An introduction to modern nonparametric statistics
by James J. Higgins
- 6 Want to read
- 1 Currently reading
Guided by problems that frequently arise in actual practice, James Higgins’ book presents a wide array of nonparametric methods of data analysis that researchers will find useful. It discusses a variety of nonparametric methods and, wherever possible, stresses the connection between methods. For instance, rank tests are introduced as special cases of permutation tests applied to ranks. The author provides coverage of topics not often found in nonparametric textbooks, including procedures for multivariate data, multiple regression, multi-factor analysis of variance, survival data, and curve smoothing. This truly modern approach teaches non-majors how to analyze and interpret data with nonparametric procedures using today’s computing technology.
Check nearby libraries
Buy this book
| Edition | Availability |
|---|---|
1
An introduction to modern nonparametric statistics
2003, Brooks/Cole
in English
0534387756 9780534387754
|
aaaa
|
Book Details
Edition Notes
Includes bibliographical references (p. 351-355) and index.
Classifications
The Physical Object
Edition Identifiers
Work Identifiers
Community Reviews (0)
Lists
See All
History
- Created November 17, 2008
- 8 revisions
Wikipedia citation
×CloseCopy and paste this code into your Wikipedia page. Need help?
| December 19, 2023 | Edited by ImportBot | import existing book |
| December 30, 2022 | Edited by MARC Bot | import existing book |
| December 5, 2020 | Edited by MARC Bot | import existing book |
| August 19, 2010 | Edited by IdentifierBot | added LibraryThing ID |
| November 17, 2008 | Created by ImportBot | Imported from University of Toronto MARC record |