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Primer of Applied Regression Analysis of Variance Third Edition

Primer of Applied Regression   Analysis of Variance  Third Edition Author Stanton A. Glantz
ISBN-10 9780071822442
Release 2016-02-22
Pages 992
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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

Applied regression analysis

Applied regression analysis Author Norman Richard Draper
ISBN-10 UOM:39076002415656
Release 1998-04-23
Pages 706
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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.

Regression ANOVA and the General Linear Model

Regression  ANOVA  and the General Linear Model Author Peter Vik
ISBN-10 9781483316017
Release 2013-01-14
Pages 344
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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 Regression Modeling

Applied Regression Modeling Author Iain Pardoe
ISBN-10 9781118345047
Release 2013-01-07
Pages 346
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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.

The Analysis of Variance

The Analysis of Variance Author Henry Scheffé
ISBN-10 0471345059
Release 1999-03-05
Pages 477
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Originally published in 1959, this classic volume has had a major impact on generations of statisticians. Newly issued in the Wiley Classics Series, the book examines the basic theory of analysis of variance by considering several different mathematical models. Part I looks at the theory of fixed-effects models with independent observations of equal variance, while Part II begins to explore the analysis of variance in the case of other models.

Applied Linear Regression

Applied Linear Regression Author Sanford Weisberg
ISBN-10 9781118625958
Release 2013-06-07
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Applied Linear Regression has been writing in one form or another for most of life. You can find so many inspiration from Applied Linear Regression also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Applied Linear Regression book for free.

Qualitative Health Research

Qualitative Health Research Author Janice M Morse
ISBN-10 9781611320114
Release 2012-06-15
Pages 176
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The leading figure in qualitative health research (QHR), Janice M. Morse, asserts that QHR is its own separate discipline—distinct from both traditional health research and other kinds of qualitative research—and examines the implications of this position for theory, research, and practice. She contends that the health care environments transform many of the traditional norms of qualitative research and shape a new and different kind of research tradition. Similarly, the humanizing ethos of qualitative health research has much to teach traditional researchers and practitioners in health disciplines. She explores how the discipline of QHR can play out in practice, both in the clinic and in the classroom, in North America and around the world. A challenging, thought-provoking call to rethink how to conduct qualitative research in health settings.

Multivariate Statistical Methods

Multivariate Statistical Methods Author Bryan F.J. Manly
ISBN-10 9781498728997
Release 2016-11-03
Pages 269
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Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

Statistics for Health Professionals

Statistics for Health Professionals Author Susan Shott
ISBN-10 UOM:49015001115931
Release 1990-01
Pages 418
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Assists nursing and health professionals in gaining a basic understanding of statistics. Appropriate for self-study or course use, this pratical text trains the student to become a better consumer of research by identifying violations of statistical assumptions and interpreting results. Emphasizes a general understanding, rather than memorization, of formulas. Where possible, calculations are simplified to avoid "number crunching." Numerous practical examples taken from published research, exercises, objectives, and summaries to aid learning.

Applied Regression Analysis

Applied Regression Analysis Author John O. Rawlings
ISBN-10 9780387227535
Release 2006-04-06
Pages 660
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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.

The R Book

The R Book Author Michael J. Crawley
ISBN-10 9781118448960
Release 2012-11-07
Pages 1080
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Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)

Applied statistics analysis of variance and regression

Applied statistics  analysis of variance and regression Author Olive Jean Dunn
ISBN-10 UCAL:B4405760
Release 1974
Pages 387
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Applied statistics analysis of variance and regression has been writing in one form or another for most of life. You can find so many inspiration from Applied statistics analysis of variance and regression also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Applied statistics analysis of variance and regression book for free.

Applied Regression Analysis and Generalized Linear Models

Applied Regression Analysis and Generalized Linear Models Author John Fox
ISBN-10 9781483321318
Release 2015-03-18
Pages 816
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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.

Regression Diagnostics

Regression Diagnostics Author John Fox
ISBN-10 080393971X
Release 1991-08-14
Pages 92
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With Regression Diagnostics, researchers now have an accessible explanation of the techniques needed for exploring problems that compromise a regression analysis and for determining whether certain assumptions appear reasonable. The book covers such topics as the problem of collinearity in multiple regression, dealing with outlying and influential data, non-normality of errors, non-constant error variance and the problems and opportunities presented by discrete data. In addition, sophisticated diagnostics based on maximum-likelihood methods, scores tests, and constructed variables are introduced.

Applied Multivariate Analysis

Applied Multivariate Analysis Author S. James Press
ISBN-10 9780486442365
Release 2005-06-28
Pages 671
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Includes practical elements of matrix theory, continuous multivariate distributions and basic multivariate statistics in the normal distribution; regression and the analysis of variance; factor analysis and latent structure analysis; canonical correlations; stable portfolio analysis; classifications and discrimination models; control in the multivariate linear model; and structuring multivariate populations. 1982 edition.

Applied Regression Analysis and Other Multivariable Methods

Applied Regression Analysis and Other Multivariable Methods Author David Kleinbaum
ISBN-10 9781285051086
Release 2013-08-30
Pages 1072
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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 Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

A Handbook of Statistical Analyses using R Third Edition

A Handbook of Statistical Analyses using R  Third Edition Author Torsten Hothorn
ISBN-10 9781482204582
Release 2014-06-25
Pages 456
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Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.