St@tServ Statistical Online Bookstore
SAS

Generalities

Title / Author(s)	Year / Publisher	Comments
The Little SAS (R) Book: A Primer Lora D. Delwiche, Susan Slaughter	SAS Institute	It is a wonderfully written book for SAS beginners. It introduces the very basic concepts of SAS in a language that everyone can understand. As an added bonus, the data used for different examples can be downloaded from the SAS homepage. A must for beginners.
Applied Statistics and the Sas Programming Language Ronald P. Cody, Ron Cody, Jeffrey Smith	1997 Prentice Hall College Div	Applied Statistics and the SAS Programming Language is intended to provide the applied researcher with the capacity to perform statistical analyses with SAS software without wading through pages of technical documentation.
Professional Sas Programmer's Pocket Reference Rick Aster	1998 SAS Institute	This is it -- the one book you need to write SAS programs quickly and efficiently. Get the authoritative information you need about SAS syntax, routines, commands, and other features, including over 100 new features you won't find in older books. Whether you're a student or a professional, an advanced programmer or a beginner, at your desk or on the road, Professional SAS Programmer's Pocket Reference is a book you'll use every time you write a SAS program.
Quick Start to Data Analysis With Sas Kenneth A. Hardy (Contributor), Frank C. DiIorio	1996 Duxbury Pr	You'll find everything you need to get started in SAS from understanding program syntax to managing data and performing statistical analyses. First-time users of SAS will benefit from the book's no-nonsense approach to statistical analysis. The book explains the fundamentals of SAS and immediately gives readers the basic skills needed to begin effectively managing and analyzing data. Quick Start even teaches readers advanced data analysis using SAS. Readers can expect to gain basic SAS competency by using Quick Start as a self-directed guidebook or as a textbook for a course in SAS.

Econometry

Title / Author(s)	Year / Publisher	Comments
Learning Sas : A Computer Handbook for Econometrics R. Carter Hill, William E. Griffiths	1993 John Wiley & Sons	Designed to promote students' understanding of econometrics and to build a more operational knowledge of economics through a meaningful combination of words, symbols and ideas. Each chapter commences in the way economists begin new empirical projects--with a question and an economic model--then proceeds to develop a statistical model, select an estimator and outline inference procedures. Contains a copious amount of problems, experimental exercises and case studies.
Forecasting Examples for Business and Economics Using the SAS (R) System	1993 SAS Institute	Numerous step-by-step examples show you - the economist, business forecaster, student, or researcher - how to use the SAS System to generate forecasts for a variety of business and economic data. Examples are based on both time series models and econometric models. You'll learn how to use the SAS System to forecast time series data using Box-Jenkins ARIMA methodology; develop and forecast transfer functions and intervention models; fit and forecast regression models with autocorrelated, heteroskedastic, and ARCH-GARCH error terms; estimate nonlinear regression models, create forecast confidence limits using Monte Carlo simulation, and more! The main focus of the book is on the code-based procedures in SAS/ETS software, but this book also provides an introduction to the interactive Time Series Forecasting Syste,and it shows how to plot data and forecasts with SAS/GRAPH software.
Learning Sas : A Computer Handbook for Econometrics R. Carter Hill, William E. Griffiths	1993 John Wiley & Sons	xxx

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Title / Author(s)	Year / Publisher	Comments
Modeling Techniques for Categorical Response Data Course Notes SAS Institute Inc	1995 SAS Institute Inc	This Course Notes supports the Modeling Techniques for Categorical ResponseData course. It explains how to use base SAS and SAS/STAT categorical analysis procedures to analyze frequency data. Topics covered include measuring the strength of association between pairs of categorical variables, estimating parameters and answering questions about categorical data using linear and log-linear models, and understanding the various types of categorical data analysis.
Multivariate Statistical Methods : A First Course George A. Marcoulides, Scott L. Hershberger	1997 Lawrence Erlbaum Assoc	Modern Elementary Probability and Statistics, With Statistical Programming in Sas, Minitab, & Bmdp
Principles of Regression Analysis Course Notes SAS Institute Inc	1994 SAS Institute Inc	This Course Notes explains techniques for performing regression analyses with SAS software. You learn how to write SAS programs and interpret output for simple and multiple linear regression analyses. The book emphasizes fitting regression models with the REG procedure and verifying the model assumptions.
SAS (R) Technical Report R-109, Conjoint Analysis Examples AAA	SAS Institute
SAS (R) Technical Report R-101, Tests of the Hypotheses in Fixed-Effects Linear Models. SAS Institute	1992 SAS Institute	This report defines three types of estimable functions that can be used in SAS software to test hypotheses in multifactor fixed-effects linear models. Each type handles unequal n's, missing cells, and any degree of confounding for any fixed-effects linear model.
SAS (R) Technical Report R-103, Least-Squares Means in the Fixed-Effects General Linear Models SAS Institute	1992 SAS Institute	Defines the least-squares means for the fixed-effects general linear model. The report also discusses the use of least-squares means in lieu of class or subclass arithmetic means with unbalanced designs, and shows the relationship between least-squares and adjusted means.
Sas Programming for Researchers and Social Scientists Paul E. Spector	1993 Sage Pubns
Selecting Statistical Techniques for Social Science Data: A Guide for SAS(R) Users Frank M. Andrews, Laura Klem, ...	1998 SAS Institute	Take the guesswork out of selecting a statistical technique for social science data! This guide will help you select from the vast array of statistical techniques that can be applied in a particular analysis. This guide addresses social scientists, data analysts, and graduate students who have some knowledge of social science statistics and who want a systematic, highly condensed overview of many of the statistical techniques in current use and the purposes for which each is intended. Originally published in 1971, this guide has been updated to incorporate current statistical and analytical developments. In addition, you'll find a summary of how each of the techniques is provided through SAS software.
A Step-by-Step Approach to Using the SAS (R) System for Univariate and Multivariate Statistics Larry Hatcher, Edward J. Stepanski	SAS Institute	A user-friendly guide beneficial to both researchers and students of the social sciences, this book provides a very comprehensive introduction of the SAS System and elementary statistical procedures. Step by step, this book guides beginners through the basic concepts of research and data analysis, to data input and on to ANOVA and MANOVA. The more advanced researchers will find the presentation of sophisticated statistical procedures invaluable. With this book you will learn to write SAS programs, interpret results, perform statistical analyses without a broad mathematics background, and summarize results in American Psychological Association format.
Making Business Decisions Using ANOVA and Regression Techniques Course Notes SAS Institute	1997 SAS Institute	This Course Notes is for data analysts and researchers with some statistical training who want to analyze continuous response data using analysis of variance and regression methods. This book teaches how to use the GLM, PLAN, REG, and TTEST procedures for analysis of variance, simple and multiple regression, and analysis of covariance, and it also introduces the MIXED procedure for repeated meansures analysis.
Logistic Regression Examples Using the SAS (R) System, Version 6, First Edition SAS Institute	SAS Institute	Packed with step-by-step examples, this book shows you how to use the SAS System to perform logistic, probit, and conditional logistic regression analyses. This book enables statisticians, researchers, and new students to learn from the set of examples so that they can perform their own analyses and produce and understand the output. This book focuses on the LOGISTIC procedure but also contains examples that use the CATMOD, GENMOD, PHREG, and PROBIT procedures in SAS/STAT software.
Introduction to Statistical Quality Improvement Using SAS/QC (R) Software Course Notes SAS Institute	1996 SAS Institute	This Course Notes introduces statistical process improvement techniques using the SQC and ADX Menu Systems in SAS/QC software. Topics covered include developing and interpreting control charts, using graphical methodsto display factors that may affect a process, and using an automated system to construct and analyze screening designs.
SAS/STAT (R) User's Guide, Version 6, Fourth Edition, Volumes 1 and 2 SAS Institute	SAS Institute	You'll find within these 2 volumes detailed reference information on the procedures in SAS/STAT software as of Release 6.06. In Volume 1, chapters 1 through 8 give an overview of different types of analytical procedures. Most of the remaining chapters in Volume 1 and all the chapters in Volume 2 describe individual SAS/STAT procedures, listed alphabetically. Combined with SAS/STAT Software: Changes and Enhancements through Release 6.12, these two volumes provide reference information on all SAS/STAT procedures. This book is designed for data analysts who use SAS/STAT software and are familiar with basic SAS System concepts.
Applied Multivariate Statistics With Sas Software Ravinda Kattree, Dayanand N. Naik	1999 John Wiley & Sons	Easy to read and comprehensive, this book presents multivariate statistical methods using real-world problems and real data sets. The authors' unique approach to integrating statistical methods, data analysis, and applications of SAS software will aid professors, researchers, and students in a variety of disciplines and industries. The extensive SAS code and corresponding output accompany sample problems and clear explanations of the appropriate SAS procedures. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both theory and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression.
Applying Statistics to Business Decisions: A Point-and-Click Approach Course Notes SAS Institute	1997 SAS Institute	This Course Notes introduces fundamental statistical concepts using graphical tools and a variety of business decision-making examples.
Basic Statistics Using SAS (R) Software Course Notes SAS Institute	1998 SAS Institute	This Course Notes covers a range of statistical topics and the use of SAS software to carry out statistical analyses. Topics include statistical inference, analysis of variance, multiple regression, and categorical data analysis.
Categorical Data Analysis Using the SAS (R) System Maura E. Stokes, Charles S. Davis, Gary G. Koch	SAS Institute
Common Statistical Methods for Clinical Research with SAS (R) Examples Glenn A. Walker	SAS Institute	Clinical researchers, with or without a statistical background, will find this book an invaluable aid in understanding the statistical methods cited most frequently in clinical protocols, statistical analysis plans, clinical and statistical reports, and medical journals. Written in a manner which leads the nonstatistician through each test by example, substantive details are presented which will benefit even the experienced data analysts. Introductory chapters provide elementary statistical concepts as applied to clinical trials and an overview of statistical inference, including discussions of power, sample size calculations, p-values and the logic behind hypothesis testing. Numerous examples from clinical research are worked through both manually and using SAS. Methods presented include t-tests, analysis of variance, repeated measures ANOVA, linear regression, analysis of covariance, non-parametric tests, binomial tests, chi-square test, Fisher's exact test, McNemar's test, Cochran-Mantel-Haenszel test, logistic regression, log-rank test, and Cox proportional hazards model.
Design and Analysis of Experiments Using the ADX Menu System Course Notes SAS Institute	SAS Institute	This Course Notes shows you how to design and analyze experiments using the ADX Menu System in SAS/QC software. The book helps you understand what makes a good design and teaches you how to select the best possible experimental design.
A Handbook of Statistical Analyses Using Sas Geoff Der, B. Everott, B. Everitt	1996 CRC Pr
Statistical Quality Control Using the SAS (R) System Dennis W. King	SAS Institute	Gain a real-world perspective on statistical methods used in quality control applications. The example-based approach guides you through using SAS/QC software to analyze quality control data and improve processes. Readers with SAS programming experience and statistics knowledge will learn how to produce and interpret check sheets, Pareto charts, Ishikawa diagrams, defect concentration diagrams, scatter diagrams, control charts, histograms, and more! Those new to quality control will benefit from the detailed section on data collection. Filled with illustrations, this book gives you a behind-the-scenes look at quality control tasks performed with and without the SQC and ADX menu systems. Also featured are strategies for designing and analyzing experiments, creating sampling plans, analyzing gage repeatability and reproducibility studies, and performing tolerance and linear calibration analysis with SAS software.
Applied Multivariate Statistics with SAS (R) Software Ravindra Khattree, Dayanand N. Naik	SAS Institute
Statistical Quality Improvement: MACONTROL and CUSUM Procedures Course Notes SAS Institute	1996 SAS Institute	This Course Notes is for SAS software users who want to generate graphic tools for quality improvement using SAS/QC software. The course discusses two quality improvement tools: moving average charts and cumulative sum control charts.
Sas Technical Report A-102, Sas Regression Applications SAS Institute	1997 SAS Institute