Lesson_Twelve_and_Test

# Lesson_Twelve_and_Test - LESSON 12 Inductive Logic Section...

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Section 30: Induction and Probability , Barker, pp. 181-185. ***Read the section, then the following additional comments. In this lesson we look at inductive logic . Of course, there will be rules and some standardization. But, appearances notwithstanding, we are now in the territory of informal logic . What this means is that we are dealing with arguments whose conclusions do not flow from the premises with iron-clad necessity. Any inductive argument begins with observation . Such an observation can be as simple as opening your eyes and looking or as complex as gathering statistics on a certain subject. In either case somehow the initial gathering of information is crucial. We accumulate certain facts which we have observed to be true. An inductive argument concludes by making a statement that in some way goes beyond the observation. The conclusion could be a generalization about all similar facts (particular to general) or it could be a prediction about a yet-to-be-observed item (particular to particular). Whatever the case, an inductive argument tells us on the basis of observation what we might find to be true of things which we have not yet observed. Consequently, an inductive argument can only deal in probability . But don’t let that word throw you off. In many cases the probability of an induced conclusion may be so high as to be virtually certain and irrefutable, though at other times it could be fairly improbable. The point is that, as long as we extend ourselves beyond observations, there is always some chance—no matter how minute—that the next observation might throw over our conclusion. In practice, that possibility is often too improbable to worry about. For example, after having eaten thousands of hamburgers in my lifetime, I conclude (inductively) that the next hamburger I eat will nourish me in the same manner as all the previous ones. This judgment is a matter of probability, to be sure, but it’s not a gamble; the probability is virtual certainty. An inductive argument with a highly probable conclusion is a strong argument (corresponding to a “valid” deductive argument). Combining a strong argument with true premises produces a reliable inductive argument (corresponding to a “sound” deductive argument). ***Prepare for submission Exercises 30 A and B. Examples 30A 1. This is a relatively weak statement. Yes, there is predictive value in weather observations, but we all know that such observations always have degrees of 1 LESSON 12 Inductive Logic

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probability, which are sometimes very limited. You can’t fault yourself for missing on a weather prediction. 30B 1. This is, in fact, a silly statement by itself. Sure, ultimately all statements are either exactly true or exactly false, but we don’t always know these things with exactness. What probability and improbability are about is helping us to determine whether a
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Lesson_Twelve_and_Test - LESSON 12 Inductive Logic Section...

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