The Collected Works of John W. Tukey: Multiple comparisons, 1948-1983
Author | : John Wilder Tukey |
Publisher | : |
Total Pages | : |
Release | : 1984 |
Genre | : Mathematical statistics |
ISBN | : 9780534033033 |
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Author | : John Wilder Tukey |
Publisher | : |
Total Pages | : |
Release | : 1984 |
Genre | : Mathematical statistics |
ISBN | : 9780534033033 |
Author | : John Wilder Tukey |
Publisher | : Elsevier |
Total Pages | : 550 |
Release | : 1994-05-15 |
Genre | : Mathematics |
ISBN | : 9780412051210 |
This volume of eleven articles compiles important papers by Tukey that examine the intriguing problems inherent in the area of multiple comparisons and provide a useful framework for thinking about them. Each volume in the set is indexed and contains a bibliography.
Author | : John A. Schinka |
Publisher | : John Wiley & Sons |
Total Pages | : 737 |
Release | : 2003-03-19 |
Genre | : Psychology |
ISBN | : 0471264431 |
Includes established theories and cutting-edge developments. Presents the work of an international group of experts. Presents the nature, origin, implications, an future course of major unresolved issues in the area.
Author | : David R. Brillinger |
Publisher | : Princeton University Press |
Total Pages | : 352 |
Release | : 2014-07-14 |
Genre | : Mathematics |
ISBN | : 1400851602 |
This collection of essays brings together many of the world's most distinguished statisticians to discuss a wide array of the most important recent developments in data analysis. The book honors John W. Tukey, one of the most influential statisticians of the twentieth century, on the occasion of his eightieth birthday. Contributors, some of them Tukey's former students, use his general theoretical work and his specific contributions to Exploratory Data Analysis as the point of departure for their papers. They cover topics from "pure" data analysis, such as gaussianizing transformations and regression estimates, and from "applied" subjects, such as the best way to rank the abilities of chess players or to estimate the abundance of birds in a particular area. Tukey may be best known for coining the common computer term "bit," for binary digit, but his broader work has revolutionized the way statisticians think about and analyze sets of data. In a personal interview that opens the book, he reviews these extraordinary contributions and his life with characteristic modesty, humor, and intelligence. The book will be valuable both to researchers and students interested in current theoretical and practical data analysis and as a testament to Tukey's lasting influence. The essays are by Dhammika Amaratunga, David Andrews, David Brillinger, Christopher Field, Leo Goodman, Frank Hampel, John Hartigan, Peter Huber, Mia Hubert, Clifford Hurvich, Karen Kafadar, Colin Mallows, Stephan Morgenthaler, Frederick Mosteller, Ha Nguyen, Elvezio Ronchetti, Peter Rousseeuw, Allan Seheult, Paul Velleman, Maria-Pia Victoria-Feser, and Alessandro Villa. Originally published in 1998. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Author | : John E. Kolassa |
Publisher | : CRC Press |
Total Pages | : 225 |
Release | : 2020-09-28 |
Genre | : Mathematics |
ISBN | : 0429511361 |
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 is paid to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included. Features Rank-based techniques including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, elementary probability, and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra.
Author | : H. Leon Harter |
Publisher | : CRC Press |
Total Pages | : 696 |
Release | : 1997-10-27 |
Genre | : Mathematics |
ISBN | : 9780849331145 |
A companion volume to the authors' previous well-received work, the CRC Handbook of Tables for the Use of Order Statistics in Estimation, this handbook discusses testing whether a hypothesis is true or false. Together, these volumes are your complete reference to theory and important tables relating to order statistics and their applications. Once a researcher completes an experiment, the resulting data is assumed to have come from a normal distribution with its mean and variance unknown. The researcher is then presented with a hypothesis testing problem. The use of order statistics and related functions offers a simple, powerful, and interesting approach to solving this problem. This volume presents an introduction to the use of order statistics and explains the various problems and their applications. The role of order statistics in solving these problems is examined, several important statistics are introduced, and their use in addressing testing of hypothesis problems is highlighted. The book also includes numerous tables that facilitate the methods of hypothesis testing using order statistics. Examples are given of the use of these tables in multiple comparison tests, with attention to error rates and sample sizes, and in the analog range of analysis of variance.
Author | : Torsten Hothorn |
Publisher | : CRC Press |
Total Pages | : 454 |
Release | : 2014-06-25 |
Genre | : Mathematics |
ISBN | : 1482204584 |
Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.
Author | : Irving B. Weiner |
Publisher | : John Wiley & Sons |
Total Pages | : 744 |
Release | : 2003-01-03 |
Genre | : Medical |
ISBN | : 9780471385134 |
Includes established theories and cutting-edge developments. Presents the work of an international group of experts. Presents the nature, origin, implications, an future course of major unresolved issues in the area.
Author | : Torsten Hothorn |
Publisher | : CRC Press |
Total Pages | : 298 |
Release | : 2006-02-17 |
Genre | : Mathematics |
ISBN | : 1420010654 |
R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-P
Author | : Torsten Hothorn |
Publisher | : CRC Press |
Total Pages | : 383 |
Release | : 2009-07-20 |
Genre | : Mathematics |
ISBN | : 1420079336 |
A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.