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Titlebook: Statistical Data Analysis Using SAS; Intermediate Statist Mervyn G. Marasinghe,Kenneth J. Koehler Textbook 2018Latest edition Springer Inte

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書目名稱Statistical Data Analysis Using SAS
副標(biāo)題Intermediate Statist
編輯Mervyn G. Marasinghe,Kenneth J. Koehler
視頻videohttp://file.papertrans.cn/877/876391/876391.mp4
概述Integrates SAS programming with complex data analysis applications.Focuses on using SAS and statistical aspects of models and methods of analysis.Introduction to SAS - beyond the basics and illustrate
叢書名稱Springer Texts in Statistics
圖書封面Titlebook: Statistical Data Analysis Using SAS; Intermediate Statist Mervyn G. Marasinghe,Kenneth J. Koehler Textbook 2018Latest edition Springer Inte
描述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 SAScode 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 i
出版日期Textbook 2018Latest edition
關(guān)鍵詞statistical modeling; SAS; data analysis; programming; statistics; analysis of random models; analysis of
版次2
doihttps://doi.org/10.1007/978-3-319-69239-5
isbn_softcover978-3-319-69238-8
isbn_ebook978-3-319-69239-5Series ISSN 1431-875X Series E-ISSN 2197-4136
issn_series 1431-875X
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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Introduction to the SAS Language,r writing elementary SAS statements. Details of the data step are covered including the creation of a SAS data set using external data and examples of important data step programming statements. The INPUT statement and the operation of the SAS data step are presented in detail. The SAS procedure ste
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Introduction to SAS Graphics,OT, SGPANEL, and SGSCATTER are discussed along with key statements available for producing many useful statistical graphics applications. Other SAS procedures such as UNIVARIATE, TTEST, and GLM that produce template-based graphics are also used in various illustrations.
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Statistical Analysis of Regression Models,anced topics such as residual analysis and multicollinearity. The REG procedure is used to compute basic fit statistics, diagnostic case statistics, as well as produce associated template-based graphical tools for fitting both simple and multiple linear regression models. Discussion on REG and GLMSE
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Analysis of Variance: Random and Mixed Effects Models, two-way crossed and nested random effects models, and two-way mixed effects models. Applications include a variety of experiments with random effects including randomized blocks, nested factorials, and split-plot type experiments. Estimation and statistical inference associated with classical metho
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Beyond Regression and Analysis of Variance,. Generalized linear models, a special type of non-linear models, are introduced and illustrated with applications to logistic and Poisson regression models using LOGISTIC and GENMOD procedures. A separate section covers methods to handle overdispersion, including negative binomial models. The final
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