Primer Of Applied Regression Analysis Of Variance

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Primer of Applied Regression & Analysis of Variance 3E

Author : Stanton A. Glantz
Publisher : McGraw Hill Professional
ISBN 13 : 0071822445
Total Pages : 1212 pages
Book Rating : 4.0/5 (718 download)

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Book Synopsis Primer of Applied Regression & Analysis of Variance 3E by : Stanton A. Glantz

Download or read book Primer of Applied Regression & Analysis of Variance 3E written by Stanton A. Glantz and published by McGraw Hill Professional. This book was released on 2016-02-22 with total page 1212 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Primer of Applied Regression & Analysis of Variance

Author : Stanton A. Glantz
Publisher : McGraw Hill Professional
ISBN 13 : 0071811834
Total Pages : 980 pages
Book Rating : 4.0/5 (718 download)

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Book Synopsis Primer of Applied Regression & Analysis of Variance by : Stanton A. Glantz

Download or read book Primer of Applied Regression & Analysis of Variance written by Stanton A. Glantz and published by McGraw Hill Professional. This book was released on 2012-09-01 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applicable for all statistics courses or practical use, teaches how to understand more advanced multivariate statistical methods, as well as how to use available software packages to get correct results. Study problems and examples culled from biomedical research illustrate key points. New to this edition: broadened coverage of ANOVA (traditional analysis of variance), the addition of ANCOVA (analysis of Co-Variance); updated treatment of available statistics software; 2 new chapters (Analysis of Variance Extensions and Mixing Regression and ANOVA: ANCOVA).

Primer of Regression and Analysis of Variance

Author : S. A. Glantz
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (646 download)

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Book Synopsis Primer of Regression and Analysis of Variance by : S. A. Glantz

Download or read book Primer of Regression and Analysis of Variance written by S. A. Glantz and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Regression, ANOVA, and the General Linear Model

Author : Peter Vik
Publisher : SAGE Publications
ISBN 13 : 1483310337
Total Pages : 345 pages
Book Rating : 4.4/5 (833 download)

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Book Synopsis Regression, ANOVA, and the General Linear Model by : Peter Vik

Download or read book Regression, ANOVA, and the General Linear Model written by Peter Vik and published by SAGE Publications. This book was released on 2013-01-14 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Peter Vik's Regression, ANOVA, and the General Linear Model: A Statistics Primer demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use. The two perspectives are (1) a traditional focus on the t-test, correlation, and ANOVA, and (2) a model-comparison approach using General Linear Models (GLM). This book juxtaposes the two approaches by presenting a traditional approach in one chapter, followed by the same analysis demonstrated using GLM. By so doing, students will acquire a theoretical and conceptual appreciation for data analysis as well as an applied practical understanding as to how these two approaches are alike.

Analysis of Variance, Design, and Regression

Author : Ronald Christensen
Publisher : CRC Press
ISBN 13 : 9780412062919
Total Pages : 608 pages
Book Rating : 4.0/5 (629 download)

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Book Synopsis Analysis of Variance, Design, and Regression by : Ronald Christensen

Download or read book Analysis of Variance, Design, and Regression written by Ronald Christensen and published by CRC Press. This book was released on 1996-06-01 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents a comprehensive treatment of basic statistical methods and their applications. It focuses on the analysis of variance and regression, but also addressing basic ideas in experimental design and count data. The book has four connecting themes: similarity of inferential procedures, balanced one-way analysis of variance, comparison of models, and checking assumptions. Most inferential procedures are based on identifying a scalar parameter of interest, estimating that parameter, obtaining the standard error of the estimate, and identifying the appropriate reference distribution. Given these items, the inferential procedures are identical for various parameters. Balanced one-way analysis of variance has a simple, intuitive interpretation in terms of comparing the sample variance of the group means with the mean of the sample variance for each group. All balanced analysis of variance problems are considered in terms of computing sample variances for various group means. Comparing different models provides a structure for examining both balanced and unbalanced analysis of variance problems and regression problems. Checking assumptions is presented as a crucial part of every statistical analysis. Examples using real data from a wide variety of fields are used to motivate theory. Christensen consistently examines residual plots and presents alternative analyses using different transformation and case deletions. Detailed examination of interactions, three factor analysis of variance, and a split-plot design with four factors are included. The numerous exercises emphasize analysis of real data. Senior undergraduate and graduate students in statistics and graduate students in other disciplines using analysis of variance, design of experiments, or regression analysis will find this book useful.

Applied Regression Analysis

Author : John O. Rawlings
Publisher : Springer Science & Business Media
ISBN 13 : 0387227539
Total Pages : 660 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Applied Regression Analysis by : John O. Rawlings

Download or read book Applied Regression Analysis written by John O. Rawlings and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Regression, ANOVA, and the General Linear Model

Author : Peter Vik
Publisher : SAGE Publications
ISBN 13 : 1483316017
Total Pages : 344 pages
Book Rating : 4.4/5 (833 download)

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Book Synopsis Regression, ANOVA, and the General Linear Model by : Peter Vik

Download or read book Regression, ANOVA, and the General Linear Model written by Peter Vik and published by SAGE Publications. This book was released on 2013-01-14 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Peter Vik's Regression, ANOVA, and the General Linear Model: A Statistics Primer demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use. The two perspectives are (1) a traditional focus on the t-test, correlation, and ANOVA, and (2) a model-comparison approach using General Linear Models (GLM). This book juxtaposes the two approaches by presenting a traditional approach in one chapter, followed by the same analysis demonstrated using GLM. By so doing, students will acquire a theoretical and conceptual appreciation for data analysis as well as an applied practical understanding as to how these two approaches are alike.

Applied Linear Regression

Author : Sanford Weisberg
Publisher : John Wiley & Sons
ISBN 13 : 1118625951
Total Pages : 266 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Applied Linear Regression by : Sanford Weisberg

Download or read book Applied Linear Regression written by Sanford Weisberg and published by John Wiley & Sons. This book was released on 2013-06-07 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master linear regression techniques with a new edition of a classic text Reviews of the Second Edition: "I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression." —Technometrics, February 1987 "Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis." —American Scientist, May–June 1987 Applied Linear Regression, Third Edition has been thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, the Third Edition stresses the use of graphical methods in an effort to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. The Third Edition incorporates new material reflecting the latest advances, including: Use of smoothers to summarize a scatterplot Box-Cox and graphical methods for selecting transformations Use of the delta method for inference about complex combinations of parameters Computationally intensive methods and simulation, including the bootstrap method Expanded chapters on nonlinear and logistic regression Completely revised chapters on multiple regression, diagnostics, and generalizations of regression Readers will also find helpful pedagogical tools and learning aids, including: More than 100 exercises, most based on interesting real-world data Web primers demonstrating how to use standard statistical packages, including R, S-Plus®, SPSS®, SAS®, and JMP®, to work all the examples and exercises in the text A free online library for R and S-Plus that makes the methods discussed in the book easy to use With its focus on graphical methods and analysis, coupled with many practical examples and exercises, this is an excellent textbook for upper-level undergraduates and graduate students, who will quickly learn how to use linear regression analysis techniques to solve and gain insight into real-life problems.

Applied Regression Analysis

Author : Norman R. Draper
Publisher : John Wiley & Sons
ISBN 13 : 1118625684
Total Pages : 736 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Applied Regression Analysis by : Norman R. Draper

Download or read book Applied Regression Analysis written by Norman R. Draper and published by John Wiley & Sons. This book was released on 2014-08-25 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applied Linear Statistical Models

Author : John Neter
Publisher : Irwin Professional Publishing
ISBN 13 :
Total Pages : 864 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis Applied Linear Statistical Models by : John Neter

Download or read book Applied Linear Statistical Models written by John Neter and published by Irwin Professional Publishing. This book was released on 1974 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some basic results in probability and statistics. Basic regression analysis. General regression and correlation analysis. Basic analysis of variance. Multifactor analysis of variance. Experimental designs.

Applied Regression Analysis and Other Multivariable Methods

Author : David G. Kleinbaum
Publisher : PWS Publishing Company
ISBN 13 :
Total Pages : 584 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applied Regression Analysis and Other Multivariable Methods by : David G. Kleinbaum

Download or read book Applied Regression Analysis and Other Multivariable Methods written by David G. Kleinbaum and published by PWS Publishing Company. This book was released on 1978 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Regression Analysis in Econometrics

Author : Howard E. Doran
Publisher : CRC Press
ISBN 13 : 9780824780494
Total Pages : 400 pages
Book Rating : 4.7/5 (84 download)

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Book Synopsis Applied Regression Analysis in Econometrics by : Howard E. Doran

Download or read book Applied Regression Analysis in Econometrics written by Howard E. Doran and published by CRC Press. This book was released on 1989-04-24 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Applied Linear Statistical Models

Author : Michael H. Kutner
Publisher : McGraw-Hill Education
ISBN 13 : 9780071122214
Total Pages : 1396 pages
Book Rating : 4.1/5 (222 download)

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Book Synopsis Applied Linear Statistical Models by : Michael H. Kutner

Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill Education. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Primer of Multivariate Statistics

Author : Richard J. Harris
Publisher : Psychology Press
ISBN 13 : 1135555435
Total Pages : 632 pages
Book Rating : 4.1/5 (355 download)

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Book Synopsis A Primer of Multivariate Statistics by : Richard J. Harris

Download or read book A Primer of Multivariate Statistics written by Richard J. Harris and published by Psychology Press. This book was released on 2001-05-01 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.

Linear Models in Statistics

Author : Alvin C. Rencher
Publisher : John Wiley & Sons
ISBN 13 : 0470192607
Total Pages : 690 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Linear Models in Statistics by : Alvin C. Rencher

Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.

Multivariable Analysis

Author : Mitchell H. Katz
Publisher : Cambridge University Press
ISBN 13 : 0521840511
Total Pages : 199 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Multivariable Analysis by : Mitchell H. Katz

Download or read book Multivariable Analysis written by Mitchell H. Katz and published by Cambridge University Press. This book was released on 2006-02-06 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to perform and interpret multivariable analysis, using plain language rather than complex derivations.

Regression Analysis and Linear Models

Author : Richard B. Darlington
Publisher : Guilford Publications
ISBN 13 : 1462527981
Total Pages : 689 pages
Book Rating : 4.4/5 (625 download)

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Book Synopsis Regression Analysis and Linear Models by : Richard B. Darlington

Download or read book Regression Analysis and Linear Models written by Richard B. Darlington and published by Guilford Publications. This book was released on 2016-08-22 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book's examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable’s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.