Authors:
- Provides a cohesive and self-contained introduction to nonparametric statistical testing
- Includes exercises and solution tips
- Offers a unified perspective on a variety of nonparametric test problems
- Discusses concrete examples and computer implementations in addition to the mathematical theory
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This textbook provides a self-contained presentation of the main concepts and methods of nonparametric statistical testing, with a particular focus on the theoretical foundations of goodness-of-fit tests, rank tests, resampling tests, and projection tests. The substitution principle is employed as a unified approach to the nonparametric test problems discussed. In addition to mathematical theory, it also includes numerous examples and computer implementations. The book is intended for advanced undergraduate, graduate, and postdoc students as well as young researchers. Readers should be familiar with the basic concepts of mathematical statistics typically covered in introductory statistics courses.
Authors and Affiliations
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Institute for Statistics, University of Bremen, Bremen, Germany
Thorsten Dickhaus
About the author
Bibliographic Information
Book Title: Theory of Nonparametric Tests
Authors: Thorsten Dickhaus
DOI: https://doi.org/10.1007/978-3-319-76315-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-76314-9Published: 10 April 2018
Softcover ISBN: 978-3-030-09462-1Published: 12 January 2019
eBook ISBN: 978-3-319-76315-6Published: 27 March 2018
Edition Number: 1
Number of Pages: X, 124
Number of Illustrations: 2 b/w illustrations, 1 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Business, Management, Economics, Finance, Insurance, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics for Social Sciences, Humanities, Law, Statistics for Life Sciences, Medicine, Health Sciences