SAS/STAT User's Guide, Version 7-1
Author: SAS Institute Staff
Publisher:
Published: 1994-04-01
Total Pages: 788
ISBN-13: 9781580254274
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SAS Statistics by Example
Author: Ron Cody, EdD
Publisher: SAS Institute
Published: 2011-08-22
Total Pages: 275
ISBN-13: 1612900127
DOWNLOAD EBOOKIn SAS Statistics by Example, Ron Cody offers up 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. For each statistical task, Cody includes heavily annotated examples using ODS Statistical Graphics procedures such as SGPLOT, SGSCATTER, and SGPANEL that show how SAS can produce the required statistics. Also, you will learn how to test the assumptions for all relevant statistical tests. Major topics featured include descriptive statistics, one- and two-sample tests, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and sample size. This is not a book that teaches statistics. Rather, SAS Statistics by Example is perfect for intermediate to advanced statistical programmers who know their statistics and want to use SAS to do their analyses. This book is part of the SAS Press program.
A Handbook of Statistical Graphics Using SAS ODS
Author: Geoff Der
Publisher: CRC Press
Published: 2014-08-15
Total Pages: 250
ISBN-13: 1466599030
DOWNLOAD EBOOKEasily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4. The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures. Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.
Learning SAS by Example
Author: Ron Cody
Publisher: SAS Institute
Published: 2018-07-03
Total Pages: 536
ISBN-13: 1635266564
DOWNLOAD EBOOKLearn to program SAS by example! Learning SAS by Example, A Programmer’s Guide, Second Edition, teaches SAS programming from very basic concepts to more advanced topics. Because most programmers prefer examples rather than reference-type syntax, this book uses short examples to explain each topic. The second edition has brought this classic book on SAS programming up to the latest SAS version, with new chapters that cover topics such as PROC SGPLOT and Perl regular expressions. This book belongs on the shelf (or e-book reader) of anyone who programs in SAS, from those with little programming experience who want to learn SAS to intermediate and even advanced SAS programmers who want to learn new techniques or identify new ways to accomplish existing tasks. In an instructive and conversational tone, author Ron Cody clearly explains each programming technique and then illustrates it with one or more real-life examples, followed by a detailed description of how the program works. The text is divided into four major sections: Getting Started, DATA Step Processing, Presenting and Summarizing Your Data, and Advanced Topics. Subjects addressed include Reading data from external sources Learning details of DATA step programming Subsetting and combining SAS data sets Understanding SAS functions and working with arrays Creating reports with PROC REPORT and PROC TABULATE Getting started with the SAS macro language Leveraging PROC SQL Generating high-quality graphics Using advanced features of user-defined formats and informats Restructuring SAS data sets Working with multiple observations per subject Getting started with Perl regular expressions You can test your knowledge and hone your skills by solving the problems at the end of each chapter.
SAS/STAT 9.1
Author: SAS Institute
Publisher: SAS institute
Published: 2004
Total Pages: 0
ISBN-13: 9781590472439
DOWNLOAD EBOOKSAS/STAT software provides extensive statistical capabilities with tools for both specialized and enterprise-wide analytical needs. It can help you analyze data and make informed decisions for research, engineering, manufacturing, medical, and business applications. This user's guide provides the latest, detailed reference material for the procedures in SAS/STAT, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, nonparametric analysis, and survey data analysis. Also included are syntax and usage information, examples, and a discussion of the use of the Output Delivery System with the statistical software. New chapters for SAS 9.1 describe software for power and sample size computations, robust regression, multiple imputation, crosstabulations, table analysis, and logistic regression for survey data. Many other chapters have been updated with SAS 9.1 enhancements. This title is also available online. This title serves as a reference guide for both novice and expert users of SAS/STAT software. Supports releases 9.1 and higher of SAS software.
Basic Statistics Using SAS Enterprise Guide
Author: Geoff Der
Publisher: SAS Press
Published: 2007
Total Pages: 226
ISBN-13: 9781599945736
DOWNLOAD EBOOKEmphasizing the practical aspects of SAS analysis, this example-rich guide shows users how to conduct a wide range of statistical analyses without any SAS programming required. Exercises at the end of each chapter help readers consolidate what they have learned.
SAS for R Users
Author: Ajay Ohri
Publisher: John Wiley & Sons
Published: 2019-09-24
Total Pages: 210
ISBN-13: 1119256410
DOWNLOAD EBOOKBRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER SAS and R are widely-used, very different software environments. Prized for its statistical and graphical tools, R is an open-source programming language that is popular with statisticians and data miners who develop statistical software and analyze data. SAS (Statistical Analysis System) is the leading corporate software in analytics thanks to its faster data handling and smaller learning curve. SAS for R Users enables entry-level data scientists to take advantage of the best aspects of both tools by providing a cross-functional framework for users who already know R but may need to work with SAS. Those with knowledge of both R and SAS are of far greater value to employers, particularly in corporate settings. Using a clear, step-by-step approach, this book presents an analytics workflow that mirrors that of the everyday data scientist. This up-to-date guide is compatible with the latest R packages as well as SAS University Edition. Useful for anyone seeking employment in data science, this book: Instructs both practitioners and students fluent in one language seeking to learn the other Provides command-by-command translations of R to SAS and SAS to R Offers examples and applications in both R and SAS Presents step-by-step guidance on workflows, color illustrations, sample code, chapter quizzes, and more Includes sections on advanced methods and applications Designed for professionals, researchers, and students, SAS for R Users is a valuable resource for those with some knowledge of coding and basic statistics who wish to enter the realm of data science and business analytics.
SAS/STAT User's Guide
Author: SAS Institute
Publisher:
Published: 1999
Total Pages: 1324
ISBN-13:
DOWNLOAD EBOOKThis title provides the latest, detailed reference material for all of the procedures in SAS/STAT software, and syntax, usage, and examples.
The Little SAS Book
Author: Lora D. Delwiche
Publisher: SAS Institute
Published: 2019-10-11
Total Pages: 512
ISBN-13: 1642953431
DOWNLOAD EBOOKA classic that just keeps getting better, The Little SAS Book is essential for anyone learning SAS programming. Lora Delwiche and Susan Slaughter offer a user-friendly approach so that readers can quickly and easily learn the most commonly used features of the SAS language. Each topic is presented in a self-contained, two-page layout complete with examples and graphics. Nearly every section has been revised to ensure that the sixth edition is fully up-to-date. This edition is also interface-independent, written for all SAS programmers whether they use SAS Studio, SAS Enterprise Guide, or the SAS windowing environment. New sections have been added covering PROC SQL, iterative DO loops, DO WHILE and DO UNTIL statements, %DO statements, using variable names with special characters, the ODS EXCEL destination, and the XLSX LIBNAME engine. This title belongs on every SAS programmer's bookshelf. It's a resource not just to get you started, but one you will return to as you continue to improve your programming skills. Learn more about the updates to The Little SAS Book, Sixth Edition here. Reviews for The Little SAS Book, Sixth Edition can be read here.
SAS and R
Author: Ken Kleinman
Publisher: CRC Press
Published: 2009-07-21
Total Pages: 325
ISBN-13: 1420070592
DOWNLOAD EBOOKAn All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, id
