05.31.Reasoning.DecisionMaking.docx

Reasoning and Decision Making 05/31/23 Learning Objectives Two Types of reasoning Deductive Process of reasoning from one or more general statements (premises) to reach a logically certain conclusion Conlucsions follow directly form premises using rules of logic. Guaranteed to be correct (if you f...

Reasoning and Decision Making 05/31/23 Learning Objectives Two Types of reasoning Deductive Process of reasoning from one or more general statements (premises) to reach a logically certain conclusion Conlucsions follow directly form premises using rules of logic. Guaranteed to be correct (if you follow the rules) Inductive Reasoning (probabilistic) Reasoning that constructs or evaluates general propositions that are derived (observed) from specific examples Probably guesses based on prior evidence Notn guaranteed to be correct Sometimes called “cause and effect” reasoning Deductive top down Inductive bottom up Deductive Reasoning (guaranteed to be true IF premises are true_ Using logic to make deduxctions Syllogism logical argument that consist of two premises followed by a conclusion Is this syllogism valid? All P are M All S are M Therefore all S are P Belief Bias May Lead Us to Wrong Conclusions Belief bias (if it corresponds to my knowledge and beliefs, it may be true) involves a tendency to Reject valid conclusions when they are unbelievable Accept invalid conclusions if they are believable REVIEW EXAMPLES OF BELIEF BIAS SLIDE (12) ON EXAM Conditional Statements A conditional statement has the format “if x, then y” The first part (antecedent) provides a condition under which the second part (consequent) is guaranteed to be true 1st premise = antecedent 2nd premise= consequent; logic = ______09:20 If today is Tuesday, then John will go to work. Today is Tuesday. Therefore, John will go to work. Modus Ponens Rule of Logic Modus Ponens: the rule of logic stating that if a conditional statement (if p then q) is accepted, and the antecedent holds (p), then the consequent may be inferred (q) Premise If P (antecedent), then Q (consequent) P (lets call this “what you’re given”) Conclusion Therefore Q Arguments of this form are valid Affirming the COnseqeunt (error in logic) (where this can go wrong is when you infer the wrong thing If you’re given Q, you assume P is true. Premise If P, then Q Q Conclusion Therefore P Arguments of this form are invalid think of this going as backwards in your reasoning Modus Tollens Rule of Logic Modus tollens the rule of logic stating that if conditional statement (if p then q) is acceptaed, and the consequent does NOT hold (NOT q) then the negative of the antecedent can be inferred (NOT p) Premise If it is raining, than Aliciagets wet (if R then W) It is not raining (not R) Conclision It is not rainign (not R) Arguments of this form are valid If its raining then Alicia will get wet \ Directionality of the inference is CRITICAL if negative modus tollens if positive modus ponens IF A, then B. A, therefore B modus ponens If A, then B. Not B, therefore, not A Another Test of Deductive Reasoning the Wason 4-card selection task each card has a number on side and a letter on the other Proposed Rule If there is an G on the side of the card, there there is a 3 on the other side Which card would you choose? “G” and “7” The wason task IRL Another proposed rule: Another proposed rule If someone drinks beer, then he/she must be 21 or over Flip? Beer and 19 Only 70% of people pass it looking for evidence to disconfirm, thus, no info is gained from flipping over 3, bc we know what it should be Inductive Reasoning In many cases, we cannot rely upon deductive inferences Instead, we rely upon induction Induction: forming generalizations based on specific incidents you’ve experienced, observations you’ve made, or facts you know to be true or false Induction does not guarantee a correct answer However, some inferences are more likely to be right than others Example of Induction We would like to form universal generalizations about the world All X’s are Y Eg., all swans are white These are based upon our previous experience Swan #1 was white … Swan #3265 was white Thus, you conclude all swans are white The problem with induction But induction is only guaranteed if we have experienced all possible instances There are black swans in Australia Basically, induction involves probabilities Induction and Confirmaiton Bias Confirmation bias More responsive to evidence that confirms one’s beliefs Essentially, we ignore disconfirming data Can lead to perpetuation of unfounded stereotypes Other Examples of Confirmation Bias Superstitions If I Velcro, un-velcro, and re-velcro my batting gloves, I’m more likely to get a hit Or conspiracy theories The moon landing was fake Notice examples that fit this pattern more readily (a bias in your attention) Will recall examples that fit the pattern more readily (a bias in your memory) Decision Making The goal most of decision making is to get the most/best stuff as often as possible This involves two kinds of information 1) how important is each outcome (how much value you place on that outcome) UTILITY 2) how likely is each outcome? PROBABILITY Expected Utility Theory According to EUT, a rational person should try to clc the expected utility (or “expected value”) of each option and choose the option that maximizes this Involves balancing costs and benefits; assumes individual is behaving and making decisions rationally Expected value = probability of a particular outcome * value of the outcome Eg., if playing roulette and there is 1/20 chance of winning $100, the expected value of the gamble is $5 If given option of certain $50, or a 50/50 shot to win $100 or nothing, people tend to choose the certain people are risk averse when it comes to gains Reversing the framing, losing vs gaining People are more risk-seeking when it comes to losses (chance to mitigate loss) Shows people HATE losing thus, will take risk of loss Framing Effects Problem 1 Program A 200 butterflies will be saved Program B 1/3 probability that 600 butterflies will be saved, and 2/3 probability that no butterflies will be saved Which would you choose? 72% choose A Problem 2 Program C 400 butterflies die Program D there is 1/3 that no butterflies will die, and 2/3 probability that 600 butterflies will die About 78% choose D Positive vs. Negative Framing If program A is adopted, 200 are saved (gain frame take sure thing and people are risk averse) If program B is adopted, ther is 1/3 probaility that 600 buterflies saved, and 2/3 that none will be saved Program C 400 die Program D 1/3 no die, 2/3 all will die (loss frame people are risk seeking) Prospect Theory Circling back do our preferenes for particular outcomes map directly onto their expected value? Answer not really. People don’t always make rational decisions Prospect Theory People make decision based on the potential gain or losses relative to their specific situation (the reference point) rather than in absolute terms describes how people ACTUALLY behave Its asymmetric a bigger impact of LOSSES than of gains In general, we are more loss averse More sensitive to losing $50, compared to winning $50 Point is, if you will lose the same amount as gain, you we will value the loss more. Humans hate to lose THM People hate to lose and will avoid losing as often as possible In a gain frmae, avoiding loss means choosing the sure thing In a loss frame, takinga risk to gain money is worth the gamble, because it means you might not lose A sure gain is preferred to a probable one, and probable loss is preferred to a sure loss.