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Asking the Right Questions, A Guide to Critical Thinking, 8th Ed

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How Good Is <strong>the</strong> Evidence 11? 123<br />

9. Are <strong>the</strong>re any biases or dis<strong>to</strong>rtions in <strong>the</strong> surveys, questionnaires, ratings, o<br />

o<strong>the</strong>r measurements that <strong>the</strong> researcher uses} We need <strong>to</strong> have confidence<br />

that <strong>the</strong> researcher has measured accurately what she has wanted <strong>to</strong><br />

measure. The problem of biased surveys and questionnaires is so pervasive<br />

in research that we discuss it in more detail in a later section.<br />

Generalizing from <strong>the</strong> Research Sample<br />

Speakers and writers usually use research reports <strong>to</strong> support generalizations,<br />

that is, claims about events in general. For example, "<strong>the</strong> medication was<br />

effective in treating cancer for <strong>the</strong> patients in <strong>the</strong> study" is not a generalization;<br />

"<strong>the</strong> medication cures cancer" is. The ability <strong>to</strong> generalize from research<br />

findings depends on <strong>the</strong> number, breadth, and randomness of events or people<br />

<strong>the</strong> researchers study.<br />

The process of selecting events or persons <strong>to</strong> study is called sampling.<br />

Because researchers can never study all events or people about which<br />

<strong>the</strong>y want <strong>to</strong> generalize, <strong>the</strong>y must choose some way <strong>to</strong> sample; and some ways<br />

are preferable <strong>to</strong> o<strong>the</strong>rs. You need <strong>to</strong> keep several important considerations in<br />

mind when evaluating <strong>the</strong> research sample:<br />

1. The sample must be large enough <strong>to</strong> justify <strong>the</strong> generalization or conclusion.<br />

In most cases, <strong>the</strong> more events or people researchers observe,<br />

<strong>the</strong> more dependable <strong>the</strong>ir conclusion. If we want <strong>to</strong> form a general<br />

belief about how often college students receive help from o<strong>the</strong>rs on term<br />

papers, we are better off studying 100 college students than studying 10.<br />

2. The sample must possess as much breadth, or diversity, as <strong>the</strong> types of<br />

events about which conclusions are <strong>to</strong> be drawn. For example, if<br />

researchers want <strong>to</strong> generalize about college students' drinking habits in<br />

general, <strong>the</strong>ir evidence should be based on <strong>the</strong> sampling of a variety of<br />

different kinds of college students in a variety of different kinds of college<br />

settings. Students at a small private school in <strong>the</strong> Midwest may have<br />

different drinking habits than students at a large public school on <strong>the</strong><br />

West Coast; thus, a study of students attending only one school would<br />

lack breadth of sampling.<br />

3. The more random <strong>the</strong> sample, <strong>the</strong> better. When researchers randomly<br />

sample, <strong>the</strong>y try <strong>to</strong> make sure that all events about which <strong>the</strong>y want <strong>to</strong>

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