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Academic Evaluation Copies
If you are considering a SAS title for your classroom, you can request an academic evaluation copy for your review. Visit our
evaluation copy form for titles that are available to you.
Authoring Opportunities
SAS also offers the opportunity for professors and instructors to author their own SAS books.
Discover why we are your publisher of choice. Or if you're already working with another publisher, consider applying for participation in our
new SAS Author Assistance Program. You can also e-mail us for details.
Recommended Titles
SAS Press offers many books particularly suited for use in higher education. Below is a list of the most popular selections. You can download the code and data for these books from the
SAS Press Companion sites.
This list of bestselling SAS Press titles is organized by the below categories. Our online bookstore lists all available titles.
These popular SAS titles are a great starting place for anyone interested in teaching or learning more about SAS and basic statistics.
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Applied Multivariate Statistics with SAS Software, Second Edition By Ravindra Khattree and Dayanand Naik
Real-world problems and data sets provide a unique approach to the topic: integrating statistical methods, data analysis, and applications.
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Basic Statistics Using SAS Enterprise Guide: A Primer By Geoff Der and Brian S. Everitt
This example-rich guide shows you how to conduct a wide range of statistical analyses with no SAS programming required.
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Cody's Data Cleaning Techniques Using SAS, Second Edition By Ron Cody, Ed.D.
Addresses tasks that nearly every SAS programmer needs to do: make sure that data errors are located and corrected.
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Elementary Statistics Using JMP By Sandra Schlotzhauer
Learn how to perform basic statistical analyses using the powerful JMP software.
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Elementary Statistics Using SAS By Sandra Schlotzhauer
Bridging the gap between statistics texts and SAS documentation, this book is written for those who want to perform analyses to solve problems.
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Introduction to Design of Experiments with JMP Examples, Third Edition By Jacques Goupy and Lee Creighton
This edition addresses a wide array of designs, including full-factorial designs, fractional-factorial designs, response surface designs, mixture designs, and more.
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JMP for Basic Univariate and Multivariate Statistics: A Step-by-Step Guide By Ann Lehman, Ph.D., Norm O'Rourke, Ph.D., Larry Hatcher, Ph.D., and Edward J. Stepanski, Ph.D.
Shows how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields.
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JMP Start Statistics: A Guide to Statistics and Data Analysis Using JMP, Fourth Edition By John Sall, Lee Creighton, and Ann Lehman
A mix of software manual and statistics text, this book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use JMP's intuitive
interface for data analysis
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Learning SAS by Example: A Programmer's Guide By Ron Cody
If you like learning by example, then this straightforward book makes it easy to learn SAS programming.
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The Little SAS Book: A Primer, Fourth Edition By Lora D. Delwiche and Susan J. Slaughter
Gently introduces you to the most commonly used features of SAS software with clear explanations and examples.
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The Little SAS Book for Enterprise Guide 4.1 By Lora D. Delwiche and Susan J. Slaughter
This guide helps you quickly become familiar with the SAS Enterprise Guide point-and-click environment.
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SAS for Linear Models, Fourth Edition By Ramon C. Littell, Ph.D., Walter W. Stroup, Ph.D., and Rudolf J. Freund, Ph.D.
Uses a tutorial approach and plenty of examples to lead you through methods related to analysis of variance with fixed and
random effects.
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SAS for Mixed Models, Second Edition By Ramon Littell, George Milliken, Walter Stroup, Russell Wolfinger, and Oliver Schabenberger
Describes the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures
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SAS System for Regression, Third Edition By Rudolf J. Freund, Ph.D., and Ramon C. Littell, Ph.D.
An example-driven guide that shows how to perform a wide variety of regression analyses using SAS software.
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A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics, Second Edition By Norm O'Rourke, Ph.D., Larry Hatcher, Ph.D., and Edward Stepanski, Ph.D.
Updated for SAS 9, this second edition is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics.
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Step-by-Step Basic Statistics Using SAS: Student Guide and Exercises By Larry Hatcher, Ph.D.
Introduces you to SAS software and leads you through a variety of elementary statistical analyses commonly used in the social and
behavioral sciences.
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Involved in more advanced analytics and concepts? Consider these recommended titles for your classroom or personal reference library.
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Advanced Log-Linear Models Using SAS By Daniel Zelterman, Ph.D.
Illustrates how to use the GENMOD procedure to analyze log-linear models for categorical data.
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Applied Multivariate Statistics with SAS Software, Second Edition By Ravindra Khattree, Ph.D., and Dayanand N. Naik, Ph.D.
Includes information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding
IML procedure code, and covariance structures. Together with Multivariate Data Reduction
and Discrimination with SAS Software, provides comprehensive information about using SAS for multivariate statistics.
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Categorical Data Analysis Using the SAS System, Second Edition By Maura E. Stokes, Ph.D., Charles S. Davis, Ph.D., and Gary G. Koch, Ph.D.
Provides a discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS.
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Fixed Effects Regression Methods for Longitudinal Data Using SAS By Paul Allison, Ph.D.
An invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques.
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Logistic Regression Using the SAS System: Theory and Application By Paul Allison, Ph.D.
Written for researchers or students with experience in multiple linear regression who want to learn about logistic regression.
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Multiple Comparisons and Multiple Tests Using SAS By Peter H. Westfall, Ph.D., Randall D. Tobias, Ph.D., Dror Rom, Ph.D., Russell D. Wolfinger, Ph.D., and Yosef Hochberg, Ph.D.
Ideal for learning multiple comparisons procedures in standard linear models, multivariate analysis, categorical analysis, and regression and
nonparametric statistics.
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Regression and ANOVA: An Integrated Approach Using SAS Software By Keith E. Muller, Ph.D., and Bethel A. Fetterman, M.S.
A graduate-level book that focuses on the general linear model (GLM) theory, stated in matrix terms, which provides a more compact, clear, and unified presentation of regression and ANOVA than
do traditional sums of squares and scalar equations.
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SAS for Forecasting Time Series, Second Edition By John C. Brocklebank, Ph.D., and David A. Dickey, Ph.D.
A tutorial guide that demonstrates how SAS performs univariate and multivariate time series analysis.
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SAS System for Mixed Models, Second Edition By Ramon Littell, Ph.D., George Milliken, Ph.D., Walter Stroup,Ph.D., Russell Wolfinger, Ph.D., and Oliver Schabenberger, Ph.D.
Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures. Completely revised and updated for SAS®9.
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Survival Analysis Using SAS: A Practical Guide By Paul Allison, Ph.D.
An easy-to-read and comprehensive guide for biomedical and social science researchers who want to analyze survival data with SAS.
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Visualizing Categorical Data By Michael Friendly, Ph.D.
Offers many new and more easily accessible graphical methods for representing categorical data using SAS software.
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These titles are a must-read for professors, students, and researchers interested in expanding their research capabilities in SAS.
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Analysis of Clinical Trials Using SAS: A Practical Guide By Alex Dmitrienko, Ph.D., Geert Molenberghs, Ph.D., Christy Chuang-Stein, Ph.D., and Walter Offen, Ph.D.
Step-by-step instructions illustrated with examples from actual trials and case studies that serve to define a statistical method and its
relevance in a clinical trials setting and to illustrate how to implement the method rapidly and efficiently using the power of SAS software.
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Analyzing Receiver Operating Characteristic Curves with SAS By Mithat Gonen
This example-driven book illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros.
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Genetic Analysis of Complex Traits Using SAS Edited by Arnold M. Saxton, Ph.D.
Demonstrates how you can use SAS and SAS/Genetics to extract answers from your quantitative and molecular genetics data.
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Pharmaceutical Statistics Using SAS: A Practical Guide By Alex Dmitrienko, Christy Chuang-Stein, and Ralph D'Agostino
This essential new book offers extensive coverage of cutting-edge biostatistical methodology used in drug development and the practical problems facing today's
drug developers.
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SAS for Monte Carlo Studies: A Guide for Quantitative Researchers By Xitao Fan, Ph.D., Akos Felsovalyi, M.S., Stephen A. Sivo, Ph.D., and Sean C. Keenan, Ph.D.
Provides detailed and practical guidance for conducting Monte Carlo studies using SAS.
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SAS Programming in the Pharmaceutical Industry By Jack Shostak
A real-world reference guide for clinical trial SAS programming, packed with solutions that programmers can apply to their day-to-day problems.
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SAS Survival Analysis Techniques for Medical Research, Second Edition By Alan Cantor, Ph.D.
Presents the theory and methods of survival analysis along with excellent discussions of the SAS procedures used to implement the methods described.
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Validating Clinical Trial Data Reporting with SAS By Carol I. Matthews and Brian Shilling
Focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and output to the Food and Drug Administration (FDA).
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Interested in exploring the exciting world of data mining using SAS? Here are some great books to guide you.
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Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring By Naeem Siddiqi, M.B.A.
Presents a business-focused process built on a solid foundation of statistic and data mining principles for the development and implementation
of risk prediction scorecards.
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CRM Segmentation and Clustering Using SAS Enterprise Miner By Randall S. Collica
In this instructive guide, Randy Collica employs SAS Enterprise Miner and the most commonly available techniques for customer relationship management (CRM).
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Data Preparation for Analytics Using SAS By Gerhard Svolba
This user-friendly text offers practical advice in the form of SAS coding tips and tricks, along with providing the reader with a conceptual background on
data structures and considerations from the business point of view.
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Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner By Barry deVille
Using SAS Enterprise Miner, this book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics,
prediction, and knowledge discovery.
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Integrating Results through Meta-Analytic Review Using SAS Software By Morgan C. Wang, Ph.D., and Brad J. Bushman, Ph.D.
Wang and Bushman offer a thorough description of how meta-analysis can be used in data mining projects to discover meaningful relations among variables
in a collection of studies.
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Introduction to Data Mining Using SAS Enterprise Miner By Patricia Cerrito
Packed with examples from an array of industries, this introductory text provides you with excellent starting points and practical guidelines to begin data
mining today.
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Multivariate Data Reduction and Discrimination with SAS Software By Ravindra Khattree, Ph.D., and Dayanand N. Naik, Ph.D.
Presents conceptual developments, theory, methods, and subsequent data analyses in an integrated manner. Together with Applied Multivariate
Statistics with SAS Software, Second Edition, provides comprehensive information about using SAS for multivariate statistics.
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Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications By Kattamuri Sarma
Step by step, you'll be able to compare manual calculations with the calculations that are performed by SAS Enterprise Miner. Addresses: data collection and data cleaning, decision trees and
regression trees, logistic regression models, and more.
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These references are recommended reading if you're interested in familiarizing yourself with SAS business intelligence.
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Business Intelligence Competency Center: A Team Approach to Maximizing Competitive Advantage By Gloria Miller, Dagmar Bräutigam, and Stefanie Gerlach
Written for anyone interested in understanding the Business Intelligence Competency Center (BICC) concept, this book covers the process of
planning, setting up and running a BICC while also exploring the benefits and potential pitfalls, and reviewing best practices.
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Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy By Olivia Rud
Many books discuss the importance of emotional intelligence in the corporate environment, but this book goes a step further. It looks at components of chaos theory, complex adaptive systems, and quantum physics
to provide a scientific framework for the new corporate examples and explains why these competencies are critical, given the speed of change, globalization, and advancement in technology and business intelligence.
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CIO Best Practices: Enabling Strategic Value with Information Technology By Joe Stenzel
CIO Best Practices is an invaluable resource filled with real-world practices used by CIOs and other IT specialists who have successfully mastered the blend
of business and IT responsibilities.
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Customer Data Integration: Reaching a Single Version of the Truth By Jill Dyche and Evan Levy
This book encompasses the new set of technologies designed to help companies conveniently and cost-efficiently turn the raw material of customer data into
usable, reliable customer information.
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Case Studies in Performance Management: A Guide from the Experts By Tony Adkins
A compilation of eight case studies in Activity-Based Costing (ABC) and Performance Management (PM), with a foreword from Gary Cokins about
their tie into a PM framework.
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Information Revolution: Using the Information Evolution Model to Grow Your Business By Jim Davis, Gloria J. Miller, and Allan Russell
Explains the Information Evolution Model (IEM), a patent-pending framework that encompasses an evolutionary path toward information-management
optimization across four dimensions: people, processes, corporate culture, and infrastructure.
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Performance Management: Finding the Missing Pieces to Close the Intelligence Gap By Gary Cokins, CPIM
Emphasizes that the current analytical tools (balanced scorecard, activity-based management, etc.) have been
tested and are mature, and that their integration is now the big opportunity.
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Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics By Gary Cokins, CPIM
Provides an overview of the current trends in performance management. Unlike other books on the topic, this book, by performance management pioneer Gary Cokins, is not a dry recipe or "how-to" guide; it provides a detailed
discussion of the relevant aspects of performance management.
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* These books are offered by SAS Publishing as a professional resource for SAS users. Concepts related to using SAS are addressed, but SAS examples are not included.