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Unformatted text preview: 3. b) Describe the features of the sample which bias it. The sample is limited to just one city, which introduces sample bias. People vary widely, and geographic region is one of the features that changes how people behave. A good counterargument could discuss the differences between Calgary and other cities, or Calgary and nonurban areas. See pp. 235– 239. Good Reasoning Matters! A Constructive Approach to Critical Thinking , Fifth Edition © Oxford University Press Canada, 2012 Passage 10 1. c) General causal reasoning. General causal reasoning proceeds as follows: X is correlated with Y ; the correlation between X and Y is not due to chance; the correlation between X and Y is not due to some mutual cause Z ; Y is not the cause of X ; therefore, X causes Y . See pp. 227–229, 233–235, 241–242. 2. b) The second premise (in which the correlation between X and Y is not due to chance) . For there to be a problem here, it must be that the correlation is due to chance or the possibility of chance has not been ruled out. See pp. 243–244. 3. b) Show that the correlation between X and Y could be due to chance. As long as the arguer hasn’t ruled out chance—and this arguer has not—it is enough to show that the correlation could be chance in order to undermine the causal claim. That also shouldn’t be too hard. After all, ice cream can disappear through other means: it can melt, and it can be eaten by other people. These possibilities could be introduced and explained. See pp. 244– 245. Passa g e 11 1. c) General causal reasoning. General causal reasoning is as follows: X is correlated with Y ; the correlation between X and Y is not due to chance; the correlation between X and Y is not due to some mutual cause Z ; Y is not the cause of X ; therefore, X causes Y . See pp. 227–229, 233–235, 241–242. 2. b) The second premise (in which the correlation between X and Y is not due to chance) . For there to be a problem here, it must be that the correlation is due to chance or the possibility of chance has not been ruled out. See pp. 243–244. 3. b) Show that the correlation between X and Y could be due to chance . As long as the arguer hasn’t ruled out chance—and this arguer has not—it is enough to show that the correlation could be chance in order to undermine the causal claim. This shouldn’t be too difficult in this case. Given the number of pieces involved in an engine, there are many other possible causes of the oil leaking. Any one of those parts could be failing. See pp. 244–245. Passage 12 1. c) What has failed to restore narwhal populations off the BC coast will fail to restore narwhal populations in Canada’s North . Generalization proceeds as follows: S is a sample of X s; Proportion 1 of X s in S are Y ; therefore, Proportion 2 of X s are Y . This is distinct from polling because it does not rely on a poll. See pp. 227–229....
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 Summer '09
 JURKOWSKI
 Logic, Districts of Vienna, Fifth Edition, Oxford University Press Canada, general causal reasoning

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