Applied Regression Analysis

Author: Norman R. Draper,Harry Smith

Publisher: John Wiley & Sons

ISBN: 1118625684

Category: Mathematics

Page: 736

View: 4167

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.
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Applied Regression Analysis and Generalized Linear Models

Author: John Fox

Publisher: SAGE Publications

ISBN: 1483321312

Category: Social Science

Page: 816

View: 6018

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.
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Applied Regression Analysis

A Research Tool

Author: John O. Rawlings,Sastry G. Pantula,David A. Dickey

Publisher: Springer Science & Business Media

ISBN: 0387227539

Category: Mathematics

Page: 660

View: 5881

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course. Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.
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Applied Regression Analysis, Linear Models, and Related Methods

Author: John Fox

Publisher: SAGE

ISBN: 9780803945401

Category: Social Science

Page: 597

View: 7714

An accessible, detailed, and up-to-date treatment of regression analysis, linear models, and closely related methods is provided in this book. Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear
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Applied Regression Analysis and Other Multivariable Methods

Author: David Kleinbaum,Lawrence Kupper,Azhar Nizam,Keith Muller

Publisher: Cengage Learning

ISBN: 111180270X

Category: Mathematics

Page: 928

View: 5912

This bestseller is known for its modern, practical approach to regression-analysis methods that students will find applicable to real-life problems. APPLIED REGRESSION ANALYSIS AND MULTIVARIABLE METHODS highlights the role of the computer in contemporary statistics with numerous printouts and exercises that can be solved with the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
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Applied Regression Analysis

A Second Course in Business and Economic Statistics

Author: Terry E. Dielman

Publisher: South-Western Pub

ISBN: 9780534465483

Category: Mathematics

Page: 496

View: 3148

APPLIED REGRESSION ANALYSIS applies regression to real data and examples while employing commercial statistical and spreadsheet software. Covering the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis, the text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets.
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Applied Regression Analysis for Business and Economics

Author: Terry E. Dielman

Publisher: Duxbury Resource Center

ISBN: 9780534265861

Category: Analyse de régression

Page: 575

View: 1636

This book's use of real data in examples and exercises helps students gain practical insights into regression and forecasting concepts. It is intended for the regression analysis course for students of business and economics or as a second course in business statistics found in schools of business or in departments of statistics and economics. (Prerequisites: college algebra and introductory business statistics.) The author includes: -- Use of the computer as the primary method of analysis with a focus on the interpretation of regression output -- Integration of cross-sectional models with time-series models throughout -- A data disk containing relevant data from examples and exercises, formatted for major statistical packages -- Many exercises that require interpretation and build on previously learned concepts -- Instructions for both Minitab RM (Release 10 for Windows RM) and SAS in new Using the Computer sections in each chapter -- An introduction to discriminant analysis and logistic regression in Chapter 9 (Qualitative Dependent Variables) -- A separate chapter covering analysis of variance topics to allow flexibility of coverage -- Data sets with real data from journals and actual business settings
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Applied Regression Analysis and Experimental Design

Author: Brook

Publisher: CRC Press

ISBN: 9780824772529

Category: Mathematics

Page: 256

View: 9641

For a solid foundation of important statistical methods, this 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 of 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 problems 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 text for courses in Regression, Experimental Design, and Linear Models in a broad range of disciplines. Moreover, applied statisticians, biometricians, and research workers in applied statistics will find the book a useful reference for the general application of the linear model. Book jacket.
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Applied Regression Modeling

Author: Iain Pardoe

Publisher: John Wiley & Sons

ISBN: 1118345045

Category: Mathematics

Page: 346

View: 9076

Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
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Applied Regression Analysis for Business

Tools, Traps and Applications

Author: Jacek Welc,Pedro J. Rodriguez Esquerdo

Publisher: Springer

ISBN: 3319711563

Category: Business & Economics

Page: 286

View: 8488

This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.
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Applied Regression Analysis in Econometrics

Author: Howard E. Doran

Publisher: CRC Press

ISBN: 9780824780494

Category: Technology & Engineering

Page: 392

View: 4588

A textbook for a one-semester course for advanced undergraduate and graduate students in economics. Covers regression techniques in the context of single equation econometric models, featuring MINITAB and SHAZAM software examples for attacking real-world problems. Annotation copyright Book News, Inc
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An R Companion to Applied Regression

Author: John Fox,Sanford Weisberg

Publisher: SAGE Publications

ISBN: 141297514X

Category: Social Science

Page: 449

View: 8368

This book aims to provide a broad introduction to the R statistical environment in the context of applied regression analysis, which is typically studied by social scientists and others in a second course in applied statistics.
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Applied Regression Analysis and Other Multivariable Methods

Author: David G. Kleinbaum,Lawrence L. Kupper,Azhar Nizam,Eli S. Rosenberg

Publisher: Cengage Learning

ISBN: 128596375X

Category: Mathematics

Page: 1072

View: 2542

This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques. Available with InfoTrac Student Collections http://gocengage.com/infotrac. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
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Student Solutions Manual for Kleinbaum's Applied Regression Analysis and Other Multivariable Methods, 5th

Author: David G. Kleinbaum,Lawrence L. Kupper,Azhar Nizam,Eli S. Rosenberg

Publisher: Cengage Learning

ISBN: 1305848535

Category: Mathematics

Page: 156

View: 8306

The SSM features worked solutions to select problems in Applied Regression Analysis and Other Multivariable Methods, 5. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
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Primer of Applied Regression & Analysis of Variance, Third Edition

Author: Stanton A. Glantz,Bryan K. Slinker,Torsten B. Neilands

Publisher: McGraw Hill Professional

ISBN: 0071822445

Category: Medical

Page: 992

View: 4614

A textbook on the use of advanced statistical methods in healthcare sciences Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods. The book has been acclaimed for its user-friendly style that makes complicated material understandable to readers who do not have an extensive math background. The text is packed with learning aids that include chapter-ending summaries and end-of-chapter problems that quickly assess mastery of the material. Examples from biological and health sciences are included to clarify and illustrate key points. The techniques discussed apply to a wide range of disciplines, including social and behavioral science as well as health and life sciences. Typical courses that would use this text include those that cover multiple linear regression and ANOVA. Four completely new chapters Completely updated software information and examples
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An R and S-Plus Companion to Applied Regression

Author: John Fox

Publisher: SAGE

ISBN: 9780761922803

Category: Mathematics

Page: 312

View: 3076

"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. " —JEFF GILL, University of Florida, Gainesville
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Applied Logistic Regression Analysis

Author: Scott Menard

Publisher: SAGE

ISBN: 9780761922087

Category: Mathematics

Page: 111

View: 2547

The focus in this Second Editionis on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS included. New to this edition: · More detailed consideration of grouped as opposed to casewise data throughout the book · Updated discussion of the properties and appropriate use of goodness of fit measures, R2 analogues, and indices of predictive efficiency · Discussion of the misuse of odds ratios to represent risk ratios, and of overdispersion and underdispersion for grouped data · Updated coverage of unordered and ordered polytomous logistic regression models.
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Applied Regression Analysis and Multivariable Methods

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1467285781

Category: Education

Page: 61

View: 7373

Facts101 is your complete guide to Applied Regression Analysis and Multivariable Methods. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.
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