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Introduction to Modern Nonparametric Statistics

James J. Higgins

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ISBN 10: 0534387756 / ISBN 13: 9780534387754
Published by Duxbury Press, 2003
Used Condition: Used: Good Hardcover
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Bibliographic Details

Title: Introduction to Modern Nonparametric ...

Publisher: Duxbury Press

Publication Date: 2003

Binding: Hardcover

Book Condition:Used: Good

About this title

Synopsis:

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.

About the Author:

James J. Higgins is Professor of Statistics at Kansas State University and Fellow of the American Statistical Association. He is the co-author of the Duxbury textbook CONCEPTS IN PROBABILITY AND STOCHASTIC MODELING with Sallie Keller-McNulty and he is author of INTRODUCTION TO MODERN NONPARAMETRIC STATISTICS as well as having over 80 scientific publications to his credit. In addition, he is a statistical consultant for Kansas State Research and Extension. His research interests include nonparametric statistics and reliability theory.

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