Decision Making Lecture Notes PDF

12/5/24 CH.14 JUDGMENT, DECISIONS, AND REASONING PART II RECAP ¡ Inductive Reasoning ¡ Reasoning based on observations, data, evidence, patterns à derive a conclusion ¡ Heuristics = mental shortcuts. ¡ Availability Heuristics ¡ Representativeness Heuristics...

12/5/24 CH.14 JUDGMENT, DECISIONS, AND REASONING PART II RECAP ¡ Inductive Reasoning ¡ Reasoning based on observations, data, evidence, patterns à derive a conclusion ¡ Heuristics = mental shortcuts. ¡ Availability Heuristics ¡ Representativeness Heuristics 1  12/5/24 HEURISTICS ¡ Heuristic: informal strategy or approach that works under some circumstances, but is not guaranteed to yield the correct answer. ¡ Rule of thumb or Mental shortcut ¡ Advantage: saves resources at the cost of accuracy, fast decision making ¡ Disadvantage: it can be misleading, inaccurate decisions 2  12/5/24 SYLLOGISMS ¡ Syllogisms consist of three statements ¡ First two statements (premises): taken to be true (accept them as given). ¡ Third statement = the conclusion based on the first two. ¡ 2 types of syllogism ¡ Categorical syllogism ¡ Conditional syllogism 5 CATEGORICAL SYLLOGISM 3  12/5/24 CATEGORICAL SYLLOGISM ¡ All three statements (premises and conclusions) start with either ALL, NO, or SOME. ¡ Example and the form: ¡ Statement 1 (P1): All beagles are dogs. (All X are Y). ¡ Statement 2 (P2): All dogs are animals. (All Y are Z). ¡ Conclusion (C): Therefore, all beagles are animals. (All X are Z). ¡ Both premises are taken to be true, the conclusion follows logically, so the conclusion is valid Likely to rate as valid Likely to rate as invalid 4  12/5/24 EVALUATING SYLLOGISMS:VALIDITY AND TRUTH ¡ Good reasoning (judging validity) and truth are not the same thing. ¡ We are not always accurate at formal reasoning. ¡ We often take a believable conclusion as a logical argument (belief bias). CONDITIONAL SYLLOGISM 5  12/5/24 CONDITIONAL SYLLOGISM ¡ Three statements (2 premises & 1 conclusion) ¡ But it involves conditional clauses ¡ If P, then Q ¡ Antecedent = the IF statement ¡ Consequent = the THEN statement CONDITIONAL SYLLOGISM Form: ¡ P1: Conditional statement If P (antecedent) then Q (consequence). ¡ P2: Evidence ¡ Conclusion: that follows the logic of P1 & P2 ¡ A logical determination of whether the evidence supports, refutes, or is irrelevant to the stated relationship. 6  12/5/24 CONDITIONAL SYLLOGISM Example: ¡ Conditional statement (P1) : If I am going to drive a car, then I have to buckle up. ¡ Evidence (P2): I need to drive my car to campus today. ¡ Conclusion: I must buckle up. EVALUATING CONDITIONAL SYLLOGISM ¡ Form: (1) If P (antecedent) then Q (consequence) (2) Evidence (3) Conclusion ¡ Depends on the evidence ¡ 4 possible evidence: 1. Affirm the antecedent (P) VALID CONCLUSION 2. Deny the consequent (NOT Q) 3. Deny the antecedent (NOT P) INVALID CONCLUSION 4. Affirm the consequent (Q) 7  12/5/24 CONDITIONAL REASONING: EXAMPLE 1 1. Affirming the antecedent ¡ P1: If I am a freshman, (then) I have to register today. ¡ P2 (Evidence): I am a freshman ¡ Affirming the antecedent. ¡ C: Therefore, I have to register today ¡ VALID statement CONDITIONAL REASONING: EXAMPLE 2 2. Denying the consequent ¡ P1: If I am a freshman, (then) I have to register today ¡ P2 (Evidence): I do “not” have to register today. ¡ denying the consequent. ¡ C: Therefore, I’m not a freshman. ¡ VALID statement 8  12/5/24 CONDITIONAL REASONING: EXAMPLE 3 3. Denying the antecedent ¡ P1: If I am a freshman, (then) I have to register today ¡ P2 (Evidence): I am a “not” a freshman. ¡ denying the antecedent. ¡ C: Therefore, I do not have to register today ¡ (is this true ??) ¡ NO! -- INVALID statement. CONDITIONAL REASONING: EXAMPLE 4 ¡ Affirming the consequent ¡ P1: If I am a freshman, (then) I have to register today ¡ P2 (Evidence): I have to register today. ¡ affirming the consequent. ¡ Therefore, I am a freshman. ¡ (is this true ??) ¡ NO! -- INVALID statement 9  12/5/24 CONDITIONAL REASONING (4 POSSIBILITIES) Form Name Validity Example If P, then Q Affirming the Valid If I am a freshman, (then) I have to register today Evidence: P antecedent Inference Evidence: I am a freshman Therefore, Q Therefore, I have to register today If P, then Q Denying the Valid If I am a freshman, (then) I have to register today Evidence: NOT Q consequent Inference Evidence: I do not have to register today Therefore, NOT P Therefore, I am not a freshman If P, then Q Denying the Invalid If I am a freshman, (then) I have to register today Evidence: NOT P antecedent Inference Evidence: I am a not a freshman *Therefore, NOT Q * Therefore, I do not have to register today If P, then Q Affirming the Invalid If I am a freshman, (then) I have to register today Evidence: Q consequent Inference Evidence: I have to register today *Therefore, P * Therefore, I am a freshman 22 10  12/5/24 CONDITIONAL REASONING – ANOTHER EXAMPLE “If I am a driver, then I have a driver’s license.” ¡ Valid: ¡ Evidence à Affirming antecedent: I am driver. ¡ Conclusion: I have a driver’s license. ¡ Evidence à Denying the consequent: I do not have a driver’s license. ¡ Conclusion: I am not a driver. 24 CONDITIONAL REASONING – ANOTHER EXAMPLE “If I am a driver, then I have a driver’s license.” ¡ Invalid: ¡ Evidence à Denying the antecedent: I am not a driver ¡ I might or might not have a driver’s license ¡ Evidence à Affirming the consequent: I have a driver’s license ¡ I might or might not be a driver 25 11  12/5/24 CONDITIONAL REASONING – ANOTHER EXAMPLE “If a card has even number, then the other side is blue.” 4 7 Which card should you flip to gather the evidence that confirms it? 26 CONDITIONAL REASONING – ANOTHER EXAMPLE “If a card has even number, then the other side is blue.” 4 7 Which card should you flip to gather the evidence that confirms it? 27 12  12/5/24 ¡ Inductive reasoning ¡ But, heuristics can lead to wrong conclusion. ¡ Deductive reasoning ¡ Categorical syllogism ¡ Conditional syllogism DECISION MAKING § Expected Utility Theory § How people will choose in uncertainty. § If rational à people will choose the option that maximizes the expected utility (possible outcomes) § We are rational within limits 13  12/5/24 DECISION MAKING: EXPECTED UTILITY Your goal is to pick out a red bean. You can try with only one bowl. Which of the two bowls will you choose to get the red bean? DECISION MAKING: EXPECTED UTILITY § Expected Utility Theory § How people will choose in uncertainty. § If rational à people will choose the option that maximizes the expected utility (possible outcomes) § We are rational within limits We sometimes / often ignore probabilities when making decisions. 14  12/5/24 DECISION MAKING: EMOTION § Expected Emotion § We make decisions based on how we think they’ll make us feel § Risk aversion § Incidental Emotion § Emotions not tied to a decision § Clouds make nerds look good (Simonsohn, 2007, 2009) DECISION MAKING: CONTEXT ¡ Status quo bias: tendency to not make a decision ¡ Opt-in-procedure: make a choice to get X ¡ Opt-out-procedure: make a choice to not get X ¡ Let’s assume X = green choice energy program ¡ Which of the two procedures would you have more sign ups for the green choice energy program? Opt-out procedure 15  12/5/24 FINAL EXAM & REVIEW SESSIONS ¡ REVIEW SESSIONS (see the announcement) ¡ FINAL EXAM ¡ Dec 9th (Monday) from 12:50 -- 2:50 PM (Location: SL 212) SOOT survey: https://soot.binghamton.edu/ Google form for your feedback. THANKS FOR A GREAT SEMESTER! 16