Stack of SAS books

SAS® Upcoming Titles

SAS® for R Users (free e-Book)

SAS® Programming for R Users (Free e-Book) 

By Jordan Bakerman
Anticipated publication date: Fourth quarter 2019

This book is designed for experienced R users who want to transfer their programming skills to SAS. Emphasis is on programming and not statistical theory or interpretation. You will learn how to write programs in SAS that replicate familiar functions and capabilities in R. You will also learn how to call R from SAS using IML. 

Exercises and Projects for The Little SAS® Book: A Primer, Sixth Edition

By Rebecca OttesenLora Delwiche, and Susan Slaughter
Anticipated publication date:  First quarter 2020

The best-selling workbook companion to The Little SAS Book, Exercises and Projects for The Little SAS® Book, Sixth Edition will be updated to match the updates to the new The Little SAS® Book: A Primer, Sixth Edition. This hands-on workbook is designed to hone your SAS skills whether you are a student or a professional.

Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS

Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS®

By Douglas Faries, Xiang Zhang, Zbigniew Kadziola, Uwe Siebert, Felicitas Kuehne, Robert L. Obenchain, and Josep Maria Haro
Anticipated publication date: First quarter 2020

Real world health care data from observational studies, pragmatic trials, patient registries, and databases is common and growing in use. Real World Health Care Data Analysis: Causal Methods and Implementation in SAS® brings together best practices for causal-based comparative effectiveness analyses based on real world data in a single location. Example SAS code is provided to make the analyses relatively easy and efficient. The book also presents several emerging topics of interest, including algorithms for personalized medicine, methods that address the complexities of time varying confounding, extensions of propensity scoring to comparisons between more than two interventions, sensitivity analyses for unmeasured confounding, and implementation of model averaging.

Intelligence at the Edge: Using SAS with the Internet of Things

Intelligence at the Edge: Using SAS® with the Internet of Things 

Edited by Michael Harvey
Anticipated publication date: Second quarter 2020

The upcoming edited collection by Michael Harvey begins with a brief description of the Internet of Things, how it has evolved over time, and why it is important along with incorporating SAS’s role in the IoT space. The book will continue with a collection of chapters showcasing SAS’s expertise in IoT analytics. Topics include Using SAS Event Stream Processing to Process Real World Events, Connectivity, Using the ESP Geofence window, Applying Analytics to Streaming Data including case study examples, Using SAS Event Stream Processing in a typical IoT Reference Architecture, The Role of SAS Event Stream Manager in managing ESP deployments in an IoT ecosystem, How to Use Deep Learning with Your IoT Digital, Accounting for Data Quality Variability in Streaming GPS Data for Location-based Analytics, and more! 

JMP® Essentials: An Illustrated Step-by-Step Guide for New Users, Third Edition

JMP® Essentials: An Illustrated Guide for New Users, Third Edition

By Curt Hinrichs, Chuck Boiler, and Susan Walsh
Anticipated publication date: Second quarter 2020

Updated to showcase the new features of JMP 15, JMP Essentials: An Illustrated Guide for New Users, Third Edition is designed for the new or occasional JMP user who needs to generate meaningful graphs or results quickly. Drawing on their own experience working with these customers, the authors provide essential steps for what new users typically need to carry out with JMP. This newest edition has all new instructions and screen shots reflecting the latest release of JMP software. 

Smart Data Discovery with SAS Visual Analytics

Smart Data Discovery with SAS® Visual Analytics

By Felix Liao
Anticipated pubication date: Second quarter 2020

The purpose of this book is to present these related concepts in a cohesive, simple and practical manner and equip the readers with the necessary knowledge and skill to take their data discovery to the next level using SAS Visual Analytics. Topics covered include a high-level overview of SAS Visual Analytics (the user interface, key features and various foundational concepts that are critical in supporting subsequent chapters) as well as applications of smart data discovery techniques. This will include multiple sections that provide relevant theories, business context and detailed guidance on how to build and interpret these advanced charts using SAS Visual Analytics such as

  • Beyond basic visualizations
  • Correlation
  • Prediction (Linear Regression, Logistic Regression, Decision Trees)

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