Business Analytics / Edition 1

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Overview

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.

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Product Details

  • ISBN-13: 9780132950619
  • Publisher: Pearson
  • Publication date: 2/24/2012
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 688
  • Sales rank: 149,957
  • Product dimensions: 7.90 (w) x 10.00 (h) x 0.90 (d)

Meet the Author

James R. Evans

Professor, University of Cincinnati College of Business

James R. Evans is professor in the Department of Operations, Business Analytics, and Information Systems in the College of Business at the University of Cincinnati. He holds BSIE and MSIE degrees from Purdue and a PhD in Industrial and Systems Engineering from Georgia Tech.

Dr. Evans has published numerous textbooks in a variety of business disciplines, including statistics, decision models, and analytics, simulation and risk analysis, network optimization, operations management, quality management, and creative thinking. He has published over 90 papers in journals such as Management Science, IIE Transactions, Decision Sciences, Interfaces, the Journal of Operations Management, the Quality Management Journal, and many others, and wrote a series of columns in Interfaces on creativity in management science and operations research during the 1990s. He has also served on numerous journal editorial boards and is a past-president and Fellow of the Decision Sciences Institute. In 1996, he was an INFORMS Edelman Award Finalist as part of a project in supply chain optimization with Procter & Gamble that was credited with helping P&G save over $250,000,000 annually in their North American supply chain, and consulted on risk analysis modeling for Cincinnati 2012’s Olympic Games bid proposal.

A recognized international expert on quality management, he served on the Board of Examiners and the Panel of Judges for the Malcolm Baldrige National Quality Award. Much of his current research focuses on organizational performance excellence and measurement practices.

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Table of Contents

Part 1: Foundations of Business Analytics
Chapter 1: Introduction to Business Analytics Chapter 2: Analytics on Spreadsheets
Part 2: Descriptive Analytics
Chapter 3: Visualizing and Exploring Data Chapter 4: Descriptive Statistical Measures Chapter 5: Probability Distributions and Data Modeling Chapter 6: Sampling and Estimation Chapter 7: Statistical Inference
Part 3: Predictive Analytics
Chapter 8: Predictive Modeling and Analysis Chapter 9: Regression Analysis Chapter 10: Forecasting Techniques Chapter 11: Simulation and Risk Analysis Chapter 12: Introduction to Data Mining
Part 4: Prescriptive Analytics
Chapter 13: Linear Optimization Chapter 14: Applications of Linear Optimization Chapter 15: Integer Optimization Chapter 16: Nonlinear and Non-Smooth Optimization Chapter 17: Optimization Models with Uncertainty
Part 5: Making Decisions
Chapter 18: Decision Analysis
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