Business Analytics [Libro Electrónico - McGraw-Hill]
Tipo de material:
TextoEditor: United Kingdom of Great Britain & Northern Ireland : McGraw-Hill Higher Education (International), 2020Edición: first editionDescripción: 1 online resourceTipo de contenido: text Tipo de medio: computer ISBN: 9781260590531Tema(s): Mathematics/Probability & Statistics/GeneralRecursos en línea: Haga clic para acceso en línea Resumen: Business Analytics: Communicating with Numbers was written from the ground up to prepare students to understand, manage, and visualize the data, apply the appropriate tools, and communicate the findings and their relevance. Unlike other texts that simply repackage statistics and traditional operations research topics, this text seamlessly threads the topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive whole. It provides a holistic analytics process, including dealing with real life data that are not necessarily 'clean' and/or 'small' and stresses the importance of effectively communicating findings by including features such as a synopsis (a short writing sample) and a sample report (a longer writing sample) in every chapter. These features help students develop skills in articulating the business value of analytics by communicating insights gained from a non-technical standpoint.
| Tipo de ítem | Ubicación actual | Colección | Signatura | Estado | Fecha de vencimiento | Código de barras |
|---|---|---|---|---|---|---|
MacGraw-Hill
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Biblioteca Central Estatal de Guanajuato, "Wigberto Jiménez Moreno" | Libros Electrónicos MacGraw-Hill | Disponible | 9781260590531 |
Business Analytics: Communicating with Numbers was written from the ground up to prepare students to understand, manage, and visualize the data, apply the appropriate tools, and communicate the findings and their relevance. Unlike other texts that simply repackage statistics and traditional operations research topics, this text seamlessly threads the topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive whole. It provides a holistic analytics process, including dealing with real life data that are not necessarily 'clean' and/or 'small' and stresses the importance of effectively communicating findings by including features such as a synopsis (a short writing sample) and a sample report (a longer writing sample) in every chapter. These features help students develop skills in articulating the business value of analytics by communicating insights gained from a non-technical standpoint.
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