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REASONING
Chapter Six
methods of reasoning
 argument: premise -> conclusion
logical if the premise cannot be true without the
conclusion also being true
 Boolean operators (“and”, “or”, etc.)
 contradiction: p&p, tautology: (p&p)
 truth-tables p q p->q
T T T
T F F
F T T
F F T
modern logic
 everyone has a mother, so there is someone
who is everyone’s mother
 subject-predicate information, quantifiers
(y) (x) xMy (x) (y) xMy
“there is nobody who is the mother of everybody”
“x is the mother of y”
existential quantifier: “someone is the mother of y”
universal quantifier: “everyone has a mother”
language and logic
“Tom was polite even though he smoked”
truth-condition implicature
 presupposition, terminology, word order
“Have you stopped beating your wife?”
“Is your brother still in the hospital?”
plausible reasoning
 most possibilities lead to the conclusion
being true
 inductive inference
 probabilities of the real world?
 no logical argument for the uniformity of nature
 Bayes’s theorem
Prob (h/e) = Prob (h) x Prob (e/h)
Prob (e)
the prior probability of the evidence
the probability of e, given h
the prior probability of the hypothesis
the probability
of h, given e
(The end)

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Reason

  • 2. methods of reasoning  argument: premise -> conclusion logical if the premise cannot be true without the conclusion also being true  Boolean operators (“and”, “or”, etc.)  contradiction: p&p, tautology: (p&p)  truth-tables p q p->q T T T T F F F T T F F T
  • 3. modern logic  everyone has a mother, so there is someone who is everyone’s mother  subject-predicate information, quantifiers (y) (x) xMy (x) (y) xMy “there is nobody who is the mother of everybody” “x is the mother of y” existential quantifier: “someone is the mother of y” universal quantifier: “everyone has a mother”
  • 4. language and logic “Tom was polite even though he smoked” truth-condition implicature  presupposition, terminology, word order “Have you stopped beating your wife?” “Is your brother still in the hospital?”
  • 5. plausible reasoning  most possibilities lead to the conclusion being true  inductive inference  probabilities of the real world?  no logical argument for the uniformity of nature  Bayes’s theorem Prob (h/e) = Prob (h) x Prob (e/h) Prob (e) the prior probability of the evidence the probability of e, given h the prior probability of the hypothesis the probability of h, given e