R for business analytics [Documento eletrónico] / A. Ohri
Language: eng.Country: US - United States of America.Publication: New York, NY : Springer , 2013Description: XVIII, 312 p. : il.ISBN: 978-1-4614-4343-8.Subject - Topical Name: 28929 | 28930 | 6653Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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E-Books | Biblioteca NOVA FCT Online | Não Ficção | HF1017.SPR FCT 81345 (Browse shelf(Opens below)) | 1 | Available |
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HE332.SPR FCT 94605 Mathematical and computational models for congestion charging | HE571.HAN FCT 101243 The Handbook of Maritime Economics and Business | HE571.TAL FCT 101255 The Blackwell companion to maritime economics | HF1017.SPR FCT 81345 R for business analytics | HF1017.SPR FCT 81363 Mathematical statistics for economics and business | HF1365.SPR FCT Data analytics applications in emerging markets | HF5410.SPR FCT Artificial neural networks and structural equation modeling, marketing and consumer research applications |
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R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.
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