Applied Nonparametric Statistical Methods Fourth Edition
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Applied Nonparametric Statistical Methods
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Author : Peter Sprent
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Applied Nonparametric Statistical Methods written by Peter Sprent and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Mathematics categories.
While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. Reorganized and with additional material, this edition begins with a brief summary of some
Applied Nonparametric Statistical Methods
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Author : P. Sprent
language : en
Publisher:
Release Date : 1993
Applied Nonparametric Statistical Methods written by P. Sprent and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
Applied Nonparametric Statistical Methods
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Author : Nigel C. Smeeton
language : en
Publisher:
Release Date : 2025
Applied Nonparametric Statistical Methods written by Nigel C. Smeeton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Applied Nonparametric Statistical Methods, Fifth Edition, is a comprehensive course text in nonparametric techniques suitable for undergraduate students of mathematics and statistics. It assumes only basic previous experience of statistics, and with algebra kept to a minimum, it is also ideal for quantitative methods modules delivered to undergraduate or postgraduate students in science, business and health service training. It is an invaluable resource for researchers, medical practitioners, business managers, research and development staff, and others needing to interpret quantitative information. Suitable for self-directed learning in continuing professional development, it also acts as a handy accessible reference manual.
Applied Nonparametric Statistical Methods Third Edition
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Author : Peter Sprent
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2000-09-07
Applied Nonparametric Statistical Methods Third Edition written by Peter Sprent and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-09-07 with Mathematics categories.
This new edition follows the basic easy-to-digest pattern that was so well received by users of the earlier editions. The authors substantially update and expand Applied Nonparametric Statistical Methods to reflect changing attitudes towards applied statistics, new developments, and the impact of more widely available and better statistical software. The book takes into account computing developments since the publication of the popular Second Edition, rearranging the material in a more logical order, and introducing new topics. It emphasizes better use of significance tests and focuses greater attention on medical and dental applications. Applied Nonparametric Statistical Methods: Third Edition explains the rationale of procedures with a minimum of mathematical detail, making it not only an outstanding textbook, but also an up-to-date reference for professionals who do their own statistical analyses. New in the Third Edition: Expanded coverage of topics - such as ethical considerations and calculation of power and of sample sizes needed Refers to a wide variety of statistical packages - such as StatXact, Minitab, Testimate, S-plus, Stata, and SPSS Includes sections on the analysis of angular data, the use of capture-recapture methods, the measurement of agreement between observers, runs tests, and regression diagnostics.
Applied Nonparametric Statistical Methods
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Author : Nigel Smeeton
language : en
Publisher: CRC Press
Release Date : 2025-03-31
Applied Nonparametric Statistical Methods written by Nigel Smeeton and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Mathematics categories.
Nonparametric statistical methods minimize the number of assumptions that need to be made about the distribution of data being analysed, unlike classical parametric methods. As such, they are an essential part of a statistician’s armoury, and this book is an essential resource in their application. Starting from the basics of statistics, it takes the reader through the main nonparametric approaches with an emphasis on carefully explained examples backed up by use of the R programming language. Key features of this fully revised and extended fifth edition include the following: An introductory chapter that provides a gentle introduction to the basics of statistics, including types of data, hypothesis testing, confidence intervals and ethical issues An R package containing functions that have been written for the examples in the text and the exercises Summary bullet points at the end of each section to enable the reader to locate important principles quickly A case study from medical research to demonstrate nonparametric approaches to the data analysis Examples fully integrated into the text, drawn from published research on contemporary issues, with more detail given in their explanation Extensive exercises along with complete solutions that allow the reader to test their understanding of the material Articles used in the examples and exercises carefully chosen to enable readers to identify up-to-date literature in their field for research, publications and teaching material Numerous historical references throughout the text, from which to explore the origins of nonparametric methods Applied Nonparametric Statistical Methods, Fifth Edition, is a comprehensive course text in nonparametric techniques suitable for undergraduate students of mathematics and statistics. It assumes only basic previous experience of statistics, and with algebra kept to a minimum, it is also ideal for quantitative methods modules delivered to undergraduate or postgraduate students in science, business and health service training. It is an invaluable resource for researchers, medical practitioners, business managers, research and development staff, and others needing to interpret quantitative information. Suitable for self-directed learning in continuing professional development, it also acts as a handy accessible reference manual.
Applied Nonparametric Statistical Methods
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Author : Peter Sprent
language : en
Publisher:
Release Date : 1989
Applied Nonparametric Statistical Methods written by Peter Sprent and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Nonparametric statistics categories.
Applied Nonparametric Statistical Methods
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Author : Neil Spencer
language : en
Publisher:
Release Date : 2025-02-14
Applied Nonparametric Statistical Methods written by Neil Spencer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-14 with Mathematics categories.
A comprehensive course text in nonparametric techniques suitable for undergraduate mathematics students. Assumes only basic experience of statistics with algebra kept to a minimum. Ideal for quantitative methods modules delivered to undergraduate or postgrad students in science, business, and health service training.
Multivariate Survival Analysis And Competing Risks
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Author : Martin J. Crowder
language : en
Publisher: CRC Press
Release Date : 2012-04-17
Multivariate Survival Analysis And Competing Risks written by Martin J. Crowder and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-17 with Mathematics categories.
Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate
Theory Of Stochastic Objects
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Author : Athanasios Christou Micheas
language : en
Publisher: CRC Press
Release Date : 2018-01-19
Theory Of Stochastic Objects written by Athanasios Christou Micheas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-19 with Mathematics categories.
This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks; one would need material on real analysis, measure and probability theory, as well as stochastic processes - in addition to at least one text on statistics- to capture the detail and depth of material that has gone into this volume. Presents and illustrates ‘random objects’ in different contexts, under a unified framework, starting with rudimentary results on random variables and random sequences, all the way up to stochastic partial differential equations. Reviews rudimentary probability and introduces statistical inference, from basic to advanced, thus making the transition from basic statistical modeling and estimation to advanced topics more natural and concrete. Compact and comprehensive presentation of the material that will be useful to a reader from the mathematics and statistical sciences, at any stage of their career, either as a graduate student, an instructor, or an academician conducting research and requiring quick references and examples to classic topics. Includes 378 exercises, with the solutions manual available on the book's website. 121 illustrative examples of the concepts presented in the text (many including multiple items in a single example). The book is targeted towards students at the master’s and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary.
Statistical Methods For Spatial Data Analysis
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Author : Oliver Schabenberger
language : en
Publisher: CRC Press
Release Date : 2017-01-27
Statistical Methods For Spatial Data Analysis written by Oliver Schabenberger and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Computers categories.
Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.