handbook of sas r data step programming

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Handbook Of Sas Data Step Programming

Author : Arthur Li
ISBN : 9781466552395
Genre : Mathematics
File Size : 25. 51 MB
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To write an accomplished program in the DATA step of SAS®, programmers must understand programming logic and know how to implement and even create their own programming algorithm. Handbook of SAS® DATA Step Programming shows readers how best to manage and manipulate data by using the DATA step. The book helps novices avoid common mistakes resulting from a lack of understanding fundamental and unique SAS programming concepts. It explains that learning syntax does not solve all problems; rather, a thorough comprehension of SAS processing is needed for successful programming. The author also guides readers through a programming task. In most of the examples, the author first presents strategies and steps for solving the problem, then offers a solution, and finally gives a more detailed explanation of the solution. Understanding the DATA steps, particularly the program data vector (PDV), is critical to proper data manipulation and management in SAS. This book helps SAS programmers thoroughly grasp the concept of DATA step processing and write accurate programs in the DATA step. Numerous supporting materials, including data sets and programs used in the text, are available on the book’s CRC Press web page.

Sas Macro Programming Made Easy Third Edition

Author : Michele M Burlew
ISBN : 1635269075
Genre :
File Size : 36. 78 MB
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This book provides beginners with a thorough foundation in SAS macro programming. The macro facility is a popular part of SAS. Macro programming is a required skill for many SAS programming jobs, and the SAS Advanced Programming Certification Exam tests macro processing concepts. Whether you're looking to become certified, land a job, or increase your skills, you'll benefit from SAS Macro Programming Made Easy, Third Edition. By following Michele Burlew's examples and step-by-step instructions, you'll be able to rapidly perform repetitive programming tasks, to pass information between programming steps more easily, and to make your programming easier to read. Updated for SAS 9.4, this book teaches you the elements of the macro facility (macro variables, macro programs, macro language), 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. Beginning macro programmers will learn to write SAS macro programs quickly and efficiently. More experienced programmers will find this book useful to refresh their conceptual knowledge and expand on their macro programming skills. Ultimately, any user interested in automating their programs-including analysts, programmers, and report writers-will find Michele Burlew's book an excellent tutorial. This book is part of the SAS Press program.

The Data Science Handbook

Author : Field Cady
ISBN : 9781119092940
Genre : Mathematics
File Size : 77. 69 MB
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A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

R In A Nutshell

Author : Joseph Adler
ISBN : 9783897216501
Genre : Computers
File Size : 22. 88 MB
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Wozu sollte man R lernen? Da gibt es viele Gründe: Weil man damit natürlich ganz andere Möglichkeiten hat als mit einer Tabellenkalkulation wie Excel, aber auch mehr Spielraum als mit gängiger Statistiksoftware wie SPSS und SAS. Anders als bei diesen Programmen hat man nämlich direkten Zugriff auf dieselbe, vollwertige Programmiersprache, mit der die fertigen Analyse- und Visualisierungsmethoden realisiert sind – so lassen sich nahtlos eigene Algorithmen integrieren und komplexe Arbeitsabläufe realisieren. Und nicht zuletzt, weil R offen gegenüber beliebigen Datenquellen ist, von der einfachen Textdatei über binäre Fremdformate bis hin zu den ganz großen relationalen Datenbanken. Zudem ist R Open Source und erobert momentan von der universitären Welt aus die professionelle Statistik. R kann viel. Und Sie können viel mit R machen – wenn Sie wissen, wie es geht. Willkommen in der R-Welt: Installieren Sie R und stöbern Sie in Ihrem gut bestückten Werkzeugkasten: Sie haben eine Konsole und eine grafische Benutzeroberfläche, unzählige vordefinierte Analyse- und Visualisierungsoperationen – und Pakete, Pakete, Pakete. Für quasi jeden statistischen Anwendungsbereich können Sie sich aus dem reichen Schatz der R-Community bedienen. Sprechen Sie R! Sie müssen Syntax und Grammatik von R nicht lernen – wie im Auslandsurlaub kommen Sie auch hier gut mit ein paar aufgeschnappten Brocken aus. Aber es lohnt sich: Wenn Sie wissen, was es mit R-Objekten auf sich hat, wie Sie eigene Funktionen schreiben und Ihre eigenen Pakete schnüren, sind Sie bei der Analyse Ihrer Daten noch flexibler und effektiver. Datenanalyse und Statistik in der Praxis: Anhand unzähliger Beispiele aus Medizin, Wirtschaft, Sport und Bioinformatik lernen Sie, wie Sie Daten aufbereiten, mithilfe der Grafikfunktionen des lattice-Pakets darstellen, statistische Tests durchführen und Modelle anpassen. Danach werden Ihnen Ihre Daten nichts mehr verheimlichen.

Sas Programming For Researchers And Social Scientists

Author : Paul E. Spector
ISBN : 0761922687
Genre : Computers
File Size : 88. 85 MB
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This book provides instruction about how to write computer programs using SAS language. It focuses on common programming tasks frequently encountered in conducting data analysis; and provides advice about how to learn the SAS lanuguage and how to use it efficiently.

Handbook Of Research On Educational Communications And Technology

Author : J. Michael Spector
ISBN : 9781461431855
Genre : Education
File Size : 75. 67 MB
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The 4th edition of the Handbook of Research on Educational Communications and Technology expands upon the previous 3 versions, providing a comprehensive update on research pertaining to new and emerging educational technologies. Chapters that are no longer pertinent have been eliminated in this edition, with most chapters being completely rewritten, expanded, and updated Additionally, new chapters pertaining to research methodologies in educational technology have been added due to expressed reader interest. Each chapter now contains an extensive literature review, documenting and explaining the most recent, outstanding research, including major findings and methodologies employed. The Handbook authors continue to be international leaders in their respective fields; the list is cross disciplinary by design and great effort was taken to invite authors outside of the traditional instructional design and technology community.

The Oxford Handbook Of Quantitative Methods In Psychology Vol 2

Author : Todd D. Little
ISBN : 9780199934898
Genre : Medical
File Size : 84. 86 MB
Format : PDF
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The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.

The Sas Programmer S Proc Report Handbook Basic To Advanced Reporting Techniques

Author : Jane Eslinger
ISBN : 9781629602103
Genre : Computers
File Size : 82. 55 MB
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The SAS Programmer's PROC REPORT Handbook: Basic to Advanced Reporting Techniques is intended for programmers of all skill levels. Learn how to link multiple reports, add graphics and logos, and manipulate table of contents values to help refine your programs, macrotize where possible, troubleshoot easily, and get great-looking reports every time. From beginner to advanced, the examples in this book will help you harness all the power and capability of PROC REPORT. With dozens of useful examples, this book is completely unique in three ways. First, this book describes the default behavior of table of contents nodes and labels, and how to change the nodes inside of PROC REPORT. The chapter also explains how to use PROC DOCUMENT in conjunction with PROC REPORT. Secondly, an entire chapter is dedicated to the troubleshooting of errors, warnings, and notes that are produced by PROC REPORT, including explanations of what generated the log message and how to avoid it. Third, the book explains how to preprocess your data in order to get the best output from PROC REPORT, and it explores reports that require multiple steps to create. Whether you work in banking/finance, pharmaceuticals, the health and life sciences, or government, this handbook is sure to be your new favorite reporting reference.

R F R Dummies

Author : Andrie de Vries
ISBN : 9783527812523
Genre : Computers
File Size : 69. 48 MB
Format : PDF, Docs
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A Handbook Of Statistical Analyses Using R

Author : Torsten Hothorn
ISBN : 1420010654
Genre : Mathematics
File Size : 69. 98 MB
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R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

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