cortex are activated by actual movements and by reading related action words 0 The activation is more extensive for actual movements Producing language conversations 0 Two or more people talking together 0 Dynamic and rapid Givennew contract 0 Speaker takes these steps to guide listeners through conversation 0 Speaker constructs sentences so they include I Given information information listener already knows I New information information listener is hearing for the first time I New then becomes given information 0 Syntactic coordination 0 Using similar grammatical constructions 0 Syntactic Priming 0 Production of a specific grammatical construction by one person increases chances other person will use than construction 0 Common that you say a sentence in the same format of the previous one you heard 0 Reduces computational load in conversation 0 SapirWhorf Hypothesis 0 Language in uences thought 0 Winawer and coworkers 0 Russianspeaking and Englishspeaking discriminated between different shades of blue 0 Two cultures had differences n how participants responded to blue squares based on how they were categorized 0 Differences in the way names were assigned to color affect the ability to tell the difference between colors Chapter 12 0 Gestalt approach 0 Representing a problem in the mind 0 Restructuring changes the problem s representation I Kohler s circle problem 0 Sudden realization of problem s solution 0 Often requires restructuring the problem 0 Metcalf and Wiebe 0 Insight vs noninsight problems 0 Insight I Triangle problem chain problem 0 Noninsight algebra 0 Warmth judgements every 15 seconds 0 Insight problems solved suddenly noninsight problems solved gradually 0 Functional fixedness O Restricting use of an object to its familiar functions 0 Candle problem seeing boxes as containers inhibited using them as supports 0 Twostring problem function of pliers gets in the way of seeing them as a weight 0 Mental set 0 A preconceived notion about how to approach a problem 0 Determined by a person s past experiences with the problem or similar problems O Waterjug problem given mental set inhibited participants from using simpler solution I Newell and Simon 0 Logic theorist computer program designed to stimulate human problem solving 0 Posing of a problem and the solution 0 Problem space I Initial state I Intermediate state I Goal state 0 Givens I Initial state conditions objects information 0 Goal I Desired outcome 0 Operators I Means of transforming conditions I Actions that take the problem from one state to another 0 Obstacles I No simple direct known way from given to goal 0 The point is that the problem solver is constrained by how it is built 0 Common heuristic O Meansends analysis I Reduce differences between initial and goal states I Look for difference between where you are in problem space and where you want to be try to eliminate the difference getting rid of big differences first I You need to know which operators reduce which differences I Subgoals create intermediate states closer to goal 0 Compare current and goal state 0 If no difference then done 0 Difference Select largest difference and set it as a goal to be solved 0 Goal stack LIFO last in first out 0 Select operator to reduce difference 0 Apply operator I new current state 0 Return to step 1 0 Thinkaloud protocol 0 The importance of how a problem is stated 0 Say aloud what one is thinking 0 Shift in how one perceives elements of a problem I Mutilatedcheckerboard problem 0 Conditions different in how much information provided about the squares O Easier to solve when information is provided that points toward the correct representation of the problem The Russian marriage problem 0 Analogies I Processing of noticing connections between the couples in the story and the alternating squares on the checkerboard 0 Russian marriage problem source problem I mutilated checkerboard problem target problem 0 Analogical problem solving 0 Analogical transfer the transfer from one problem to another I Source problem to target problem Gick and Holyoak O Noticing relationship 0 Mappng correspondence between source and target 0 Applying mapping to generate solution Duncker s Radiation Problem 0 Analogies aid problemsolving O Often hints must be given to notice connection I Surface features get in the way I Structural features must be used What makes it hard iss that people focus too much on surface features 0 Specific elements of a problem Lightbulb problem 0 Radiation problem was the source problem 0 Makes surface features more similar which makes it easier 0 High surface similarities aid analogical problem solving I Surface features speci c elements of a given problem 0 Making structural features more obvious aids analogical problemsolving I Structural features the underlying principle that govern the solution to a problem Analogical encoding 0 Process by which two problems are compared and similarities between them are determined I Effective way to get participants to pay attention to structural features that aide problemsolving Analogical paradox 0 It can be difficult to apply analogies in the laboratory but people routinely use analogies in realworld settings In vivo problemsolving 0 People are observed to determine how they solve problems in the real world I Advantage naturalistic setting I Disadvantage timeconsuming cannot isolate and control vriables 0 How experts solve problems I Have more knowledge in the field skilled I Knowledge is organized differently than novices I Novice surface features expert structural features I They spend more time analyzing problem open new ways of looking at problems 0 Creativity 0 Innovative ideas novel new connections 0 Divergent thinking openended large number of potential solutions 0 Creative cognition 0 Technique to train people to think creatively I Preinventive forms ideas that precede creation of finished creative product Chapter 13 0 Decisions the process of making choices between alternatives 0 Reasoning the process of drawing conclusions 0 Inductive reasoning O Reasoning based on observation 0 Reaching conclusions from evidence 0 Used to make scientific discoveries I Hypotheses and general conclusions 0 Used in everyday life I Make a prediction about what will happen based on observation about what happened in the past 0 Heuristics O Shortcut rules of thumb that are likely to provide the correct answer to a problem but are not foolproof 0 Two or more commonly used heuristics include the availability heuristic and the representativeness heuristic 0 Availability heuristic 0 How often we expect an event to occur 0 Events more easily remembered are judged as being more probable that those less easily remembered I Illusory correlations correlation appears to exist but either does not exist or is much weaker than assumed 0 These expectations might take the form of stereotypes O Stereotypes oversimplified generalizations about a group or class of people that often focuses on the negative 0 Representativeness heuristic the probability that class A is a member of class B can be determined by how well the properties in class A resemble properties normally associated with class B O Idea that people make judgments based on how much one event resembles the other event 0 Use base rate information if it is all that is available 0 Use descriptive information if available and disregard base rate information I Conjunction fallacy O Conjunction rule I The probability of two events cannot be higher than the probability of single constituents I People tend to violate the conjunction rule even though they understand it 0 Law of large numbers 0 The larger the number of individuals that are randomly drawn from a population the more representative of overall birthrate for males and females 0 Myside bias 0 The tendency for people to generate and evaluate evidence and test their hypothesis in a way that is biased toward their own opinions and attitudes I Three numbers 0 Myside bias is a type of confirmation bias 0 Confirmation bias 0 Holds for any situation 0 Tendency to selectively look for information that conforms to our hypothesis and overlook information that argues against it 0 Lord and coworkers 0 Had those in favor and against capital punishment to read the same article I Those in favor found the article convincing I Those against it found it unconvincing 0 Expected utility theory I People are rational I If they have all relevant information they will make a decision that results in the maximum expected utility 0 Utility I Outcomes that are desirable because they are in the person s best interest 0 Maximum monetary payoff 0 Advantages for utility approach 0 Specific procedures to determine the best choice 0 Problems for utility approach 0 Many decisions do not maximize the probability of the best outcome Decisionmaking 0 Emotion affect decisions 0 Expected emotions 0 Emotions people predict they will feel concerning an outcome 0 People inaccurately predict their emotions Incidental emotions emotions that are not specifically related to having to make a decision 0 May be related to ones general disposition or personality some recent experience or one s general environment or surroundings Decisions depend on how choices are presented 0 Optin procedure I Active step to be an organ donor 0 Optout procedure I Organ donor unless requested not to be Status quo bias 0 The tendency to do nothing when faced with making a decision Framing effect 0 Decisions are in uenced by how a decision is stated or framed I Can highlight one aspect of a situation 0 Tversky and Kahnemann I When situation are framed in terms of gain people tend toward a riskaversion strategy I When situations are framed in terms of losses people tend toward a risktaking strategy Neuroeconomics 0 One finding decisions are in uenced by emotions and those emotions are associated with activity in specific areas of the brain 0 How brain activation is related to decisions that involve potential losses and gains 0 Ultimatum game 0 fMRI Scanning During O Often rejected low offers because they became angry that offers were unfair 0 Less angry with an unfair computer 0 More activation of right anterior insula connected with emotional states participants more likely to reject more offers 0 Emotion is important in decisionmaking Deductive reasoning 0 Determining whether a conclusion logically follows from premises 0 Syllogism I Two statements called premises I Third statement called conclusion 0 Categorical syllogism I Describe relation between two categories using all no some Syllogism is valid if conclusion follows logically from its two premises If two premises of a valid syllogism are true the syllogism s conclusion must be true 0 Do not confuse validity with truth Many errors in evaluation 0 Belief bias the tendency to think that a syllogism is valid if its conclusions are believable Mental model 0 A specific situation represented in a person s mind that can be used to help determine the validity of syllogisms in deductive reasoning I Create a model of a situation I Generate tentative conclusions about model I Look for exceptions to falsify model I Determine validity of syllogism Conditional syllogisms 0 If p then q Effect of realworld items in a conditionalreasoning problem 0 Determine minimum number of cards to turn over to test if there is a vowel on one side then there is an even number on the other 0 The Wason fourcard problem I Necessary to turn E and 7 Falsification principle 0 To test a rule it is necessary to look for situations that would falsify the rule I More participants fail to do this I When problem is stated in concrete everyday terms correct responses greatly increase I beer and soda Permission schema if A is satisfied B can be carried out 0 Used in the concrete versions 0 People are familiar with rules 0 Based on the idea that people think in schemas Evolutionary principles of natural selection Wason task governed by builtin cognitive program for detecting cheating O In contrast to permission schema 0 More likely to detect cheating than other situations Social exchange theory 0 An important aspect of human behavior is the ability of two people to cooperate in a way that is beneficial to both of them


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