A leading guide for performing statistical analyses including analyzing categorical data, factor analysis, logistic regression, and psychometrics.

Learn how to perform basic statistical analyses using the powerful JMP software.

Shows how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields.

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.

SAS For Dummies is the introductory title in the fun and easy Dummies format to get up and running using SAS 9, SAS's statistical and data analysis software.

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

Demonstrates how to use SAS to perform basic statistical analysis including creating a data set with SAS; summarizing data with descriptive statistics, frequency tables, bar charts, and more.

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

Discover how easy it is to perform statistical analysis using the power of SAS Enterprise Guide.

Explains the following topics in easy-to-understand terms: exploratory factor analysis, principal component analysis, developing measurement models with confirmatory factor analysis, and more.

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

Introduces you to SAS software and leads you through a variety of elementary statistical analyses commonly used in the social and behavioral sciences.
Exercises included.

Step-by-step instructions illustrated with examples from actual trials and case studies that serve to define a statistical method and its relevance in a clinical trials setting and to illustrate how to implement the method rapidly and efficiently using the power of SAS software.

This example-driven book illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros.

Demonstrates how you can use SAS and SAS/Genetics to extract answers from your quantitative and molecular genetics data.

This essential new book offers extensive coverage of cutting-edge biostatistical methodology used in drug development and the practical problems facing today's drug developers.

Provides detailed and practical guidance for conducting Monte Carlo studies using SAS.

A real-world reference guide for clinical trial SAS programming, packed with solutions that programmers can apply to their day-to-day problems.

Presents the theory and methods of survival analysis along with excellent discussions of the SAS procedures used to implement the methods described.

Written for anyone interested in understanding the Business Intelligence Competency Center (BICC) concept, this book covers the process of planning, setting up and running a BICC while also exploring the benefits and potential pitfalls, and reviewing best practices.

CIO Best Practices is an invaluable resource filled with real-world practices used by CIOs and other IT specialists who have successfully mastered the blend of business and IT responsibilities.

This book encompasses the new set of technologies designed to help companies conveniently and cost-efficiently turn the raw material of customer data into usable, reliable customer information.

A compilation of eight case studies in Activity-Based Costing (ABC) and Performance Management (PM), with a foreword from Gary Cokins about their tie into a PM framework.

Explains the Information Evolution Model (IEM), a patent-pending framework that encompasses an evolutionary path toward information-management optimization across four dimensions: people, processes, corporate culture, and infrastructure.

Emphasizes that the current analytical tools (balanced scorecard, activity-based management, etc.) have been tested and are mature, and that their integration is now the big opportunity.