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Reasoning n Deductive Reasoning Deductive reasoning vs. Inductive reasoning n n Deductive reasoning n If valid argument (follows logical rules) n Logic n Facts -- items that may be true or false n Operators -- truth value depends on facts and n n If premises are true n Then conclusions are true (guaranteed) n Have truth table AND, OR, NOT AND(A,B) n Inductive reasoning n No certainty about truth n Assess probability of conclusion being true OR(A,B) A is FALSE A is TRUE B is FALSE FALSE FALSE B is FALSE FALSE TRUE B is TRUE FALSE TRUE B is TRUE TRUE TRUE Schemas n Templates for combining operators and facts n P OR Q NOT P ∴Q Deductive Reasoning n n n n n If Premises true and argument valid ---Conclusion Conclusion true Domain general Apply schemas to any situation If premises true and valid form n n n n n n n n n n First part of conditional -- antecedent (e.g,. P) Second part of conditional -- consequent (e.g., Q) Modus Ponens (affirming the antecedent) P→Q P n ∴Q n n n Valid? n n n Truth – statement about world (premises or conclusion) Validity – form of the argument Conditional Schemas Conditional statements Propositional Calculus reasoning from "if then" statements P → Q (if P then Q) P (P is TRUE) ∴Q (therefore Q is TRUE) Conclusions guaranteed to be true Note: n n A is FALSE A is TRUE Yes Example If it is sunny then Dr. Mounts will play golf It is sunny n ∴ Dr. Mounts will play golf n n 1 Conditional Schemas n Conditional Schemas Modus Tollens (denying the consequent) Denying the Antecedent n P→Q n NOT Q n ∴NOT P n n n Valid? n n P→Q NOT P n ∴NOT Q n Yes n Valid? n Example n Example If it is sunny then Dr. Mounts will play golf Dr. Mounts will not play golf n ∴ It is not sunny n No If it is sunny then Dr. Mounts will play golf It is not sunny n ∴ Dr. Mounts will not play golf n n n Conditional Schemas n Human Performance Affirming the Consequent P→Q Q n∴P n n Modus Ponens -- affirming the antecedent n n n n Valid? n n n Modus Tollens -- denying the consequent n No n Example n If it is sunny then Dr. Mounts will play golf n Dr. Mounts will play golf n ∴ It is sunny n People are good at Will use spontaneously People are not good at Typically don’t use spontaneously Affirming the consequent n n Examples Often tempting to people Will use -- even though invalid Wason (1968) (1968)--- 4 card problem If it rains today, the game will be cancelled n It rained today n ∴The game was cancelled n If it rains today, the game will be cancelled The game was not cancelled n ∴It did not rain today E n n If it rains today, the game will be cancelled The game was cancelled n ∴It rained today n n n F 2 5 If a card has a vowel on one side, it will have an even number on the back Which cards allow you to evaluate hypothesis? E -- modus ponens (affirming the antecedent) [valid] n 2 -- affirming the consequent [invalid] n F -- denying the antecedent [invalid] n 5 -- modus tollens (denying the consequent) [valid] n n 2 Wason (1968) results n Vowel (E) only -- 33% n n Vowel: Modus ponens ponens--- valid Vowel (E) + Even (2) -- 46% Why so bad n n n Confirmation bias Matching Content / Familiarity Vowel: Modus ponens ponens--- valid n Even: affirming the consequent -- invalid n n Vowel (E) + Odd (5) -- 4% -- correct answer n n Vowel: Modus ponens -- valid Odd: Modus tollens -- valid Confirmation bias n People readily use modus ponens n n n Look for evidence consistent with beliefs Mistakenly affirm the consequent People don't use modus tollens n Matching n n n n People assume all information conveyed relevant People don’t process all information fully Surface structure of hypothesis If Vowel then Even n Looking for evidence inconsistent with beliefs n n Check Vowel Check Even Performance much better on: n If a card has a vowel on one side, then it will not have an even number on the other side. Familiarity n n n Familiar examples help reasoning Aids in finding appropriate reasoning schema Pragmatic reasoning schemas n schema or outline for interacting with world n different schemas for different situations n fairly concrete "rules" to follow n obligation schema n permission schema Familiarity Example n Everyone drinking beer must be 21 n Who do you check? Ned Beverage: Age: Beer ?? Ted Soda ?? Jed ?? 22 Zed ?? 19 3 Hypothesis Testing n n n n n n If my hypothesis is correct, then I will obtain specific pattern of results Hypothesis → Results Hypothesis ∴ Results Modus Ponens -- Valid Not applicable (Can’ (Can ’t know truth of hypothesis) Hypothesis Testing n n n n n n n n n n Hypothesis → Results Not Results ∴ Not Hypothesis Affirming the consequent Invalid The Null Hypothesis Hypothesis Testing n Hypothesis → Results Results ∴ Hypothesis Null Hypothesis Null Hypothesis → Null Results Not Null Results n ∴ Not Null Hypothesis n n n Combined with: Null Hypothesis OR Alternative Hypothesis Not Null Hypothesis n ∴ Alternative Hypothesis n Modus Tollens -- Valid Conclude hypothesis is wrong n n Why is this initially difficult n Uses Modus Tollens 4