![]() ![]() 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. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Completely new chapter on analysis of nonlinear and generalized linear models.All SAS outputs are new and updated, including graphics.SAS® In-Memory Statistics Find insights in big data with a single environment that moves you quickly through each phase of the analytical life cycle. Presents new commands needed to produce ODS output SAS® Analytics Pro Access, manipulate, analyze and present information with a comprehensive analytical toolset that combines statistical analysis, reporting and high-impact visuals.Uses SAS ODS (output delivery system) for reproduction of tables and graphics output.Covers SAS v9.2 and incorporates new commands The data are analyzed with the commonly used statistical software of R/SAS (with online supplementary on SPSS/Stata).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. The text focuses on applied statistical problems and methods. 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 statistical techniques are updated by the solution to reflect current. 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. SAS Analytics Pro features statistical analysis and reporting capabilities. ![]() The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. Regardless of role, everyone in your organization will feel the impact of increased performance and productivity. 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. With our fully integrated, open source, cloud-native AI and analytics platform, you can understand what’s happening with your data now, predict how to pivot seamlessly, and make progress faster. ![]()
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