Introduction to Statistics - The Nonparametric Way (Hardcover, 1991 ed.)

The present text introduces the student to the basic ideas of estimation and hypothesis testing early in the course after a rather brief introduction to data organization and some simple ideas about probability. Estimation and hypothesis testing are discussed in terms of the two-sample problem. The book exploits nonparametric ideas that rely on nothing more complicated than sample differences Y-X, referred to as elementary estimates, to define the Wilcoxon-Mann-Whitney test statistics and the related point and interval estimates. The ideas behind elementary estimates are then applied to the one-sample problem and to linear regression and rank correlation. Discussion of the Kruskal-Wallis and Friedman procedures for the k-sample problem rounds out the nonparametric coverage. The concluding chapters provide a discussion of Chi-square tests for the analysis of categorical data and introduce the student to the analysis of binomial data including the computation of power and sample size. Most chapters in the book have an appendix discussing relevant Minitab commands.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Springer Texts in Statistics
Release date:	December 1990
First published:	1991
Authors:	Gottfried E. Noether
Assisted by:	Marilynn Dueker
Dimensions:	235 x 155 x 23mm (L x W x T)
Format:	Hardcover
Pages:	415
Edition:	1991 ed.
ISBN-13:	978-0-387-97284-8
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Promotions
LSN:	0-387-97284-6
Barcode:	9780387972848

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