A Primer of Permutation Statistical Methods PDF Download
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Author: Kenneth J. Berry
Publisher: Springer
ISBN: 3030209334
Category : Mathematics
Languages : en
Pages : 488
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Book Description
The primary purpose of this textbook is to introduce the reader to a wide variety of elementary permutation statistical methods. Permutation methods are optimal for small data sets and non-random samples, and are free of distributional assumptions. The book follows the conventional structure of most introductory books on statistical methods, and features chapters on central tendency and variability, one-sample tests, two-sample tests, matched-pairs tests, one-way fully-randomized analysis of variance, one-way randomized-blocks analysis of variance, simple regression and correlation, and the analysis of contingency tables. In addition, it introduces and describes a comparatively new permutation-based, chance-corrected measure of effect size. Because permutation tests and measures are distribution-free, do not assume normality, and do not rely on squared deviations among sample values, they are currently being applied in a wide variety of disciplines. This book presents permutation alternatives to existing classical statistics, and is intended as a textbook for undergraduate statistics courses or graduate courses in the natural, social, and physical sciences, while assuming only an elementary grasp of statistics.
Author: Kenneth J. Berry
Publisher: Springer
ISBN: 3030209334
Category : Mathematics
Languages : en
Pages : 488
Get Book Here
Book Description
The primary purpose of this textbook is to introduce the reader to a wide variety of elementary permutation statistical methods. Permutation methods are optimal for small data sets and non-random samples, and are free of distributional assumptions. The book follows the conventional structure of most introductory books on statistical methods, and features chapters on central tendency and variability, one-sample tests, two-sample tests, matched-pairs tests, one-way fully-randomized analysis of variance, one-way randomized-blocks analysis of variance, simple regression and correlation, and the analysis of contingency tables. In addition, it introduces and describes a comparatively new permutation-based, chance-corrected measure of effect size. Because permutation tests and measures are distribution-free, do not assume normality, and do not rely on squared deviations among sample values, they are currently being applied in a wide variety of disciplines. This book presents permutation alternatives to existing classical statistics, and is intended as a textbook for undergraduate statistics courses or graduate courses in the natural, social, and physical sciences, while assuming only an elementary grasp of statistics.
Author: Kenneth J. Berry
Publisher: Springer
ISBN: 3319287702
Category : Mathematics
Languages : en
Pages : 634
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Book Description
This research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size. Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research. lly-informed="" audience,="" and="" can="" also="" easily="" serve="" as="" textbook="" in="" graduate="" course="" departments="" such="" statistics,="" psychology,="" or="" biology.="" particular,="" the="" audience="" for="" book="" is="" teachers="" of="" practicing="" statisticians,="" applied="" quantitative="" students="" fields="" medical="" research,="" epidemiology,="" public="" health,="" biology.
Author: Kenneth J. Berry
Publisher: Springer Nature
ISBN: 3030743616
Category : Mathematics
Languages : en
Pages : 677
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Book Description
This book takes a unique approach to explaining permutation statistics by integrating permutation statistical methods with a wide range of classical statistical methods and associated R programs. It opens by comparing and contrasting two models of statistical inference: the classical population model espoused by J. Neyman and E.S. Pearson and the permutation model first introduced by R.A. Fisher and E.J.G. Pitman. Numerous comparisons of permutation and classical statistical methods are presented, supplemented with a variety of R scripts for ease of computation. The text follows the general outline of an introductory textbook in statistics with chapters on central tendency and variability, one-sample tests, two-sample tests, matched-pairs tests, completely-randomized analysis of variance, randomized-blocks analysis of variance, simple linear regression and correlation, and the analysis of goodness of fit and contingency. Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity, depend only on the observed data, and do not require random sampling. The methods are relatively new in that it took modern computing power to make them available to those working in mainstream research. Designed for an audience with a limited statistical background, the book can easily serve as a textbook for undergraduate or graduate courses in statistics, psychology, economics, political science or biology. No statistical training beyond a first course in statistics is required, but some knowledge of, or some interest in, the R programming language is assumed.
Author: Kenneth J. Berry
Publisher: Springer Nature
ISBN: 3031418964
Category : Mathematics
Languages : en
Pages : 795
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Book Description
The primary purpose of this book is to introduce the reader to a wide variety of interesting and useful connections, relationships, and equivalencies between and among conventional and permutation statistical methods. There are approximately 320 statistical connections and relationships described in this book. For each connection or connections the tests are described, the connection is explained, and an example analysis illustrates both the tests and the connection(s). The emphasis is more on demonstrations than on proofs, so little mathematical expertise is assumed. While the book is intended as a stand-alone monograph, it can also be used as a supplement to a standard textbook such as might be used in a second- or third-term course in conventional statistical methods. Students, faculty, and researchers in the social, natural, or hard sciences will find an interesting collection of statistical connections and relationships - some well-known, some more obscure, and some presented here for the first time.
Author: Darrin Speegle
Publisher: CRC Press
ISBN: 1000504514
Category : Business & Economics
Languages : en
Pages : 644
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Book Description
This book is a fresh approach to a calculus based, first course in probability and statistics, using R throughout to give a central role to data and simulation. The book introduces probability with Monte Carlo simulation as an essential tool. Simulation makes challenging probability questions quickly accessible and easily understandable. Mathematical approaches are included, using calculus when appropriate, but are always connected to experimental computations. Using R and simulation gives a nuanced understanding of statistical inference. The impact of departure from assumptions in statistical tests is emphasized, quantified using simulations, and demonstrated with real data. The book compares parametric and non-parametric methods through simulation, allowing for a thorough investigation of testing error and power. The text builds R skills from the outset, allowing modern methods of resampling and cross validation to be introduced along with traditional statistical techniques. Fifty-two data sets are included in the complementary R package fosdata. Most of these data sets are from recently published papers, so that you are working with current, real data, which is often large and messy. Two central chapters use powerful tidyverse tools (dplyr, ggplot2, tidyr, stringr) to wrangle data and produce meaningful visualizations. Preliminary versions of the book have been used for five semesters at Saint Louis University, and the majority of the more than 400 exercises have been classroom tested.
Author: Felix Bärlocher
Publisher: Springer Nature
ISBN: 3030305155
Category : Science
Languages : en
Pages : 581
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Book Description
The primary objective of this book is to provide students and laboratory instructors at universities and professional ecologists with a broad range of established methods to study plant litter decomposition. Detailed protocols for direct use in the field or laboratory are presented in an easy to follow step-by-step format. A short introduction to each protocol reviews the ecological significance and principles of the technique and points to key references.
Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 1000080544
Category : Mathematics
Languages : en
Pages : 256
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Book Description
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization, bootstrapping, and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications, with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression, and Bayesian methods Makes it easy for biologists, researchers, and students to understand the methods used Provides information about computer programs and packages to implement calculations, particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style, with minimal coverage of theoretical details, this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students, as well as a reference for researchers from a range of disciplines. The detailed, worked examples of real applications will enable practitioners to apply the methods to their own biological data.
Author: Mark Stemmler
Publisher: Springer Nature
ISBN: 3031563182
Category :
Languages : en
Pages : 785
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Book Description
Author: Chris Taylor
Publisher: Springer Science & Business Media
ISBN: 3540405607
Category : Computers
Languages : en
Pages : 714
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Book Description
This book constitutes the refeered proceedings of the 18th Interational Conference on Information Processing in Medical Imaging, IPMI 2003, held in UK, in July 2003. The 57 revised full papers presented were carefully reviewed and selected from submissions. The papers are organized in topical sections shape modeling, shape analysis, segmentation, color, performance characterization, registration and modeling similarity, registration and modeling deformation, cardiac motion, fMRI analysis, and diffusion imaging and tractography.
Author: Paul W. Mielke
Publisher: Springer Science & Business Media
ISBN: 0387698132
Category : Mathematics
Languages : en
Pages : 449
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Book Description
This is the second edition of the comprehensive treatment of statistical inference using permutation techniques. It makes available to practitioners a variety of useful and powerful data analytic tools that rely on very few distributional assumptions. Although many of these procedures have appeared in journal articles, they are not readily available to practitioners. This new and updated edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses.
