Nonparametric Statistics

Cheng-Few Lee, John C. Lee and Alice C. Lee
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Cheng-Few Lee: Rutgers University Business School, Department of Finance and Economics
John C. Lee: Center for PBBEF Research

Chapter Chapter 17 in Statistics for Business and Financial Economics, 2013, pp 877-925 from Springer

Abstract: 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.

Keywords: Percent Level; Personnel Manager; Spearman Rank Correlation Test; Efficient Market Hypothesis; Expense Ratio (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-1-4614-5897-5_17

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