Sign Test

Thomas W. MacFarland and Jan M. Yates
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Thomas W. MacFarland: Nova Southeastern University, Office of Institutional Effectiveness
Jan M. Yates: Nova Southeastern University, Abraham S. Fischler College of Education

Chapter Chapter 2 in Introduction to Nonparametric Statistics for the Biological Sciences Using R, 2016, pp 51-76 from Springer

Abstract: Abstract The Sign Test is typically used to examine differences between two sets of data at the broadest level of comparison. As this lesson is structured, the nonparametric Sign Test is used to examine any possible difference between pretest and posttest measures but with the caution that the Sign Test is by no means as robust as other statistical tests. Even with limited rigor, the Sign Test is an excellent exploratory test and the use of this tool should not be overlooked when working with data that support nonparametric analyses. It is interesting to note that the Sign Test name, itself, is due to signs (i.e., −, +, and o) being derived from measured data. These signs are used to represent direction, as will be shown in this lesson.

Keywords: Anderson-Darling test; Bar plot (stacked; side-by-side); Code book; Continuous scale; Density plot; Descriptive statistics; Distribution-free; Frequency distribution; Histogram; Interval; Mean; Median; Mode; Nominal; Nonparametric; Normal distribution; Null hypothesis; Ordinal; Parametric; Probability (p-value); Quantile-Quantile (QQ; Q-Q); Ranking; Ratio; Sign test; Statistical significance (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-30634-6_2

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