Lecture #5, Forms of Inference

Lecture #5, Forms of Inference - LECTURE #5: FORMS OF...

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LECTURE #5: FORMS OF INFERENCE - so far we have focused our attention on deductive arguments. - what is the definition of a deductive argument? - an argument where the conclusion follows from the premises with certainty. - if the premises are true, the conclusion must also be true. - we have done so because, in some respects, deductive arguments are the simplest to reconstruct and to criticize. - but, as we have seen, there are other forms of argument besides deductive. - a complex argument may contain inferences that are nondeductive as well as deductive. - [gun control argument overhead] - the argument we looked at last week, for example, contains deductive inferences, an argument from analogy, and overall has the structure of a convergent argument. - sometimes the premises of a deductive argument will be supported by nondeductive arguments. - purely deductive arguments are relatively rare. - tonight, we’re going to consider four forms of nondeductive arguments: inductive, causal, analogical, and convergent. - we’re going to find out how each one works and then consider some strategies for criticizing each one. - as usual, we’ll practice these techniques in class. - any questions? Inductive Arguments - the term inductive is sometimes used to refer to any argument form that is not deductive. However, it is commonly used to refer to arguments with statistical premises. - consider the following argument: [1 st Modes argmt] - this argmt is similar in form to one of the deductive argmt forms we’ve studied. - which form? [predicate instantiation] - do the premises support the conclusion? - I would say that they do support it, but not in the sense that they make the conclusion certain. - instead, if the premises are true, then the conclusion is likely to be true. - how likely? [66%] - would this argmt (assuming the premises were true) convince you to take Modes of Reasoning? - it might, but then again, it might not. It depends upon other factors. 66% is not that high. We’d like to see higher. - now consider this argmt: [2 nd Modes argmt] - now it just says “most” Modes students do better on essays. But how much is most? - again, the premises support the conclusion, but they don’t lend a lot of support. - we’d much rather see a quantified figure than “most.” - “most” could be anywhere from 51% to 99%. When I see an argmt of this form, it makes me wonder why they didn’t give exact figures. - why do you think they didn’t give exact figures? - probably because the figure is not that high (say, 66%) and they wanted to hide that fact. - so although an argmt like this one is technically successful, it is less successful than one which gives more specific information.
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- we might say it’s a C or a C+. A good argmt ought to do better. - what about this one? [Modes argmt #3]
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This note was uploaded on 02/07/2011 for the course MODR 1760 taught by Professor Camelacircelli during the Spring '11 term at York University.

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Lecture #5, Forms of Inference - LECTURE #5: FORMS OF...

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