Statistical Data Analysis Using SAS: Intermediate Statistical Methods (Springer Texts in Statistics)

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.

這本教科書（之前名為SAS for Data Analytics）的目標是教授給統計學、資料科學以及涉及數據分析的高年級本科生和研究生使用SAS進行統計數據分析的方法。

本書以超越SAS基礎的介紹開始，並以非平凡的真實世界實例進行說明。接著介紹SAS編程和應用、SAS圖形、回歸模型的統計分析、變異數模型的分析、帶有隨機和混合效應模型的變異數分析，最後將討論擴展到回歸和變異數分析之外的領域。

在教學上，作者逐個主題介紹理論和方法基礎，以應用問題作為示例，提供SAS對所提供數據的分析以及結果討論。本書專注於應用統計問題和方法。主要特點包括：章末練習題、可下載的SAS代碼和數據集，以及適合進階應用統計學第二門課程的高級材料，每種方法都使用SAS分析來說明真實世界的問題。

本版新增內容：

•    涵蓋SAS v9.2並引入新的命令
•    使用SAS ODS（輸出傳遞系統）重現表格和圖形輸出
•    介紹產生ODS輸出所需的新命令
•    所有章節都重新編寫以提高清晰度
•    全書新增和更新的實例
•    所有SAS輸出都是新的和更新的，包括圖形
•    更多練習和問題
•    全新章節：非線性和廣義線性模型的分析
•    全新附錄

Mervyn G. Marasinghe, PhD，是愛荷華州立大學統計學名譽副教授，曾教授統計方法和統計計算課程。

Kenneth J. Koehler, PhD，是愛荷華州立大學統計學大學教授，教授研究生和本科生的統計方法課程，主要使用SAS輔助教學。