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Auteur Hector Guerrero |
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Titre : Excel data analysis : modeling and simulation Type de document : Guide/Manuel Auteurs : Hector Guerrero, Auteur Mention d'édition : 2ème édition Editeur : Springer Nature Année de publication : 2019 Importance : 358 p. ISBN/ISSN/EAN : 978-3-030-01279-3 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] analyse de données
[Termes IGN] données qualitatives
[Termes IGN] Excel (logiciel)
[Termes IGN] inférence statistique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] programmation linéaireRésumé : (Editeur) 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 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. Note de contenu :
1. Introduction to Spreadsheet Modeling
2. Presentation of Quantitative Data: Data Visualization
3. Analysis of Quantitative Data
4. Presentation of Qualitative Data—Data Visualization
5. Analysis of Qualitative Data
6. Inferential Statistical Analysis of Data
7. Modeling and Simulation: Part 1
8. Modeling and Simulation: Part 2
9. Solver, Scenarios, and Goal Seek ToolsNuméro de notice : 26280 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Manuel informatique DOI : 10.1007/978-3-030-01279-3 En ligne : https://doi.org/10.1007/978-3-030-01279-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94931
