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Bring your data to life and add meaning to your information with Maps Made Easy Using SAS. Abundant real-world examples and a tutorial approach help new users create maps easily and quickly. You will learn the basic mapping components, including map and response data sets as well as simple SAS/GRAPH statements. With in-depth examples you will move on to more advanced mapping techniques, such as annotating maps and producing customized maps and output. The process used to annotate maps is demystified and described in clear, easy-to-follow steps. You will produce data-driven, updatable maps in GIF format for use in Web-based presentations and other applications. Also presented are details on creating more complicated choropleth maps. These include maps that combine geographic areas with internal boundaries removed, maps that display multiple geographic areas, and clipped maps. Enhance your data presentations with this well-organized guide. This book is part of the SAS Press program.
Text addresses such tasks as: viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, and using SAS procedures for scoring.
This indispensable guide focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and output to the Food and Drug Administration.
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 a user-friendly, practice-oriented, introductory text to teach businesspeople, students, and others core statistical concepts and applications. It begins with absolute core principles and takes you through an overview of statistics, data and data collection, an introduction to SAS®, and basic statistics (descriptive statistics and basic associational statistics). The book also provides an overview of statistical modeling, effect size, statistical significance and power testing, basics of linear regression, introduction to comparison of means, basics of chi-square tests for categories, extrapolating statistics to business outcomes, and some topical issues in statistics, such as big data, simulation, machine learning, and data warehousing. The book steers away from complex mathematical-based explanations, and it also avoids basing explanations on the traditional build-up of distributions, probability theory and the like, which tend to lose the practice-oriented reader. Instead, it teaches the core ideas of statistics through methods such as careful, intuitive written explanations, easy-to-follow diagrams, step-by-step technique implementation, and interesting metaphors. With no previous SAS experience necessary, Business Statistics Made Easy in SAS® is an ideal introduction for beginners. It is suitable for introductory undergraduate classes, postgraduate courses such as MBA refresher classes, and for the business practitioner. It is compatible with SAS® University Edition.
Easy-to-read and comprehensive, this book shows how the SAS System performs multivariate time series analysis and features the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. The interrelationship of SAS/ETS procedures is demonstrated with an accompanying discussion of how the choice of a procedure depends on the data to be analysed and the reults desired. Other topics covered include detecting sinusoidal components in time series models and performing bivariate corr-spectral analysis and comparing the results with the standard transfer function methodology. The authors? unique approach to integrating students in a variety of disciplines and industries. Emphasis is on correct interpretation of output to draw meaningful conclusions. The volume, co-pubished by SAS and JWS, features both theory and practicality, and accompanies a soon-to-be extensive library of SAS hands-on manuals in a multitude of statistical areas. The book can be used with a number of hardware-specific computing machines including CMS, Mac, MVS, Opem VMS Alpha, Opmen VMS VAX, OS/390, OS/2, UNIX, and Windows.
Features and capabilities of the REG, ANOVA, and GLM procedures are included in this introduction to analysing linear models with the SAS System. This guide shows how to apply the appropriate procedure to data analysis problems and understand PROC GLM output. Other helpful guidelines and discussions cover the following significant areas: Multivariate linear models; lack-of-fit analysis; covariance and heterogeneity of slopes; a classification with both crossed and nested effects; and analysis of variance for balanced data. This fourth edition includes updated examples, new software-related features, and new material, including a chapter on generalised linear models. Version 8 of the SAS System was used to run the SAS code examples in the book. * Provides clear explanations of how to use SAS to analyse linear models * Includes numerous SAS outputs * Includes new chapter on generalised linear models * Uses version 8 of the SAS system This book assists data analysts who use SAS/STAT software to analyse data using regression analysis and analysis of variance. It assumes familiarity with basic SAS concepts such as creating SAS data sets with the DATA step and manipulating SAS data sets with the procedures in base SAS software.
Navigate the world of the powerful SQL procedure with Katherine Prairie's Essential PROC SQL Handbook for SAS Users. Written in an easy-to-use, logical format, this comprehensive reference focuses on the functionality of the procedure, as well as the accomplishment of common tasks using PROC SQL, enabling readers to quickly develop and enhance their SQL skills. Features include more than 300 examples of PROC SQL code, plus queries and diagrams showing how the statements are processed, tips and techniques highlighting "need-to-know" concepts, and an appendix designed specifically for SQL Pass-Through Facility and SAS/ACCESS users. This practical guide is written for SAS users of all levels who want to learn how to integrate the SQL procedure into their Base SAS and/or SAS/ACCESS programs as well as SQL programmers who want to adapt their current skills to SAS. This book is part of the SAS Press program.
Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.
Robert Allison's SAS/GRAPH: Beyond the Basics collects examples that demonstrate a variety of techniques you can use to create custom graphs using SAS/GRAPH software. SAS/GRAPH is known for its flexibility and power, but few people know how to use it to its full potential. Written for the SAS programmer with experience using Base SAS to work with data, the book includes examples that can be used in a variety of industry sectors. SAS/GRAPH: Beyond the Basics will help you create the exact graph you want.
This book introduces advanced techniques for using PROC SQL in SAS. If you are a SAS programmer, analyst, or student who has mastered the basics of working with SQL, Advanced SQL with SAS® will help take your skills to the next level. Filled with practical examples with detailed explanations, this book demonstrates how to improve performance and speed for large data sets. Although the book addresses advanced topics, it is designed to progress from the simple and manageable to the complex and sophisticated. In addition to numerous tuning techniques, this book also touches on implicit and explicit pass-throughs, presents alternative SAS grid- and cloud-based processing environments, and compares SAS programming languages and approaches including FedSQL, CAS, DS2, and hash programming. Other topics include: Missing values and data quality with audit trails “Blind spots” like how missing values can affect even the simplest calculations and table joins SAS macro language and SAS macro programs SAS functions Integrity constraints SAS Dictionaries SAS Compute Server