Nonparametric Statistics for the Biological Sciences

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

Chapter Chapter 1 in Introduction to Nonparametric Statistics for the Biological Sciences Using R, 2016, pp 1-50 from Springer

Abstract: Abstract Nonparametric statistics provide a useful purpose for inferential analyses when data: (1) do not meet the purported precision of an interval scale, (2) there are serious concerns about extreme deviation from normal distribution, and (3) there is considerable difference in the number of subjects for each breakout group. It is not totally uncommon to hear terms such as ranking tests and distribution-free tests to describe the inferential tests associated with nonparametric statistics, due to the use of nominal and ordinal data and data that may not meet the desired assumption of normal distribution (i.e., bell-shaped curve). Although those who work in the biological sciences would ideally like to have precise measurement for their data, to have data that follow normal distribution patterns, and to have adequately-sized samples for all breakout groups, only too often these three desires are not met. Nonparametric statistics and the many inferential tests associated with nonparametric statistics provide a valuable set of options on how these data can be used to good effect. Following along with these aspirations, the R environment and the many external packages associated with R offer many practical applications that support inferential tests associated with nonparametric statistics.

Keywords: Anderson-Darling test; Bar plot (stacked; side-by-side); Box plot; Central tendency; Code book; Continuous scale; Density plot; Distribution-free; Dotplot; Frequency distribution; Histogram; Interval; Mean; Median; Mode; Nominal; Nonparametric; Normal distribution; Ordinal; Parametric; Quantile-Quantile (QQ; Q-Q); Ranking; Ratio; Violin plot (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-30634-6_1

Ordering information: This item can be ordered from
http://www.springer.com/9783319306346

DOI: 10.1007/978-3-319-30634-6_1

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().