Time Series Analysis Using Sas Enterprise Guide
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Time Series Analysis Using Sas Enterprise Guide
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Author : Timina Liu
language : en
Publisher: Springer Nature
Release Date : 2020-02-19
Time Series Analysis Using Sas Enterprise Guide written by Timina Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-19 with Computers categories.
This is the first book to present time series analysis using the SAS Enterprise Guide software. It includes some starting background and theory to various time series analysis techniques, and demonstrates the data analysis process and the final results via step-by-step extensive illustrations of the SAS Enterprise Guide software. This book is a practical guide to time series analyses in SAS Enterprise Guide, and is valuable resource that benefits a wide variety of sectors.
Data Preparation For Analytics Using Sas
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Author : Gerhard Svolba
language : en
Publisher: SAS Institute
Release Date : 2006-11-27
Data Preparation For Analytics Using Sas written by Gerhard Svolba and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-27 with Computers categories.
Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include 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, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!
Applied Data Mining For Forecasting Using Sas
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Author : Tim Rey
language : en
Publisher: SAS Institute
Release Date : 2012-07-02
Applied Data Mining For Forecasting Using Sas written by Tim Rey and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-02 with Computers categories.
Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input variables for time series regression models in environments when the number of candidates is large, and identifies the correlation structure between selected candidate inputs and the forecast variable. This book is essential for forecasting practitioners who need to understand the practical issues involved in applied forecasting in a business setting. Through numerous real-world examples, the authors demonstrate how to effectively use SAS software to meet their industrial forecasting needs. This book is part of the SAS Press program.
Business Analytics Using Sas Enterprise Guide And Sas Enterprise Miner
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Author : Olivia Parr-Rud
language : en
Publisher: SAS Institute
Release Date : 2014-10-01
Business Analytics Using Sas Enterprise Guide And Sas Enterprise Miner written by Olivia Parr-Rud and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-01 with Computers categories.
This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. Today’s businesses increasingly use data to drive decisions that keep them competitive. Especially with the influx of big data, the importance of data analysis to improve every dimension of business cannot be overstated. Data analysts are therefore in demand; however, many hires and prospective hires, although talented with respect to business and statistics, lack the know-how to perform business analytics with advanced statistical software. Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner is a beginner’s guide with clear, illustrated, step-by-step instructions that will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. This book is part of the SAS Press program.
Data Quality For Analytics Using Sas
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Author : Gerhard Svolba
language : en
Publisher: SAS Institute
Release Date : 2015-05-05
Data Quality For Analytics Using Sas written by Gerhard Svolba and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-05 with Computers categories.
Analytics offers many capabilities and options to measure and improve data quality, and SAS is perfectly suited to these tasks. Gerhard Svolba's Data Quality for Analytics Using SAS focuses on selecting the right data sources and ensuring data quantity, relevancy, and completeness. The book is made up of three parts. The first part, which is conceptual, defines data quality and contains text, definitions, explanations, and examples. The second part shows how the data quality status can be profiled and the ways that data quality can be improved with analytical methods. The final part details the consequences of poor data quality for predictive modeling and time series forecasting.
Sas For Dummies
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Author : Stephen McDaniel
language : en
Publisher: John Wiley & Sons
Release Date : 2010-03-16
Sas For Dummies written by Stephen McDaniel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-16 with Computers categories.
The fun and easy way to learn to use this leading business intelligence tool Written by an author team who is directly involved with SAS, this easy-to-follow guide is fully updated for the latest release of SAS and covers just what you need to put this popular software to work in your business. SAS allows any business or enterprise to improve data delivery, analysis, reporting, movement across a company, data mining, forecasting, statistical analysis, and more. SAS For Dummies, 2nd Edition gives you the necessary background on what SAS can do for you and explains how to use the Enterprise Guide. SAS provides statistical and data analysis tools to help you deal with all kinds of data: operational, financial, performance, and more Places special emphasis on Enterprise Guide and other analytical tools, covering all commonly used features Covers all commonly used features and shows you the practical applications you can put to work in your business Explores how to get various types of data into the software and how to work with databases Covers producing reports and Web reporting tools, analytics, macros, and working with your data In the easy-to-follow, no-nonsense For Dummies format, SAS For Dummies gives you the knowledge and the confidence to get SAS working for your organization. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Data Mining And Exploration
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Author : Chong Ho Alex Yu
language : en
Publisher: CRC Press
Release Date : 2022-10-27
Data Mining And Exploration written by Chong Ho Alex Yu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Business & Economics categories.
This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. First, most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between traditional statistics and modern data science; as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a “black box”, without a comprehensive view of the foundational differences between traditional and modern methods (e.g., dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation etc.). This book delineates the transition between classical methods and data science (e.g. from p value to Log Worth, from resampling to ensemble methods, from content analysis to text mining etc.). Second, this book aims to widen the learner's horizon by covering a plethora of software tools. When a technician has a hammer, every problem seems to be a nail. By the same token, many textbooks focus on a single software package only, and consequently the learner tends to fit the problem with the tool, but not the other way around. To rectify the situation, a competent analyst should be equipped with a tool set, rather than a single tool. For example, when the analyst works with crucial data in a highly regulated industry, such as pharmaceutical and banking, commercial software modules (e.g., SAS) are indispensable. For a mid-size and small company, open-source packages such as Python would come in handy. If the research goal is to create an executive summary quickly, the logical choice is rapid model comparison. If the analyst would like to explore the data by asking what-if questions, then dynamic graphing in JMP Pro is a better option. This book uses concrete examples to explain the pros and cons of various software applications.
Business Statistics Made Easy In Sas
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Author : Gregory Lee
language : en
Publisher: SAS Institute
Release Date : 2015-10-30
Business Statistics Made Easy In Sas written by Gregory Lee and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-30 with Business & Economics categories.
This book is designed 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). It 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. 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. --
Cases On Health Outcomes And Clinical Data Mining Studies And Frameworks
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Author : Cerrito, Patricia
language : en
Publisher: IGI Global
Release Date : 2010-02-28
Cases On Health Outcomes And Clinical Data Mining Studies And Frameworks written by Cerrito, Patricia and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-28 with Computers categories.
"Because so much data is now becoming readily available to investigate health outcomes, it is important to examine just how statistical models are used to do this. This book studies health outcomes research using data mining techniques"--Provided by publisher.
International Encyclopedia Of Statistical Science
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Author : Miodrag Lovric
language : en
Publisher: Springer Nature
Release Date : 2025-06-19
International Encyclopedia Of Statistical Science written by Miodrag Lovric and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-19 with Mathematics categories.
The International Encyclopedia of Statistical Science stands as a monumental effort to enrich statistics education globally, particularly in regions facing educational challenges. By amalgamating the expertise of over 700 authors from 110 countries, including Nobel Laureates and presidents of statistical societies, it offers an unparalleled resource for readers worldwide. This encyclopedia is not just a collection of entries; it is a concerted effort to revive statistics as a vibrant, critical field of study and application. Providing a comprehensive and accessible account of statistical terms, methods, and applications, it enables readers to gain a quick insight into the subject, regardless of their background. This work serves to refresh and expand the knowledge of researchers, managers, and practitioners, highlighting the relevance and applicability of statistics across various fields, from economics and business to healthcare and public policy. Furthermore, it aims to inspire students by demonstrating the significance of statistics in solving real-world problems, thus encouraging a new generation to explore and contribute to the field.