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Nonparametric statistics for applied research / Jared A Linebach, Brian P. Tesch and Lea M. Kovacsiss.

By: Contributor(s): Material type: TextTextPublication details: New York : Springer, 2014.Description: xii, 408 p. ; illustrations (some color)ISBN:
  • 9781461490401
Subject(s): DDC classification:
  • 23 L754 000SA.12
Contents:
1. Introduction-- 2. Meeting the Team -- 3. Questions, Assumptions, and Decisions -- 4. Understanding Similarity -- 5. The Bourgeoisie, the Proletariat, and an Unwelcomed Press Conference -- 6. Agreeing to Disagree -- 7. Guesstimating the Fluffy-Maker -- 8. X Marks the Spot Revisited -- 9. Let My People Go! -- 10. Here's Your Sign and the Neighborhood Bowling League -- 11. Geometry on Steroids -- 12. Crunch Time -- 13. Presentation to the Governor-- Appendices-- Answers to "Check Your Understanding" Questions-- Glossary-- Bibliography-- Index--
Summary: Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in "ordinal" data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.12 L754 (Browse shelf(Opens below)) Available 135390
Total holds: 0

Includes bibliographical references and index.

1. Introduction--
2. Meeting the Team --
3. Questions, Assumptions, and Decisions --
4. Understanding Similarity --
5. The Bourgeoisie, the Proletariat, and an Unwelcomed Press Conference --
6. Agreeing to Disagree --
7. Guesstimating the Fluffy-Maker --
8. X Marks the Spot Revisited --
9. Let My People Go! --
10. Here's Your Sign and the Neighborhood Bowling League --
11. Geometry on Steroids --
12. Crunch Time --
13. Presentation to the Governor--

Appendices--
Answers to "Check Your Understanding" Questions--
Glossary--
Bibliography--
Index--

Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in "ordinal" data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine.

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