Applied Nonparametric Statistics

This book PDF is perfect for those who love Mathematics genre, written by Wayne W. Daniel and published by Wadsworth Publishing Company which was released on 02 May 1990 with total hardcover pages 660. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Applied Nonparametric Statistics books below.

Applied Nonparametric Statistics

Author	: Wayne W. Daniel
File Size	: 51,8 Mb
Publisher	: Wadsworth Publishing Company
Language	: English
Release Date	: 02 May 1990
ISBN	: UOM:39015049287603
Pages	: 660 pages

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Applied Nonparametric Statistics by Wayne W. Daniel Book PDF Summary

This book covers the most commonly used nonparametric statistical techniques by emphasizing applications rather than theory. Exercises and examples are drawn from various disciplines including agriculture, biology, sociology, education, psychology, medicine, business, geology, and anthropology. The applications of techniques are presented in a step-by-step format that is repeated for all illustrative examples. Concepts are reinforced with many references to statistical literature to show the relevance to real-world problems. Chapters contain references of available computer programs and software packages that apply to methods presented in the book.

Applied Nonparametric Statistics by Wayne W. Daniel

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All of Nonparametric Statistics by Larry Wasserman

This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up

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An Introduction to Nonparametric Statistics by John E. Kolassa

An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention

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Nonparametric Statistics by Gregory W. Corder,Dale I. Foreman

“…a very useful resource for courses innonparametric statistics in which the emphasis is on applicationsrather than on theory. It also deserves a place in librariesof all institutions where introductory statistics courses aretaught." –CHOICE This Second Edition presents a practical andunderstandable approach that enhances and expands the statisticaltoolset for readers. This

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Nonparametric Statistical Methods by Myles Hollander,Douglas A. Wolfe,Eric Chicken

Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book

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A Parametric Approach to Nonparametric Statistics by Mayer Alvo,Philip L. H. Yu

This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make

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Nonparametric Statistics for Non Statisticians by Gregory W. Corder,Dale I. Foreman

A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the

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Practical Nonparametric Statistics by W. J. Conover

Probability theory; Statistical inference; Some tests based on the binomial distribution; Contingency tables; Some methods based on ranks; Statistics of the koolmogorov-smirnov type.

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