Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries. Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.

Combine complex concepts facing the financial sector with the software toolsets available to analysts.

The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications combines both theoretical explanation and practical applications to define as well as demonstrate how you can build credit risk models using SAS Enterprise Miner and SAS/STAT and apply them into practice.

The ultimate goal of credit risk is to reduce losses through better and more reliable credit decisions that can be developed and deployed quickly. In this example-driven book, Dr. Brown breaks down the required modeling steps and details how this would be achieved through the implementation of SAS Enterprise Miner and SAS/STAT.

Users will solve real-world risk problems as well as comprehensively walk through model development while addressing key concepts in credit risk modeling. The book is aimed at credit risk analysts in retail banking, but its applications apply to risk modeling outside of the retail banking sphere. Those who would benefit from this book include credit risk analysts and managers alike, as well as analysts working in fraud, Basel compliancy, and marketing analytics. It is targeted for intermediate users with a specific business focus and some programming background is required.

Efficient and effective management of the entire credit risk model lifecycle process enables you to make better credit decisions. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications demonstrates how practitioners can more accurately develop credit risk models as well as implement them in a timely fashion.

This book is part of the SAS Press Program.

Grasp essential steps in order to generate meaningful results quickly with JMP.

JMP Essentials: An Illustrated Step-by-Step Guide for New Users, Second 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. In addition, it has eight new detailed sections and 10 new subsections that include creating maps, filtering data, creating dashboards, and working with Excel data, all of which highlight new, useful and basic level enhancements to JMP.

The format of the book is unique. It adopts a show-and-tell design with essential step-by-step instructions and corresponding screen illustrations, which help users quickly see how to generate the desired results. In most cases, each section completes a JMP task, which maximizes the book's utility as a reference. In addition, each chapter contains a family of features that are carefully crafted to first introduce you to basic features and then on to more advanced ones. JMP Essentials: An Illustrated Step-by-Step Guide for New Users, Second Edition is the quickest and most accessible reference book available.

This is part of the SAS Press program.

Businesses rely on career professionals with strong SAS knowledge and skills. Set yourself apart from the competition by earning the only globally recognized credential endorsed by SAS.

The SAS Certification Prep Guide: Advanced Programming for SAS 9, Fourth Edition, prepares you to take the Advanced Programming for SAS 9 exam. Major topics include SQL processing with SAS, the SAS macro language, advanced SAS programming techniques, and optimizing SAS programs, as well as a new chapter on creating functions with PROC FCMP. You will also become familiar with the enhancements and new functionality that are available in SAS 9.

New or experienced SAS users will find this guide to be an invaluable resource that covers the objectives tested on the exam. The text contains quizzes that enable you to test your understanding of material in each chapter. Quiz solutions are included at the end of the book. Candidates must earn the SAS Certified Base Programmer for SAS 9 Credential before taking the SAS Advanced Programming for SAS 9 exam.

You’ll find instructions on how to obtain sample data when accessing SAS through SAS Enterprise Guide, SAS Studio, SAS University Edition, and the SAS windowing environment. This edition provides significant improvements to numerous examples, making the code even more efficient.

Experience is a critical component to becoming a SAS Certified Professional. This comprehensive guide along with training in SAS SQL1, SAS Macro Language 1, and SAS Programming 3 are valuable resources designed to help you prepare for the Advanced SAS Certification exam.

Develop your own multiple-choice tests, score students, produce student rosters (in print form or Excel), and explore item response theory (IRT).

Aimed at nonstatisticians working in education or training, Test Scoring and Analysis Using SAS describes item analysis and test reliability in easy-to-understand terms, and teaches you SAS programming to score tests, perform item analysis, and estimate reliability. Maximizing flexibility, the scoring and analysis programs enable you to analyze tests with multiple versions, define alternate correct responses for selected items, and repeat the scoring with selected items deleted.

You will be guided step-by-step on how to design multiple-choice items, use analysis to improve your tests, and even detect cheating on students’ submitted multiple-choice tests. Other subjects addressed include reading in data from a variety of sources (text files and Excel workbooks, for example), detecting errors in the input data, and producing class rosters in printed form or Excel workbooks. Also included is a chapter on IRT—widely used in education to calibrate and evaluate items in tests in education such as the SAT and GRE—with instructions for running the new SAS procedure PROC IRT.

This book is part of the SAS Press program.

Why does SAS use January 1, 1960 as its arbitrary reference date? How do you convert a value such as 27 January 2003 into a SAS date? How do you put a date into a filename, or label an Excel worksheet with the date?

You'll find the answers to these questions and much more in Derek Morgan's Essential Guide to SAS Dates and Times, Second Edition, which makes it easy to understand how to use and manipulate dates, times, and datetimes in SAS. Updated for SAS 9.4, with additional functions, formats, and capabilities, the Second Edition has a new chapter dedicated to the ISO 8601 standard and the formats and functions that are new to SAS, including how SAS works with Universal Coordinated Time (UTC).

Novice users will appreciate the new "Troubleshooting" appendix, which discusses questions common to newer SAS users in a conversational way and provides clear examples of simple solutions to these questions. Both novice and intermediate users will find the clear, task-based examples on how to accomplish date-related tasks and the detailed explanations of standard formats and functions invaluable. Users working with intervals will appreciate the expanded discussion of the topic, which details the new custom interval capability, among other enhancements to intervals.

Users working with international dates and times will benefit from the detailed discussion of the NLS facility as it relates to dates and times. Included are bonus "Quick Reference Guides" that list both the standard date and time formats and the NLS date and time formats with examples. These guides illustrate how each format displays the same date, time, or datetime, so you can find the format you want to use at a glance.

The Essential Guide to SAS Dates and Times, Second Edition is the most complete and up-to-date collection of examples on how to write complex programs involving dates, times, or datetime values.

This book is part of the SAS Press Program.

Sanjay Matange and Dan Heath's Statistical Graphics Procedures by Example: Effective Graphs Using SAS shows the innumerable capabilities of SAS Statistical Graphics (SG) procedures. The authors begin with a general discussion of the principles of effective graphics, ODS Graphics, and the SG procedures. They then move on to show examples of the procedures' many features. The book is designed so that you can easily flip through it, find the graph you need, and view the code right next to the example. Among the topics included are how to combine plot statements to create custom graphs; customizing graph axes, legends, and insets; advanced features, such as annotation and attribute maps; tips and tricks for creating the optimal graph for the intended usage; real-world examples from the health and life sciences domain; and ODS styles. The procedures in Statistical Graphics Procedures by Example are specifically designed for the creation of analytical graphs. That makes this book a must-read for analysts and statisticians in the health care, clinical trials, financial, and insurance industries. However, you will find that the examples here apply to all fields. This book is part of the SAS Press program.

Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media.

However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS.

This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries.

Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis.

This book is part of the SAS Press program.

Mixed modelling is very useful, and easier than you think! Mixed modelling is now well established as a powerful approach to statistical data analysis. It is based on the recognition of random-effect terms in statistical models, leading to inferences and estimates that have much wider applicability and are more realistic than those otherwise obtained. Introduction to Mixed Modelling leads the reader into mixed modelling as a natural extension of two more familiar methods, regression analysis and analysis of variance. It provides practical guidance combined with a clear explanation of the underlying concepts. Like the first edition, this new edition shows diverse applications of mixed models, provides guidance on the identification of random-effect terms, and explains how to obtain and interpret best linear unbiased predictors (BLUPs). It also introduces several important new topics, including the following: Use of the software SAS, in addition to GenStat and R. Meta-analysis and the multiple testing problem. The Bayesian interpretation of mixed models. Including numerous practical exercises with solutions, this book provides an ideal introduction to mixed modelling for final year undergraduate students, postgraduate students and professional researchers. It will appeal to readers from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, archaeology and geography. Praise for the first edition: "One of the main strengths of the text is the bridge it provides between traditional analysis of variance and regression models and the more recently developed class of mixed models...Each chapter is well-motivated by at least one carefully chosen example...demonstrating the broad applicability of mixed models in many different disciplines...most readers will likely learn something new, and those previously unfamiliar with mixed models will obtain a solid foundation on this topic."— Kerrie Nelson University of South Carolina, in American Statistician, 2007

With a growing number of scientists and engineers using JMP software for design of experiments, there is a need for an example-driven book that supports the most widely used textbook on the subject, Design and Analysis of Experiments by Douglas C. Montgomery. Design and Analysis of Experiments by Douglas Montgomery: A Supplement for Using JMP meets this need and demonstrates all of the examples from the Montgomery text using JMP. In addition to scientists and engineers, undergraduate and graduate students will benefit greatly from this book.
While users need to learn the theory, they also need to learn how to implement this theory efficiently on their academic projects and industry problems. In this first book of its kind using JMP software, Rushing, Karl and Wisnowski demonstrate how to design and analyze experiments for improving the quality, efficiency, and performance of working systems using JMP. Topics include JMP software, two-sample t-test, ANOVA, regression, design of experiments, blocking, factorial designs, fractional-factorial designs, central composite designs, Box-Behnken designs, split-plot designs, optimal designs, mixture designs, and 2 k factorial designs. JMP platforms used include Custom Design, Screening Design, Response Surface Design, Mixture Design, Distribution, Fit Y by X, Matched Pairs, Fit Model, and Profiler.
With JMP software, Montgomery’s textbook, and Design and Analysis of Experiments by Douglas Montgomery: A Supplement for Using JMP, users will be able to fit the design to the problem, instead of fitting the problem to the design. This book is part of the SAS Press program.

Fixed Effects Regression Methods for Longitudinal Data Using SAS, written by Paul Allison, is an invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques. First introduced by economists, fixed effects methods are gaining widespread use throughout the social sciences. Designed to eliminate major biases from regression models with multiple observations (usually longitudinal) for each subject (usually a person), fixed effects methods essentially offer control for all stable characteristics of the subjects, even characteristics that are difficult or impossible to measure. This straightforward and thorough text shows you how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. The theoretical background of each model is explained, and the models are then illustrated with detailed examples using real data. The book contains thorough discussions of the following uses of SAS procedures: PROC GLM for estimating fixed effects linear models for quantitative outcomes, PROC LOGISTIC for estimating fixed effects logistic regression models, PROC PHREG for estimating fixed effects Cox regression models for repeated event data, PROC GENMOD for estimating fixed effects Poisson regression models for count data, and PROC CALIS for estimating fixed effects structural equation models. To gain the most benefit from this book, readers should be familiar with multiple linear regression, have practical experience using multiple regression on real data, and be comfortable interpreting the output from a regression analysis. An understanding of logistic regression and Poisson regression is a plus. Some experience with SAS is helpful, but not required. This book is part of the SAS Press program.

This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data.

This book is part of the SAS Press program.

This IBM® Redbooks® publication highlights TS7700 Virtualization Engine Release 3.1. It is intended for system architects who want to integrate their storage systems for smoother operation. The IBM Virtualization Engine TS7700 offers a modular, scalable, and high-performing architecture for mainframe tape virtualization for the IBM System z® environment. It integrates 3592 Tape Drives, high-performance disks, and a new disk cache subsystem into a storage hierarchy. This storage hierarchy is managed by robust storage management firmware with extensive self-management capability. It includes the following advanced functions: Policy management to control physical volume pooling Cache management Redundant copies, including across a grid network Copy mode control The new IBM Virtualization Engine TS7700 Release 3.1 continues the next generation of TS7700 Virtualization Engine servers for System z tape: IBM Virtualization Engine TS7720 Server Model VEB with 3956-CS9 and 3-TB SAS drives with RAID 6 protection IBM Virtualization Engine TS7740 Server Model V07 with 3956-CC9 with 600-GB SAS drives with RAID 6 protection TS7700 Virtualization Engine Release 3.1 builds on the existing capabilities of the TS7700 family. It also introduces the following capabilities: 8-Gb IBM FICON® adapters for host attachment Up to eight FICON channel host attachments, doubling the previous number of channels available Up to 512 logical path definitions per FICON channel, doubling the previous number of logical paths per channel IBM FlashCopy® for disaster recovery testing Support for a second TS7720 expansion frame attached to a TS7720 system for a total TS7720 system capacity up to 1 PB before compression New Time Delayed Copy policy

Learn everything you need to know to start using business analytics and integrating it throughout your organization. brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. Business Analytics Principles, Concepts, and Applications with SAS They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research. Business Analytics Principles, Concepts, and Applications with SAS

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 that keep them competitive. Especially with the influx of big data, the importance of data analysis to improve every dimension of business cannot be overstated. Data analysts are therefore in demand; however, many hires and prospective hires, although talented with respect to business and statistics, lack the know-how to perform business analytics with advanced statistical software.

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner is a beginner’s guide with clear, illustrated, step-by-step instructions that will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence.

This book is part of the SAS Press program.

Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

Provides comprehensive information about the Base SAS functions and CALL routines.

Provides usage information and examples for the Graph Template Language (GTL). The GTL is the underlying language for the default templates that are provided by SAS for procedures that use ODS Graphics. You can use the GTL either to modify these templates or to create your own highly customized charts and plots. Information covered includes how to combine language elements to build a custom graph, creating panels that contain multiple graphs, managing plot axes, using legends, modifying style elements to control appearance characteristics, and using functions, expressions, and conditional processing.

Explains how to increase the modularity, flexibility, and maintainability of your SAS code using the SAS macro facility. Provides complete information about macro language elements, interfaces between the SAS macro facility and other parts of SAS software, and macro processing in general.

Provides comprehensive reference information for the statistical graphics (SG) family of procedures. These procedures include the SGPANEL, SGPLOT, SGSCATTER, SGDESIGN, and SGRENDER procedures. These procedures use ODS Graphics functionality to produce plots for exploratory data analysis and customized statistical displays.