Applied Regression Analysis and Other Multivariable Methods PDF Download
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Author: Kleinbaum
Publisher:
ISBN: 9780534915247
Category :
Languages : en
Pages :
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Book Description
Author: Kleinbaum
Publisher:
ISBN: 9780534915247
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: David G. Kleinbaum
Publisher: Duxbury Resource Center
ISBN:
Category : Mathematics
Languages : en
Pages : 748
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Book Description
* An introductory text for undergraduates, graduates, and working professionals; emphasizes applications in public health, biology, and the social and behavioral sciences.
Author: Richard J. Brook
Publisher: Routledge
ISBN: 1351465880
Category : Mathematics
Languages : en
Pages : 148
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Book Description
For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems. Stressing principles while keeping computational and theoretical details at a manageable level, Applied Regression Analysis and Experimental Design features an emphasis on vector geometry and least squares to unify and provide an intuitive basis for most topics covered... abundant examples and exercises using real-life data sets clearly illustrating practical of data analysis...essential exposure to MINITAB and GENSTAT computer packages , including computer printouts...and important background material such as vector and matrix properties and the distributional properties of quadratic forms. Designed to make theory work for students, this clearly written, easy-to-understand work serves as the ideal texts for courses Regression, Experimental Design, and Linear Models in a broad range of disciplines. Moreover, applied statisticians will find the book a useful reference for the general application of the linear model.
Author: Norman R. Draper
Publisher: John Wiley & Sons
ISBN: 1118625684
Category : Mathematics
Languages : en
Pages : 736
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Book Description
An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts and applications, offers a complete, easily accessible introduction to the fundamentals of regression analysis. Assuming only a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear and nonlinear regression models, using small and large data sets, with pocket calculators or computers. This Third Edition features separate chapters on multicollinearity, generalized linear models, mixture ingredients, geometry of regression, robust regression, and resampling procedures. Extensive support materials include sets of carefully designed exercises with full or partial solutions and a series of true/false questions with answers. All data sets used in both the text and the exercises can be found on the companion disk at the back of the book. For analysts, researchers, and students in university, industrial, and government courses on regression, this text is an excellent introduction to the subject and an efficient means of learning how to use a valuable analytical tool. It will also prove an invaluable reference resource for applied scientists and statisticians.
Author: Mitchell H. Katz
Publisher: Cambridge University Press
ISBN: 9780521549851
Category : Mathematics
Languages : en
Pages : 228
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Book Description
How to perform and interpret multivariable analysis, using plain language rather than complex derivations.
Author: Michael H. Kutner
Publisher: McGraw-Hill/Irwin
ISBN: 9780072386882
Category : Mathematics
Languages : en
Pages : 1396
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Book Description
Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Author: Stuart R. Stock
Publisher: CRC Press
ISBN: 1420058770
Category : Technology & Engineering
Languages : en
Pages : 366
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Book Description
Due to the availability of commercial laboratory systems and the emergence of user facilities at synchrotron radiation sources, studies of microcomputed tomography or microCT have increased exponentially. MicroComputed Technology provides a complete introduction to the technology, describing how to use it effectively and understand its results. The first part of the book focuses on methodology, covering experimental methods, data analysis, and visualization approaches. The second part addresses various microCT applications, including porous solids, microstructural evolution, soft tissue studies, multimode studies, and indirect analyses. The author presents a sufficient amount of fundamental material so that those new to the field can develop a relative understanding of how to design their own microCT studies. One of the first full-length references dedicated to microCT, this book provides an accessible introduction to field, supplemented with application examples and color images.
Author: David W. Hosmer, Jr.
Publisher: John Wiley & Sons
ISBN: 0471654027
Category : Mathematics
Languages : en
Pages : 397
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Book Description
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.
Author: John Fox
Publisher: SAGE Publications
ISBN: 1483321312
Category : Social Science
Languages : en
Pages : 612
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Book Description
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. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.
Author: Alan J. Izenman
Publisher: Springer Science & Business Media
ISBN: 0387781897
Category : Mathematics
Languages : en
Pages : 757
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Book Description
This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.
