Applied Regression and ANOVA Using SAS

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Author :
Publisher : CRC Press
ISBN 13 : 0429527039
Total Pages : 490 pages
Book Rating : 4.36/5 ( download)

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Book Synopsis Applied Regression and ANOVA Using SAS by : Patricia F. Moodie

Download or read book Applied Regression and ANOVA Using SAS written by Patricia F. Moodie and published by CRC Press. This book was released on 2022-06-07 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Regression and ANOVA Using SAS® has been written specifically for non-statisticians and applied statisticians who are primarily interested in what their data are revealing. Interpretation of results are key throughout this intermediate-level applied statistics book. The authors introduce each method by discussing its characteristic features, reasons for its use, and its underlying assumptions. They then guide readers in applying each method by suggesting a step-by-step approach while providing annotated SAS programs to implement these steps. Those unfamiliar with SAS software will find this book helpful as SAS programming basics are covered in the first chapter. Subsequent chapters give programming details on a need-to-know basis. Experienced as well as entry-level SAS users will find the book useful in applying linear regression and ANOVA methods, as explanations of SAS statements and options chosen for specific methods are provided. Features: •Statistical concepts presented in words without matrix algebra and calculus •Numerous SAS programs, including examples which require minimum programming effort to produce high resolution publication-ready graphics •Practical advice on interpreting results in light of relatively recent views on threshold p-values, multiple testing, simultaneous confidence intervals, confounding adjustment, bootstrapping, and predictor variable selection •Suggestions of alternative approaches when a method’s ideal inference conditions are unreasonable for one’s data This book is invaluable for non-statisticians and applied statisticians who analyze and interpret real-world data. It could be used in a graduate level course for non-statistical disciplines as well as in an applied undergraduate course in statistics or biostatistics.

Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set

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Author :
Publisher : Wiley-Interscience
ISBN 13 : 9780470388037
Total Pages : 0 pages
Book Rating : 4.3X/5 ( download)

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Book Synopsis Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set by : Keith E. Muller

Download or read book Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set written by Keith E. Muller and published by Wiley-Interscience. This book was released on 2008-03-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This set contains: 9780471469438 Regression and ANOVA: An Integrated Approach Using SAS(R) Software by Keith E. Muller, Bethel A. Fetterman and 9780471370383 Applied Statistics: Analysis of Variance and Regression, Third Edition by Ruth M. Mickey, Olive Jean Dunn, Virginia A. Clark.

Applied Regression and ANOVA Using SAS

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Author :
Publisher : CRC Press
ISBN 13 : 1439869529
Total Pages : 428 pages
Book Rating : 4.29/5 ( download)

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Book Synopsis Applied Regression and ANOVA Using SAS by : Patricia F. Moodie

Download or read book Applied Regression and ANOVA Using SAS written by Patricia F. Moodie and published by CRC Press. This book was released on 2022-06-07 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Regression and ANOVA Using SAS® has been written specifically for non-statisticians and applied statisticians who are primarily interested in what their data are revealing. Interpretation of results are key throughout this intermediate-level applied statistics book. The authors introduce each method by discussing its characteristic features, reasons for its use, and its underlying assumptions. They then guide readers in applying each method by suggesting a step-by-step approach while providing annotated SAS programs to implement these steps. Those unfamiliar with SAS software will find this book helpful as SAS programming basics are covered in the first chapter. Subsequent chapters give programming details on a need-to-know basis. Experienced as well as entry-level SAS users will find the book useful in applying linear regression and ANOVA methods, as explanations of SAS statements and options chosen for specific methods are provided. Features: •Statistical concepts presented in words without matrix algebra and calculus •Numerous SAS programs, including examples which require minimum programming effort to produce high resolution publication-ready graphics •Practical advice on interpreting results in light of relatively recent views on threshold p-values, multiple testing, simultaneous confidence intervals, confounding adjustment, bootstrapping, and predictor variable selection •Suggestions of alternative approaches when a method’s ideal inference conditions are unreasonable for one’s data This book is invaluable for non-statisticians and applied statisticians who analyze and interpret real-world data. It could be used in a graduate level course for non-statistical disciplines as well as in an applied undergraduate course in statistics or biostatistics.

Understanding Regression and ANOVA as Research Tools Using SAS

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Author :
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781439869512
Total Pages : 384 pages
Book Rating : 4.10/5 ( download)

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Book Synopsis Understanding Regression and ANOVA as Research Tools Using SAS by : Patricia F. Moodie

Download or read book Understanding Regression and ANOVA as Research Tools Using SAS written by Patricia F. Moodie and published by Chapman and Hall/CRC. This book was released on 2016-02-15 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for researchers and data analysts, this book presents rigorous statistical methods without burdening readers with mathematical theory. Readers see how linear regression and ANOVA can be used in biology, agriculture, health science, environmental science, fisheries, forestry, as well as the physical, social, and behavioral sciences. Each statistical topic is illustrated using detailed worked examples and relevant SAS procedures. The book emphasizes interpretation of analyses integrating graphical and statistical results and offers a detailed step-by-step guide for each analysis.

SAS for Data Analysis

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 038777372X
Total Pages : 562 pages
Book Rating : 4.28/5 ( download)

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Book Synopsis SAS for Data Analysis by : Mervyn G. Marasinghe

Download or read book SAS for Data Analysis written by Mervyn G. Marasinghe and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Statistical Data Analysis Using SAS

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Author :
Publisher : Springer
ISBN 13 : 3319692399
Total Pages : 679 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis Statistical Data Analysis Using SAS by : Mervyn G. Marasinghe

Download or read book Statistical Data Analysis Using SAS written by Mervyn G. Marasinghe and published by Springer. This book was released on 2018-04-12 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. New to this edition: • Covers SAS v9.2 and incorporates new commands • Uses SAS ODS (output delivery system) for reproduction of tables and graphics output • Presents new commands needed to produce ODS output • All chapters rewritten for clarity • New and updated examples throughout • All SAS outputs are new and updated, including graphics • More exercises and problems • Completely new chapter on analysis of nonlinear and generalized linear models • Completely new appendix Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.

SAS System for Regression

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 0471416649
Total Pages : 258 pages
Book Rating : 4.47/5 ( download)

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Book Synopsis SAS System for Regression by : Rudolf Freund

Download or read book SAS System for Regression written by Rudolf Freund and published by John Wiley & Sons. This book was released on 2000-12-29 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS® System for Regression Learn to perform a wide variety of regression analyses using SAS® software with this example-driven revised favorite from SAS Publishing. With this Third Edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics covered include performing linear regression analyses using PROC REG diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and the SAS System are assumed. New for this edition The Third Edition includes revisions, updated material, and new material. You’ll find new information on using SAS/INSIGHT® software regression with a binary response with emphasis on PROC LOGISTIC nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, using the OUTEST option to produce a data set, and using PROC SCORE to predict another data set.

Applied Regression Analysis

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 0387227539
Total Pages : 671 pages
Book Rating : 4.35/5 ( 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 2006-03-31 with total page 671 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 and ANOVA

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Author :
Publisher : SAS Press
ISBN 13 : 9781580258906
Total Pages : 0 pages
Book Rating : 4.05/5 ( download)

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Book Synopsis Regression and ANOVA by : Keith E. Muller

Download or read book Regression and ANOVA written by Keith E. Muller and published by SAS Press. This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Muller and Fetterman (U. of N. Carolina, Chapel Hill) developed this text for use in "Intermediate Linear Models," a graduate level biostatistics class at UNC, covering basic theory, multiple regression, model building and evaluation, ANOVA, and universal tools. The text uses sets of real data, and contains almost no proofs. Ideal prerequisites for use include a matrix algebra class, an undergraduate introduction to mathematical statistics, basic programming skills in the statistical package used in the course (data input, data transformation, and analysis), and basic skills in linear models. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).

Regression and ANOVA

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Author :
Publisher : Wiley-SAS
ISBN 13 :
Total Pages : 582 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis Regression and ANOVA by : Keith E. Muller

Download or read book Regression and ANOVA written by Keith E. Muller and published by Wiley-SAS. This book was released on 2003-06-03 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: Muller and Fetterman (U. of N. Carolina, Chapel Hill) developed this text for use in "Intermediate Linear Models," a graduate level biostatistics class at UNC, covering basic theory, multiple regression, model building and evaluation, ANOVA, and universal tools. The text uses sets of real data, and contains almost no proofs. Ideal prerequisites for use include a matrix algebra class, an undergraduate introduction to mathematical statistics, basic programming skills in the statistical package used in the course (data input, data transformation, and analysis), and basic skills in linear models. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).