This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics. Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book. For a more complete understanding of mathematical statistics.

Introduction to Mathematical Statistics

Science & Math

Craig, Allen

Hogg, Robert V.

McKean, Joseph W.

Mathematics

Pearson

Introduction to Mathematical Statistics, Seventh Edition, offers a proven approach designed to provide you with an excellent foundation in mathematical statistics. Ample examples and exercises throughout the text illustrate concepts to help you gain a solid understanding of the material.

Introduction to Mathematical Statistics, Books a la Carte Edition (7th Edition)

Craig, Allen T.

Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science)

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures\nNonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm.\nThe book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data.\nThe book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.

Kloke, John

Routledge

Brunden, Marshall N., Vidmar, Thomas J., McKean, Joseph W.

Drug Interaction and Lethality Analysis

Brunden, Marshall N.

Vidmar, Thomas J.

Biological Sciences

Chapman and Hall/CRC

Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models. It follows the approach of the first edition by developing rank-based methods from the unifying theme of geometry. This edition, however, includes more models and methods and significantly extends the possible analyses based on ranks. New to the Second Edition <ul>
<li>A new section on rank procedures for nonlinear models</li> <li>A new chapter on models with dependent error structure, covering rank methods for mixed models, general estimating equations, and time series </li> <li>New material on the development of computationally efficient affine invariant/equivariant sign methods based on transform-retransform techniques in multivariate models</li> </ul> Taking a comprehensive, unified approach to statistical analysis, the book continues to describe one- and two-sample problems, the basic development of rank methods in the linear model, and fixed effects experimental designs. It also explores models with dependent error structure and multivariate models. The authors illustrate the implementation of the methods using many real-world examples and R. More information about the data sets and R packages can be found at www.crcpress.com

Robust Nonparametric Statistical Methods (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Hettmansperger, Thomas P.

CRC-Press

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.

See the best price to sell, buy, or rent books by McKean, Joseph W.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by McKean, Joseph W.

See the best price to sell, buy, or rent books by McKean, Joseph W.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Introduction to Mathematical Statistics

Introduction to Mathematical Statistics, Books a la Carte Edition (7th Edition)

Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science)

Drug Interaction and Lethality Analysis

Robust Nonparametric Statistical Methods (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science)