Applied Statistics in Business and Economics, 7th Edition [Libro Electrónico - McGraw-Hill]

Por: David Doane; Lori Seward [author]Tipo de material: TextoTextoEditor: United Kingdom of Great Britain & Northern Ireland : McGraw-Hill Higher Education (International), 2021Edición: seventh editionDescripción: 1 online resourceTipo de contenido: text Tipo de medio: computer ISBN: 9781264360956Tema(s): Mathematics/Probability & Statistics/GeneralRecursos en línea: Haga clic para acceso en línea Resumen: Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how.  The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics.  It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.
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MacGraw-Hill MacGraw-Hill Biblioteca Central Estatal de Guanajuato, "Wigberto Jiménez Moreno"
Libros Electrónicos MacGraw-Hill Disponible 9781264360956

Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how.  The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics.  It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.

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