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Erschienen in:
2013 | OriginalPaper | Buchkapitel
17. Nonparametric Statistics
verfasst von : Cheng-Few Lee, John C. Lee, Alice C. Lee
Erschienen in: Statistics for Business and Financial Economics
Verlag: Springer New York
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Abstract
In previous chapters, we discussed alternative tests of hypotheses. These tests were generally concerned with statistical measures such as the mean, variance, or proportion of a population. A mean, variance, or proportion is referred to as a parameter in statistics. To test these parameters, we generally assume that the sample observations were drawn from a normally distributed population. The assumption of normality is especially critical when the sample size is small. Tests such as the Z, t, and F tests discussed in Chap. 11 depend on assumptions about the parameters of the population, so all these tests are parametric tests or classical tests. A parametric test is generally a test based on a parametric model.