Statistical Methods For Ranking Data
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Statistical Methods For Ranking Data
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Author : Mayer Alvo
language : en
Publisher: Springer
Release Date : 2014-09-02
Statistical Methods For Ranking Data written by Mayer Alvo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-02 with Mathematics categories.
This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.
Probability Models And Statistical Analyses For Ranking Data
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Author : Michael A. Fligner
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Probability Models And Statistical Analyses For Ranking Data written by Michael A. Fligner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
In June of 1990, a conference was held on Probablity Models and Statisti cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians. The conference took place at the University of Massachusetts, Amherst, and was attended by 36 participants, including statisticians, mathematicians, psychologists and sociologists from the United States, Canada, Israel, Italy, and The Nether lands. There were 18 presentations on a wide variety of topics involving ranking data. This volume is a collection of 14 of these presentations, as well as 5 miscellaneous papers that were contributed by conference participants. We would like to thank Carole Kohanski, summer program coordinator for the American Mathematical Society, for her assistance in arranging the conference; M. Steigerwald for preparing the manuscripts for publication; Martin Gilchrist at Springer-Verlag for editorial advice; and Persi Diaconis for contributing the Foreword. Special thanks go to the anonymous referees for their careful readings and constructive comments. Finally, we thank the National Science Foundation for their sponsorship of the AMS-IMS-SIAM Joint Summer Programs. Contents Preface vii Conference Participants xiii Foreword xvii 1 Ranking Models with Item Covariates 1 D. E. Critchlow and M. A. Fligner 1. 1 Introduction. . . . . . . . . . . . . . . 1 1. 2 Basic Ranking Models and Their Parameters 2 1. 3 Ranking Models with Covariates 8 1. 4 Estimation 9 1. 5 Example. 11 1. 6 Discussion. 14 1. 7 Appendix . 15 1. 8 References.
Analyzing And Modeling Rank Data
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Author : John I Marden
language : en
Publisher: CRC Press
Release Date : 2014-01-23
Analyzing And Modeling Rank Data written by John I Marden and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-23 with Mathematics categories.
This book is the first single source volume to fully address this prevalent practice in both its analytical and modeling aspects. The information discussed presents the use of data consisting of rankings in such diverse fields as psychology, animal science, educational testing, sociology, economics, and biology. This book systematically presents th
Statistical Methods For Machine Learning
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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2018-05-30
Statistical Methods For Machine Learning written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Computers categories.
Statistics is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in statistics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of statistical methods to machine learning, summary stats, hypothesis testing, nonparametric stats, resampling methods, and much more.
Statistical Methods For Food Science
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Author : John A. Bower
language : en
Publisher: John Wiley & Sons
Release Date : 2009-11-09
Statistical Methods For Food Science written by John A. Bower and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-11-09 with Technology & Engineering categories.
The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing – there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This book provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a ‘hands on’ approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level.
Statistics In Medicine
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Author : Robert H. Riffenburgh
language : en
Publisher: Elsevier
Release Date : 2011-08-29
Statistics In Medicine written by Robert H. Riffenburgh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-29 with Mathematics categories.
Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context. - Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises - Two-part design features course material and a professional reference section - Chapter summaries provide a review of formulas, method algorithms, and check lists - Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods New in this Edition: - New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods - New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions - Updated database coverage and additional exercises - Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression - Thorough discussion on required sample size
Statistical Methods In Psychiatry And Related Fields
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Author : Ralitza Gueorguieva
language : en
Publisher: CRC Press
Release Date : 2017-11-20
Statistical Methods In Psychiatry And Related Fields written by Ralitza Gueorguieva and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-20 with Mathematics categories.
Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. Features Provides an overview of intermediate to advanced statistical methods applied to psychiatry. Takes a non-technical approach with mathematical details kept to a minimum. Includes lots of detailed examples from published studies in psychiatry and related fields. Software programs, data sets and output are available on a supplementary website. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data. Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health. She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.
Elementary Statistical Methods
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Author : G. Barrie Wetherill
language : en
Publisher: Springer
Release Date : 2013-11-11
Elementary Statistical Methods written by G. Barrie Wetherill and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.
This book is mainly based on lectures given by Professor D. R. Cox and myself at Birkbeck College over a period of eight to nine years. It began as a joint venture, but pressure of other work made it necessary for Professor Cox to withdraw early on. I have throughout received much valuable advice and encouragement from Professor Cox, but of course, I am solely responsible for the text, and any errors remaining in it. The book is intended as a first course on statistical methods, and there is a liberal supply of exercises. Although the mathematical level of the book is low, I have tried to explain carefully the logical reasoning behind the use of the methods discussed. Some of the exercises which require more difficult mathematics are marked with an asterisk, and these may be omitted. In this way, I hope that the book will satisfy the needs for a course on statistical methods at a range of mathematical levels. It is essential for the reader to work through the numerical exercises, for only in this way can he grasp the full meaning and usefulness of the statistical techniques, and gain practice in the interpretation of the results. Chapters 7 and 8 discuss methods appropriate for use on ranked or discrete data, and Chapters 9-12 do not depend on these chapters. Chapters 7 and 8 may therefore be omitted, if desired.
Elementary Statistical Methods
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Author : G. Wetherill
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Elementary Statistical Methods written by G. Wetherill and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Social Science categories.
This book is mainly based on lectures given by Professor D. R. Cox and myself at Birkbeck College over a period of eight to nine years. It began as a. joint venture, but pressure of other work made it necessary for Professor Cox to withdraw early on. I have throughout received much valuable advice and encouragement from Professor Cox, but of course, I am solely responsible for the text, and any errors remaining in it. The book is intended as a first course on statistical methods, and there is a liberal supply of exercises. Although the mathematical level of the book is low, I have tried to explain carefully the logical reasoning behind the use of the methods discussed. Some of the exercises which require more difficult mathematics are marked with an asterisk, and these may be omitted. In this way, I hope that the book will satisfy the needs for a course on statistical methods at a range of mathematical levels. It is essential for the reader to work through the numerical exercises, for only in this way can he grasp the full meaning and usefulness of the statistical techniques, and gain practice in the interpretation of the results. Chapters 7 and 8 discuss methods appropriate for use on ranked or discrete data, and Chapters 9-12 do not depend on these chapters. Chapters 7 and 8 may therefore be omitted, if desired.
Breakthroughs In Statistics
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Author : Samuel Kotz
language : en
Publisher: Springer Science & Business Media
Release Date : 1992
Breakthroughs In Statistics written by Samuel Kotz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.
This is author-approved bcc: This is the third volume of a collection of seminal papers in the statistical science written during the past 110 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Volume III concertrates on articles from the 1980's while including some earlier articles not included in Volumes I and II. Samuel Kotz is Professor of Statistics in the College of Business and Management at the University of Maryland. Norman L. Johnson is Professor Emeritus of Statistics at the University of North Carolina. Also available: Breakthroughs in Statistics Volume I: Foundations and Basic Theory Samuel Kotz and Norman L. Johnson, Editors 1993. 631 pp. Softcover. ISBN 0-387-94037-5 Breakthroughs in Statistics Volume II: Methodology and Distribution Samuel Kotz and Norman L. Johnson, Editors 1993. 600 pp. Softcover. ISBN 0-387-94039-1