Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells,
introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select ...
This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides
valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. Today's businesses increasingly use data to drive decisions ...
Learn or refresh core statistical methods for business with SAS® and approach real business analytics
issues and techniques using a practical approach that avoids complex mathematics and instead employs easy-to-follow explanations. Business Statistics Made Easy in SAS® is designed as ...
Art Carpenter demystifies the powerful REPORT procedure and shows you how to incorporate this highly
flexible and customizable procedure into your SAS reporting programs. Combining his years of SAS experience with a talent for instruction, Art offers clear and comprehensive ...
Carpenter's Guide to Innovative SAS Techniques offers advanced SAS programmers an all-in-one programming reference that
includes advanced topics not easily found outside the depths of SAS documentation or more advanced training classes. Art Carpenter has written fifteen chapters of advanced ...
SAS users in the Health and Life Sciences industry need to create complex graphs to
analyze biostatistics data and clinical data, and they need to submit drugs for approval to the FDA. Graphs used in the HLS industry are complex ...
Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation
for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on ...
Analytics offers many capabilities and options to measure and improve data quality, and SAS is
perfectly suited to these tasks. Gerhard Svolba's Data Quality for Analytics Using SAS focuses on selecting the right data sources and ensuring data quantity, relevancy, ...
