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Record Nr. |
UNINA9910337790703321 |
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Autore |
Guerrero Hector |
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Titolo |
Excel Data Analysis : Modeling and Simulation / / by Hector Guerrero |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[2nd ed. 2019.] |
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Descrizione fisica |
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1 online resource (XIX, 346 p. 215 illus.) |
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Classificazione |
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Disciplina |
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Soggetti |
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Operations research |
Probabilities |
Statistics |
Industrial organization |
Business mathematics |
Business information services |
Operations Research and Decision Theory |
Probability Theory |
Statistics in Business, Management, Economics, Finance, Insurance |
Organization |
Business Mathematics |
IT in Business |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction to Spreadsheet Modeling -- Presentation of Quantitative Data - Data Visualization -- Analysis of Quantitative Data - Data Visualization -- Presentation of Qualitative Data -- Analysis of Qualitative Data -- Inferential Statistical Analysis of Data -- Modeling and Simulation: Part I -- Modeling and Simulation: Part II -- Solver, Scenarios, and Goal Seek Tools. |
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Sommario/riassunto |
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This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their |
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proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations. . |
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