ARGUING FROM THE SPECIFIC TO THE GENERAL (INDUCTIVE GENERALIZING) <br><br>It would be illogical to think that York’s being a teacher means he is a Democrat, if you had no reason to think that most teachers are Democrats. When does one have a good reason for thinking most Xs are Ys? This question concerns us next. One method of finding out what percentage of Xs are Ys is simply to observe all the Xs. If the Xs in question are the teachers in your school, and you want to know what percentage of them are Democrats, you could simply canvass them—assuming they are willing to tell you their politics. However, depending on what the Xs are, it may not be feasible to canvass them all. The population “American teachers,” for example, includes too many teachers to survey. To find out what percentage of American teachers are Democrats, you need to study a sample —a subset of American teachers—and probability theory—topics requiring entire books and courses and curricula to explore fully. Fortunately, the underlying logical principles of scientific generalizing from samples are straightforward and apply nicely to everyday generalizing. The basic form of all inductive generalizing, whether scientific or otherwise, is easily displayed using the teachers-and-Democrats example: <br><br>Such-and-such percent of surveyed American teachers are Democrats. <br>Therefore, the same percentage of all American teachers are Democrats. <br><br>To represent this even more schematically, since inductive generalizations can be about anything: <br><br>Such-and-such percent of observed Xs are Ys. <br>Therefore, the same percentage of all Xs are Ys.
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