Critical Thinking

Chapter 11 Glossary

This alphabetical glossary contains short definitions for all the important terms and concepts from the chapter. You will also find hyperlinks to Websites relevant to the study of these terms and concepts. You should employ good critical thinking when evaluating the merit of any information you find on the World Wide Web, including what you find by following these links.


Analogical argument:  Also argument from analogy, inductive analogical argument: an inductive argument that uses the properties of a group to establish the property of another thing that resembles the members of that group.  the premises claim that one or more things have a property p, while the conclusion claims that the similar thing also has p.

Confidence level:  A measurement of the likelihood that an inductive generalization will produce a true conclusion.  Confidence level indicated the percentage of random samples in which the property in question occurs within the error margin.  (Note:  do not take confidence level in psychological terms, as a measure of how sure a person happens to feel about some generalization.  It is a quantifiable measurement of a generalization's actual application to random samples.)

Diversity:  In an analogical argument, the sample's inclusion of both members that possess and members that lack a property whose presence in the target population is not known.  Diversity makes for a stronger argument by factoring out the effects of the accidental features of things.

Error margin:  Also margin of error: in statistical generalizations, a measurement of the range in which a generalization is an accurate claim.  The error margin is stated in terms of plus or minus a number of percentage points.

Fallacy of anecdotal evidence:  A type of hasty generalization that uses a few examples to counter a claim based on solid evidence.

Fallacy of biased generalization:  The error of generalizing from an unrepresentative sample.  For example: "Cats ignore music; therefore, all animals ignore music."

Fallacy of hasty generalization:  The error of generalizing from a small sample--that is, from a sample smaller than required for reliable conclusions.

Gambler's fallacy:  The error of believing that past occurrences of a repeating random even will influence its future occurrences.  The gambler's fallacy misunderstands the law of large numbers to infer that future events will catch up with expected regularities.

Inductive generalization:  Also generalization: an inductive argument about a group that argues on the basis of a subset of that group for the existence of distribution of a property in the entire larger group.  The premises claim that the sample has the property (or has it in some proportion), while the conclusion claims that the target also does.

Law of large numbers:  a statistical principle about the properties of large numbers.  "The larger the number of chance-determined repetitious events considered, the closer the alternatives will approach predictable ratios."

Property in question:  the property being studied in an inductive argument.  It is first identified in a sample, then claimed to exist in the target population.

Sample:  The group whose members are known to have the property in question.  Inductive arguments begin with claims about a sample.

Sample size:  the number of members in a sample.  In all cases, larger samples make for more accurate conclusions.  In the case of statistical generalizations, as the sample size increases, the error margin decreases, or the confidence level increases, or both.

Statistical generalization:  a generalization that attributes a property to some proportion of the target populations.  This proportion is typically expressed as a percentage.

Target population:  The individual or group that may have the property in question.  The conclusion of an inductive argument is a claim about its target population.

General Analogy Web links:

Evaluating Opinion Polls:

 


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