Bndl: Business Analytics Data Analysis/Decision Making, Albright/Winston
Автор: Gelman Название: Bayesian Data Analysis, Third Edition ISBN: 1439840954 ISBN-13(EAN): 9781439840955 Издательство: Taylor&Francis Рейтинг: Цена: 11088.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Описание: This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary concepts and definitions are gradually built in Chapters 1-6 based upon four examples of one input and one output factors, two input factors, two output factors, and four input and three output factors. Simultaneously, the mathematical foundations using linear programming are also introduced without any prerequisites. A reader with basic knowledge of mathematics and computers is able to understand the contents of the book. In addition, to prevent pre-judgment about the available concepts and definitions in the DEA literature, some new phrases are introduced and, after elucidating each phrase in detail in Chapters 1-6, they are reintroduced for industry-wide accuracy in Chapter 7. After that, some of the more advanced DEA topics are illustrated in Chapters 8-12, such as: production-planning problems, output-input ratio analysis, efficiency over different time periods, Malmquist efficiency indexes, and a delta neighborhood model.
A clear overview of many of the elementary and advanced concepts of DEA is provided, including Technical Efficiency, Relative Efficiency, Cost/Revenue/Profit Efficiency, Price/Overall Efficiency, the DEA axioms, the mathematical background to measure technical efficiency and overall efficiency, the multiplier/envelopment form of basic DEA models in input/output-orientation, the multiplier/envelopment of Additive DEA model, the multiplier/envelopment of slacks-based models, and others. The book also covers a variety of DEA techniques, input-output ratio analysis, the natural relationships between DEA frontier and the ratio of output to input factors, production-planning problems, planning ideas with a centralized decision-making unit, context-dependent DEA, Malmquist efficiency index, efficiency over different time periods, and others. End-of-chapter exercises are provided for each chapter.
Автор: Albright S. Christian, Winston Wayne L. Название: Business Analytics: Data Analysis & Decision Making ISBN: 0357109953 ISBN-13(EAN): 9780357109953 Издательство: Cengage Learning Рейтинг: Цена: 12670.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Master data analysis, modeling and the effective use of spreadsheets with the popular BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 7E. The quantitative methods approach in this edition helps you maximize your success with a proven teach-by-example presentation, inviting writing style and complete integration of the latest version of Excel. The approach is also compatible with earlier versions of Excel for your convenience.
This edition is more data-oriented than ever before with a new chapter on the two main Power BI tools in Excel -- Power Query and Power Pivot -- and a new section of data visualization with Tableau Public. Current problems and cases demonstrate the importance of the concepts you are learning. In addition, a useful Companion Website provides data and solutions files, SolverTable for optimization sensitivity analysis and Palisade DecisionTools Suite.
MindTap online resources are also available.
Автор: Gressel, Simone Pauleen, David Taskin, Nazim Название: Management decision-making, big data and analytics ISBN: 1526492008 ISBN-13(EAN): 9781526492005 Издательство: Sage Publications Рейтинг: Цена: 7285.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Автор: Solomon Michael G. Название: Blockchain Data Analytics for Dummies ISBN: 1119651778 ISBN-13(EAN): 9781119651772 Издательство: Wiley Рейтинг: Цена: 4117.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Get ahead of the curve-learn about big data on the blockchain Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain.
Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data.
Set your organization on the cutting edge of analytics, before your competitors get there! Learn how blockchain technologies work and how they can integrate with big dataDiscover the power and potential of blockchain analyticsEstablish data models and quickly mine for insights and resultsCreate data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!
Описание: A compendium of health care quantitative techniques based in Excel Analytics and Decision Support in Health Care Operations is a comprehensive introductory guide to quantitative techniques, with practical Excel-based solutions for strategic health care management.
Автор: David J. Pauleen, Nazim Taskin, Simone Gressel Название: Management Decision-Making, Big Data and Analytics ISBN: 1529736498 ISBN-13(EAN): 9781529736496 Издательство: Sage Publications Рейтинг: Цена: 4909.00 р. Наличие на складе: Нет в наличии.
Описание: Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers.
The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management.
The book features chapters on cutting-edge topics, including: •Big data •Analytics •Managing emerging technologies and decision-making •Managing the ethics, security, privacy and legal aspects of data-driven decision-making
The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles.
Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.
Описание: The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers.
Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies.
Описание: The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers.
Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies.
Автор: Boris Deliba?i?; Jorge E. Hern?ndez; Jason Papatha Название: Decision Support Systems V – Big Data Analytics for Decision Making ISBN: 3319185322 ISBN-13(EAN): 9783319185323 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Big Data' Decision Making Use Cases.- The Roles of Big Data in the Decision-Support Process: An Empirical Investigation.- Cloud Enabled Big Data Business Platform for Logistics Services: A Research and Development Agenda.- Making Sense of Governmental Activities Over Social Media: A Data-Driven Approach.- Data-Mining and Expert Models for Predicting Injury Risk in Ski Resorts.- The Effects of Performance Ratios in Predicting Corporate Bankruptcy: The Italian Case.- A Tangible Collaborative Decision Support System for Various Variants of the Vehicle Routing Problem.- Decision Support Model for Participatory Management of Water Resource.- Modeling Interactions Among Criteria in MCDM Methods: A Review.
Автор: Gressel, Simone Pauleen, David Taskin, Nazim Название: Management decision-making, big data and analytics ISBN: 1526492016 ISBN-13(EAN): 9781526492012 Издательство: Sage Publications Рейтинг: Цена: 22176.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Описание: This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.
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