Business analytics

Business analytics: methods, models, and decisions

by Evans, James R., (James Robert)

Type Book
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"A balanced, holistic approach to understanding business analytics. This book provides readers with the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations. Evans also shows readers how to apply basic business analytics tools in a spreadsheet environment, and how to communicate with analytics professionals to effectively use and interpret analytic models and results for making better business decisions."--Provided by publisher.

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Title Statements

  • Full title :Business analytics : methods, models, and decisions / James R. Evans.

Summary

"A balanced, holistic approach to understanding business analytics. This book provides readers with the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations. Evans also shows readers how to apply basic business analytics tools in a spreadsheet environment, and how to communicate with analytics professionals to effectively use and interpret analytic models and results for making better business decisions."--Provided by publisher.

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Edition Statements

  • Publication Date:©2013.
  • Edition:1st ed

Publication Statements

  • Publisher(s):Pearson
  • Place of Publication:Boston
  • Language:eng
  • Publication Date:©2013.

Notes

Includes index.

The Physical Object

  • Description:xvii, 665 pages : : color illustrations ; : 26 cm.

Edition Identifiers

  • ISBN:9780132950619, 0132950618, 9780133051711, 0133051714
  • oclc:ocn771913458
  • LC Classification:HD30.28
  • Dewey Decimal:658.4/01

Table of Contents

Introduction to business analytics -- Analytics on spreadsheets -- Visualizing and exploring data -- Descriptive statistical measures -- Probability distributions and data modeling -- Sampling and estimation -- Statistical inference --Predictive modeling and analysis -- Regression analysis -- Forecasting techniques -- Simulation and risk analysis -- Introduction to data mining -- Linear optimization -- Applications of linear optimization -- Integer optimization -- Nonlinear and non- smooth optimization -- Optimization models with uncertainty -- Decision analysis.

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