Cognitive Psychology Exam 3 Logic and Decision Making 1 Assumptions Individuals are motivated to maximize utility o Achieve the greatest pleasure reward with the least pain cost Individuals must anticipate the outcome of alternative courses of action and calculate that which will be the best for them what will have the greatest utility Rational individuals choose the alternative that is likely to give them the greatest satisfaction 2 Rational Choice Decision Tree To play or not to play All the factors influencing the decision have a utility value By taking all the factors into consideration and calculating their utility we can reach a rational decision 3 Decision making using Bayes Theorem A mathematical model that provides a method for evaluating hypotheses when new information changes the probabilities of certain outcomes occurring Book example Did the dog eat the roast on the table and should we punish him o Prior Probability of guilt 95 based on the circumstances and knowing how much he likes roast o Conditional probability of guilt based on new info 2 we put food in front of him and he eats it vigorously not behavior of a well fed dog o Probability of effectiveness of punishment 40 o Bayes Theorem calculated to help us decide if punishing vs not punishing is more rational 4 Limits We obviously don t do this all that often if at all Example Ultimatum game Almakias Weiss 2012 o Your partner in the next room was given 50 and told to split it o If you accept his offer you both get the money o If you reject no one gets it 5 Three problems with the Rational Choice model We rarely have complete information It is too costly and time consuming to make decisions this way o We tend to be cognitive misers motivated to conserve cognitive resources o Cognitive resources are indeed limited and exhaustible So is our time o Instead we re more likely to satisfice using heuristics Choosing a good enough option decision or Satisficing solution Heuristics weight partial information Fast and frugal decision rules that heavily Heuristics are not necessarily wrong they can be adaptive but they lead us to be biased in predictable ways 6 Heuristics Representative Heuristic o The tendency to judge the frequency of an event by the extent to which it resembles a typical case o Judging the likelihood of things by how well they match prototypes Availability Heuristic o Ignoring base rates example with librarian vs salesperson o The tendency to judge the frequency or likelihood of an event by the ease with which instances come to mind o More memorable events are misperceived as more likely Anchoring Adjustment o The tendency to judge the frequency or likelihood of an event by using a starting point and then adjusting up or down from this starting point Deduction Reasoning from general premises which are known or presumed to be known to more specific certain conclusions Induction conclusions Reasoning from specific cases to more general but uncertain Both deductive and inductive arguments occur frequently and naturally both forms of reasoning can be equally compelling and persuasive and neither form is preferred over the other 7 Two basic categories of human reasoning 8 Deduction Vs Induction Deduction Commonly associated with formal logic Involves reasoning from known premises or premises presumed to be true to a certain conclusion The conclusions reached are certain inevitable inescapable It is the form or structure of a deductive argument that determines its validity Induction Commonly known as informal logic or everyday argument Involves drawing uncertain inferences based on probabilistic reasoning The conclusions reached are probable reasonable plausible believable By contrast the form or structure of an inductive argument has little to do with its perceived believability The fundamental property of a valid deductive argument is that if the premises are true then the conclusion necessarily follows The conclusion is said to be entailed in or contained in the premises Example use of DNA testing to establish paternity Deductive reasoning is either valid or invalid A deductive argument can t be sort of valid If the reasoning employed in an argument is valid and the argument s premises are true then the argument is said to be sound or credibility apart from making the argument seem more clear or more well organized The receiver or a 3rd party determines the worth of an inductive argument Inductive reasoning enjoys a wide range of probability it can be plausible possible reasonable credible etc The inferences drawn may be placed on a continuum ranging from cogent at one end to fallacious at the other Intelligence 1 History of IQ testing Identifying at risk children and High Potential children o First test was Binet Simon Test France 1905 o Adapted in English by Lewis Terman o Historical context was compulsory education 1910 and large immigrant population o Meant to both identify at risk children AND track students on career paths o IQ Mental age Actual age x 100 Tracking Army recruits in WWI o Terman adapted the Stanford Binet test for adults o Used to place 1 7 million army during WWI 1916 for US o A track recruits became officers o D E unfit for officer training 2 Legacy of Early Testing Biggest legacy o Intelligence was comprised of multiple abilities but could still be reduced to a single score Charles Spearman developed factor analysis to study different component parts of intelligence o Intelligence can be thought of as being represented by two factors g general intelligence s specific ability o People may have strengths in some domains over others but 40 50 of the variability in scores can be explained by g 3 Spearman Cattell s specific abilities of intelligence g factor Correlations among the subjects of intelligence test reflect an underlying ability called general intelligence g Verbal ability mathematical ability spatial ability reasoning ability and problem solving ability are all general intelligence 4 Further Refining of Intelligence Raymond Cattell 1905 o Student of Spearman s o Modified Spearman s intelligence theory to argue for two broader factors comprising intelligence Fluid Intelligence experience Crystallized Intelligence o Ability to perceive relationships without previous specific o Identifying patterns spatial rotation tasks pictoral analogies o Mental ability derived from previous experience including vocabulary use of tools objects culturally situated problem solving semantic
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