Real-world problems and data sets provide a unique approach to the topic: integrating statistical methods, data analysis, and applications.

Provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries.

This example-rich guide shows you how to conduct a wide range of statistical analyses with no SAS programming required.

Addresses tasks that nearly every SAS programmer needs to do: make sure that data errors are located and corrected.

Bridging the gap between statistics texts and SAS documentation, this book is written for those who want to perform analyses to solve problems.

Learn how to harness the power of Regular Expressions within the SAS programming language for a wide array of everyday applications of unstructured data analyses.

If you like learning by example, then this straightforward book makes it easy to learn SAS programming.

Gently introduces you to the most commonly used features of SAS software with clear explanations and examples.

This guide helps you quickly become familiar with the SAS Enterprise Guide point-and-click environment.

Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. It provides both theoretical background and practical solutions for those working with incomplete data sets in an engaging example-driven format.

Create a wide variety of professional reports with real-world examples. SAS users from all disciplines will gain valuable insight and turn seemingly complex reporting tasks into a matter of practice.

Uses a tutorial approach and plenty of examples to lead you through methods related to analysis of variance with fixed and random effects.

Describes the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures

A cookbook approach for doing statistics with SAS. Structured specifically around the most commonly used statistical tasks or techniques--for example, comparing two means, ANOVA, and regression--this book provides an easy-to-follow, how-to approach to statistical analysis not found in other books.

Updated for SAS 9.4, this book teaches you the elements of the macro facility, how to write a macro program, techniques for macro programming, tips on using the macro facility, how the macro facility fits into SAS, and about the interfaces between the macro facility and other components of SAS.

An example-driven guide that shows how to perform a wide variety of regression analyses using SAS software.

A how-to book for statistical programmers who use SAS software and who want to simulate data efficiently.

Integrates SAS tools with interesting statistical applications. Uses SAS 9.2 to introduce programming ideas for statistical analysis, data management, and data display and simulation.

Structural equation modeling has become one of the most important statistical procedures in the social and behavioral sciences. This single user-friendly volume, gently guides users through performing some of the most sophisticated data analysis procedures used by researchers today.

Updated for SAS 9, this second edition is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics.

Intended for high school and introductory college-level statistics courses, this book demonstrates JMP and offers the latest research on best practices in teaching statistics using JMP.

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

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.