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Author: Vishesh Dhingra Publisher: Orange Education Pvt Ltd ISBN: 8197396647 Category : Computers Languages : en Pages : 282
Book Description
TAGLINE Elevate Your Data Analytics Skills, Optimize Workflows, and Drive Informed Decision-Making Across the Spectrum of Data Professions! KEY FEATURES ● Solve practical problems using SAS with real-world case studies that provide hands-on experience. ● Clear, step-by-step tutorials that guide you through various SAS procedures, ensuring easy understanding and application. ● Explore an extensive range of SAS capabilities, from basic data management to advanced analytics and reporting techniques. DESCRIPTION The "Ultimate Statistical Analysis System (SAS) for Data Analytics" is your go-to resource for mastering SAS, a powerful software suite for statistical analysis. This comprehensive book covers everything from the basics of SAS for data professionals to advanced topics like clustering analysis and association rules. With practical examples and clear explanations, this book equips readers with the knowledge and skills needed to excel in their roles as data scientists, analysts, researchers, and more. Whether you're a beginner looking to build a solid foundation in SAS or an experienced user seeking to expand your proficiency, this handbook has something for everyone. You'll learn essential techniques for importing, cleaning, and visualizing data, as well as conducting hypothesis testing, regression analysis, and inferential statistics. Advanced topics like SAS programming concepts and generating reports are also covered in detail, providing readers with the tools to tackle complex data challenges with confidence. With its accessible writing style and emphasis on real-world applications, this book is a practical guide that empowers readers to unlock the full potential of their data. Whether you're analyzing customer behavior, optimizing business processes, or conducting academic research, this handbook will be your trusted companion on the journey to mastering SAS and making informed decisions based on data-driven insights. WHAT WILL YOU LEARN ● Master the skills to import, clean, and transform data using SAS's powerful data manipulation tools. ● Gain the ability to conduct hypothesis testing to build regression models to analyze data relationships. ● Learn to design and produce compelling data visualizations that effectively communicate your data findings. ● Develop proficiency in advanced SAS programming techniques to tackle intricate analytical tasks. ● Discover the use of clustering analysis and association rules to identify meaningful patterns and relationships in your data. ● Generate professional reports to clearly present your analytical results. WHO IS THIS BOOK FOR? This book is ideal for data professionals, analysts, researchers, and anyone seeking to enhance their statistical analysis skills with SAS. Prior familiarity with basic statistical concepts and some experience with data analysis tools would be beneficial for readers to fully leverage the content of this handbook. TABLE OF CONTENTS 1. Introduction to SAS for Data Professionals 2. Data Import and Export in SAS 3. Data Cleaning and Transformation 4. Data Visualizations with SAS 5. Hypothesis Testing and Regression Analysis 6. Descriptive and Inferential Statistics 7. Advanced SAS Programming Concepts 8. Clustering Analysis with PROC CLUSTER 9. Association Rules in SAS 10. Generating Reports in SAS Index
Author: Vishesh Dhingra Publisher: Orange Education Pvt Ltd ISBN: 8197396647 Category : Computers Languages : en Pages : 282
Book Description
TAGLINE Elevate Your Data Analytics Skills, Optimize Workflows, and Drive Informed Decision-Making Across the Spectrum of Data Professions! KEY FEATURES ● Solve practical problems using SAS with real-world case studies that provide hands-on experience. ● Clear, step-by-step tutorials that guide you through various SAS procedures, ensuring easy understanding and application. ● Explore an extensive range of SAS capabilities, from basic data management to advanced analytics and reporting techniques. DESCRIPTION The "Ultimate Statistical Analysis System (SAS) for Data Analytics" is your go-to resource for mastering SAS, a powerful software suite for statistical analysis. This comprehensive book covers everything from the basics of SAS for data professionals to advanced topics like clustering analysis and association rules. With practical examples and clear explanations, this book equips readers with the knowledge and skills needed to excel in their roles as data scientists, analysts, researchers, and more. Whether you're a beginner looking to build a solid foundation in SAS or an experienced user seeking to expand your proficiency, this handbook has something for everyone. You'll learn essential techniques for importing, cleaning, and visualizing data, as well as conducting hypothesis testing, regression analysis, and inferential statistics. Advanced topics like SAS programming concepts and generating reports are also covered in detail, providing readers with the tools to tackle complex data challenges with confidence. With its accessible writing style and emphasis on real-world applications, this book is a practical guide that empowers readers to unlock the full potential of their data. Whether you're analyzing customer behavior, optimizing business processes, or conducting academic research, this handbook will be your trusted companion on the journey to mastering SAS and making informed decisions based on data-driven insights. WHAT WILL YOU LEARN ● Master the skills to import, clean, and transform data using SAS's powerful data manipulation tools. ● Gain the ability to conduct hypothesis testing to build regression models to analyze data relationships. ● Learn to design and produce compelling data visualizations that effectively communicate your data findings. ● Develop proficiency in advanced SAS programming techniques to tackle intricate analytical tasks. ● Discover the use of clustering analysis and association rules to identify meaningful patterns and relationships in your data. ● Generate professional reports to clearly present your analytical results. WHO IS THIS BOOK FOR? This book is ideal for data professionals, analysts, researchers, and anyone seeking to enhance their statistical analysis skills with SAS. Prior familiarity with basic statistical concepts and some experience with data analysis tools would be beneficial for readers to fully leverage the content of this handbook. TABLE OF CONTENTS 1. Introduction to SAS for Data Professionals 2. Data Import and Export in SAS 3. Data Cleaning and Transformation 4. Data Visualizations with SAS 5. Hypothesis Testing and Regression Analysis 6. Descriptive and Inferential Statistics 7. Advanced SAS Programming Concepts 8. Clustering Analysis with PROC CLUSTER 9. Association Rules in SAS 10. Generating Reports in SAS Index
Author: Mervyn G. Marasinghe Publisher: Springer Science & Business Media ISBN: 038777372X Category : Mathematics Languages : en Pages : 562
Book Description
This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.
Author: Geoff Der Publisher: CRC Press ISBN: 1466599030 Category : Mathematics Languages : en Pages : 250
Book Description
Easily 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.
Author: Lora D. Delwiche Publisher: SAS Institute ISBN: 1642953431 Category : Computers Languages : en Pages : 512
Book Description
A 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.
Author: Ken Kleinman Publisher: CRC Press ISBN: 1420070592 Category : Mathematics Languages : en Pages : 325
Book Description
An 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
Author: Ajay Ohri Publisher: John Wiley & Sons ISBN: 1119256410 Category : Computers Languages : en Pages : 210
Book Description
BRIDGES 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.
Author: Charles DiMaggio Publisher: Springer Science & Business Media ISBN: 1461448549 Category : Mathematics Languages : en Pages : 266
Book Description
This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude of examples. It is directly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a “hands on” approach to the use of SAS for a broad number of epidemiologic analyses, readers learn techniques for data entry and cleaning, categorical analysis, ANOVA, and linear regression and much more. Exercises utilizing real-world data sets are featured throughout the book. SAS screen shots demonstrate the steps for successful programming. SAS (Statistical Analysis System) is an integrated system of software products provided by the SAS institute, which is headquartered in California. It provides programmers and statisticians the ability to engage in many sophisticated statistical analyses and data retrieval and mining exercises. SAS is widely used in the fields of epidemiology and public health research, predominately due to its ability to reliably analyze very large administrative data sets, as well as more commonly encountered clinical trial and observational research data.
Author: Taylor H. Lewis Publisher: CRC Press ISBN: 1498776809 Category : Mathematics Languages : en Pages : 341
Book Description
Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.
Author: Carlos Andre Reis Pinheiro Publisher: SAS Institute ISBN: 1953329624 Category : Computers Languages : en Pages : 169
Book Description
Boost your understanding of data science techniques to solve real-world problems Data science is an exciting, interdisciplinary field that extracts insights from data to solve business problems. This book introduces common data science techniques and methods and shows you how to apply them in real-world case studies. From data preparation and exploration to model assessment and deployment, this book describes every stage of the analytics life cycle, including a comprehensive overview of unsupervised and supervised machine learning techniques. The book guides you through the necessary steps to pick the best techniques and models and then implement those models to successfully address the original business need. No software is shown in the book, and mathematical details are kept to a minimum. This allows you to develop an understanding of the fundamentals of data science, no matter what background or experience level you have.
Author: Matthew Windham Publisher: SAS Institute ISBN: 1635267099 Category : Computers Languages : en Pages : 193
Book Description
Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products.
Author: Vishesh Dhingra
Author: Vishesh Dhingra
Author: Mervyn G. Marasinghe
Author: Geoff Der
Author: Lora D. Delwiche
Author: Ken Kleinman
Author: Ajay Ohri
Author: Charles DiMaggio
Author: Taylor H. Lewis
Author: Carlos Andre Reis Pinheiro
Author: Matthew Windham