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Statistical Data Analysis Using SAS, Mervyn G. Marasinghe; Kenneth J. Koehler


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Автор: Mervyn G. Marasinghe; Kenneth J. Koehler
Название:  Statistical Data Analysis Using SAS
ISBN: 9783319692388
Издательство: Springer
Классификация:

ISBN-10: 3319692380
Обложка/Формат: Paperback
Страницы: 684
Вес: 1.43 кг.
Дата издания: 23.04.2018
Серия: Springer Texts in Statistics
Язык: English
Издание: 2nd ed. 2017
Иллюстрации: 335 illustrations, color; 49 illustrations, black and white; xvi, 684 p. 384 illus., 335 illus. in color. with 100 sas programs.
Размер: 254 x 183 x 37
Читательская аудитория: Postgraduate, research & scholarly
Основная тема: Statistics
Подзаголовок: Intermediate Statistical Methods
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.


Дополнительное описание: 1 Introduction to the SAS Language.- 2 More on SAS Programming and Some Applications.- 3 Introduction to SAS Graphics.- 4 Statistical Analysis of Regression Models.- 5 Analysis of Variance Models.- 6 Analysis of Variance: Random and Mixed Effects Models.-



Statistical Learning for Biomedical Data

Автор: Malley
Название: Statistical Learning for Biomedical Data
ISBN: 0521699096 ISBN-13(EAN): 9780521699099
Издательство: Cambridge Academ
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Цена: 6494.00 р.
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Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.

Complex Survey Data Analysis with SAS

Автор: Lewis
Название: Complex Survey Data Analysis with SAS
ISBN: 1498776779 ISBN-13(EAN): 9781498776776
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: Complex Survey Data Analysis with SAS (R) is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors.

Research design and statistical analysis

Автор: Myers, Jerome L
Название: Research design and statistical analysis
ISBN: 0805864318 ISBN-13(EAN): 9780805864311
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: This interdisciplinary group of scholars-anthropologists, archaeologists, architects, educators, lawyers, heritage administrators, policy analysts, and consultants-make the first attempt to define and assess heritage values on a local, national and global level. Chapters range from the theoretical to policy frameworks to case studies of heritage practice, written by scholars from eight countries.

Conducting Meta-Analysis Using SAS

Автор: Arthur, Jr.
Название: Conducting Meta-Analysis Using SAS
ISBN: 0805838090 ISBN-13(EAN): 9780805838091
Издательство: Taylor&Francis
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Цена: 6123.00 р.
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Описание: Designed to teach the reader about meta-analysis and show them how to conduct one using SAS. Its focus is more applied and practical than theoretical and will include additional programming codes and examples. Web site to house program code and sample ou

SAS for Data Analysis

Автор: Mervyn G. Marasinghe; William J. Kennedy
Название: SAS for Data Analysis
ISBN: 148998772X ISBN-13(EAN): 9781489987723
Издательство: Springer
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Цена: 9083.00 р.
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Описание: This book is an integrated treatment of applied statistical methods, presented at an intermediate level. It serves as an advanced introduction to the SAS programming language as well as demonstrating how to use SAS to analyse of a wide variety of data.

Applied Linear Statistical Models with Student CD

Автор: Nachtsheim;Neter;Kutner
Название: Applied Linear Statistical Models with Student CD
ISBN: 0071122214 ISBN-13(EAN): 9780071122214
Издательство: McGraw-Hill
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Цена: 9265.00 р.
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Описание: "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.

An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 27712.00 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.


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