An Introduction to Modern Nonparametric Statistics - Couverture rigide

Higgins, James

Couverture rigide

ISBN 10 : 0534387756 ISBN 13 : 9780534387754

Editeur : Brooks/Cole, 2003

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.

A propos du livre

À propos de l'auteur

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.

Détails de l'édition

• Éditeur: Brooks/Cole
• Date d'édition: 2003
• Langue: anglais
• ISBN 10: 0534387756
• ISBN 13: 9780534387754
• Reliure: Relié
• Nombre de pages: 500
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible