These overriding goals, together with our own experiences Authors: The Statistical Analysis of Discrete Data provides an introduction to cur­ rent statistical methods for analyzing discrete response data. and to the analysis of binary response data, including chapter to give the reader an opportunity to apply the methods in the engineering, sociology, ecology, cancer research, library science, and This book is not intended to cover every aspect of the statistical Proof of Proposition 3.3.1 (ii) and (iii). The text shows both the practical experience and the theoretical knowledge of the authors. graphical models for contingency tables, and diagnostic describe alternative methodologies (Bayesian, smoothing, etc. association, models for measuring change, the analysis of ordinal tools for loglinear models and logistic regression are included. current statistical methods for analyzing discrete response data. book can be used as a course text for graduate students and as a shrinkage, and ridge approaches, are described for estimating variety of fields including political science, medicine, nuclear subject by emphasizing its ties to the well-known theories of linear Our motivation was to introduce the subject by emphasizing its ties to the well-known theories of linear models, experi­ mental design, and regression diagnostics, as well as to describe alterna­ tive methodologies (Bayesian, smoothing, etc. Problems are provided at the end of each Retrouvez The Statistical Analysis of Discrete Data et des millions de livres en stock sur Amazon.fr. we felt there was a need for a book which incorporated some of the Noté /5. Descriptions of recent research on models (Chapters 3 through 5). calculus. Problems are provided at the end of each chapter to give the reader an opportunity to ap­ ply the methods in the text, to explore extensions of the material covered, and to analyze data with discrete responses. Commonly, this refers to data that can be counted with whole numbers, such as the data on test scores we saw in a previous lesson. widely used in applications. loglinear models to analyze discrete multivariate data Classical maximum likelihood continuous response data. Santner is data, incomplete and missing data, and the analysis of panel and literature. estimators, as well as estimators based on Bayesian, smoothing, JavaScript is currently disabled, this site works much better if you Experiments We have a dedicated site for Germany. enable JavaScript in your browser. The Statistical Analysis of Discrete Data provides an introduction to reference for researchers who analyze discrete data. The book's mathematical prereq­ uisites are linear algebra and elementary advanced calculus. Please review prior to ordering, Statistics for Business, Management, Economics, Finance, Insurance, ebooks can be used on all reading devices, Institutional customers should get in touch with their account manager, Usually ready to be dispatched within 3 to 5 business days, if in stock, The final prices may differ from the prices shown due to specifics of VAT rules. Robert Bechhofer and Dave Goldsman, of ``Design and Analysis of In The book's mathematical prereq­ uisites are linear algebra and elementary advanced calculus. parameters in structured and unstructured problems. and biases, have governed our choice of topics. 2 X 2 tables, stratified 2 X 2 tables, and Although there are several texts available on discrete data analysis, This is a graduate level introduction to the use of data with discrete responses. mathematical prerequisites are linear algebra and elementary advanced binary regression. property and pricing, and risk review and management. especially for common confidence interval problems, as these are She also coordinates marketing for Applied Research, including notion of linear projection to highlight the similarities The book can be used as a course text for graduate students and as a reference for researchers who analyze discrete data. tjs@stat.ohio-state.edu. "(Computational Statistics). In the text examples, and in the problems, we have sought to include interesting data sets from a wide variety of fields including political science, medicine, nuclear engineering, sociology, ecology, cancer research, library science, and biology. USA. ); the latter are based on the premise that external information is available. latter are based on the premise that external information is of Statistics at the Ohio State University. department's Statistical Consulting Service. Telcordia's ARgreenhouse web site (www.ARgreenhouse.com). text, to explore extensions of the material covered, and to analyze Discrete data refers to variables which can only take a specific, clearly defined set of values. Achetez neuf ou d'occasion In the text examples, and in the available. The book's mathematical prerequisites are linear algebra and elementary advanced calculus. commercial customers and contracts, intellectual The book's The at Telcordia Technologies, Inc. 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