Stack of SAS books

SAS® Upcoming Titles

Building Regression Models with SAS®: A Guide for Data Scientists

By Robert N. Rodriguez
Anticipated publication date: First quarter 2023

This book will provide readers with a high-level awareness and understanding of newer regression modeling procedures in SAS that are valuable for supervised machine learning, predictive analytics, and statistical modeling. This book will explain the relative benefits of these procedures, introduce the procedures with basic examples, and help users navigate to procedures and methods that meet their needs. The audience for this book includes newcomers to SAS—in particular, data scientists—who might have encountered some of the methods in open source software and are unaware of what SAS offers. The audience also includes longtime SAS users who are familiar with the REG procedure but have not kept up with the availability of newer and more effective procedures in SAS/STAT and SAS Viya.

Fundamentals of Predictive Analytics with JMP®, Third Edition

By Ron Klimberg
Anticipated publication date: First quarter 2023

This updated and expanded third edition of Fundamentals of Predictive Analytics with JMP® bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the theoretical foundation, this book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis.

Operations Research for Social Good: A Practitioner’s Introduction Using SAS® and Python

By Natalia Summerville and Rob Pratt
Anticipated publication date: Second quarter 2023

Latest technological advances allow data analytics practitioners to solve large problems better and faster with state-of-art Artificial Intelligence (AI) tools. At the same time, humanity faces overarching challenges such as climate crisis, children malnutrition, systemic racism, global pandemics, among others. Fortunately, technological advances in AI can support solution development for current world challenges. This book’s purpose is to expand Operations Research (OR) applications for social good by applying OR methodologies typically required in engineering curricula to applications targeted to make this world a better place. This book also provides skills to model and solve OR problems with both SAS and Python as well as practical tools and tips to bridge the gap between academic learning and real-world implementations.

Practitioner’s Guide to Operationalizing Data Governance

By Mary Anne Hopper
Anticipated publication date: Second quarter 2023

This book will reflect SAS’s proven methodology for creating sustainable data governance programs. The book will explore where most organizations are challenged in program development and provide practical, actionable advice to help readers understand pitfalls and a path forward.