Applied Linear Regression, 3rd Edition, Sanford Weisberg
Автор: Weisberg Sanford Название: Applied Linear Regression ISBN: 1118386086 ISBN-13(EAN): 9781118386088 Издательство: Wiley Цена: 11600 р. Наличие на складе: Нет в наличии. Описание: Providing a coherent set of basic methodology for applied linear regression without being encyclopedic, the fourth edition of Applied Linear Regression is thoroughly updated to help students master the theory and applications of linear regression modeling.
Автор: David W. Hosmer Jr.,Stanley Lemeshow,Rodney X. Stu Название: Applied Logistic Regression ISBN: 0470582472 ISBN-13(EAN): 9780470582473 Издательство: Wiley Рейтинг: Цена: 11391 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A new edition of the definitive guide to logistic regression modeling for health science and other applications Praise for the Second Edition ". . . an excellent book that balances many objectives well. . . . Applied Logistic Regression is an ideal
Автор: Lewis-Beck Michael S. Professor, Lewis-Beck Colin Название: Applied Regression: An Introduction ISBN: 1483381471 ISBN-13(EAN): 9781483381473 Издательство: Sage Publications Рейтинг: Цена: 2028 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Known for its readability and clarity, this Second Edition provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. The authors then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Описание: Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.
Автор: Kutner Название: Applied Linear Regression Models ISBN: 0071289356 ISBN-13(EAN): 9780071289351 Издательство: McGraw-Hill Рейтинг: Цена: 5642 р. Наличие на складе: Поставка под заказ.
Описание: A comprehensive and thoroughly up-to-date look at regression analys-still the most widely used technique in statistics today As basic to statistics as the Pythagorean theorem is to geometry, regression analysis is a statistical technique for investigating and modeling the relationship between variables. With far-reaching applications in almost every field, regression analysis is used in engineering, the physical and chemical sciences, economics, management, life and biological sciences, and the social sciences. Clearly balancing theory with applications, Introduction to Linear Regression Analysis describes conventional uses of the technique, as well as less common ones, placing linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. Succeeding chapters include detailed coverage of: * Indicator variables, making the connection between regression and analysis-of-variance modelss * Variable selection and model-building techniques * The multicollinearity problem, including its sources, harmful effects, diagnostics, and remedial measures * Robust regression techniques, including M-estimators, Least Median of Squares, and S-estimation * Generalized linear models The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation. Topics not usually found in a linear regression textbook, such as nonlinear regression and generalized linear models, yet critical to engineering students and professionals, have also been included. The new critical role of the computer in regression analysis is reflected in the book's expanded discussion of regression diagnostics, where major analytical procedures now available in contemporary software packages, such as SAS, Minitab, and S-Plus, are detailed. The Appendix now includes ample background material on the theory of linear models underlying regression analysis. Data sets from the book, extensive problem solutions, and software hints are available on the ftp site.
Описание: Since the late 1960s the logistic regression (LR) model has become the standard method for regression analysis of dichotomous data in many fields, especially in the health sciences. This text offers an introduction to the LR model and examines its use in methods for modelling.
Описание: The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
Автор: Draper, N.r. Smith, Harry Название: Applied regression analysis ISBN: 0471170828 ISBN-13(EAN): 9780471170822 Издательство: Wiley Рейтинг: Цена: 16616 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A major goal of scientific exploration is the discovery of relationships among variables. Regression is the analysis or measure of the relationship between a dependent variable and one or more independent variables. This text covers a commonly used statistical tool in constructing mathematical models from experimental data.
Описание: Providing an introduction to the logistic regression model, this work includes software packages for the analysis of data sets. It contains discussion, from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers through the use of modeling techniques for dichotomous data in diverse fields.
Автор: John Fox and Sanford Weisberg Название: An R Companion to Applied Regression ISBN: 141297514X ISBN-13(EAN): 9781412975148 Издательство: Sage Publications Рейтинг: Цена: 8795 р. Наличие на складе: Поставка под заказ.
Описание: The authors provide a step-by-step guide to using the high-quality free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, enhanced coverage of R graphics and programming, and substantial web-based support materials.
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