Five sections guide students through the information

· Part 1: Foundations of Business Analytics. The first two chapters provide the basic foundations needed to understand business analytics and Microsoft Excel, and show students how to manipulate data and develop simple spreadsheet models.

· Part 2: Descriptive Analytics. Chapters 3 through 7 cover the fundamental tools and methods of data analysis and statistics. These chapters focus on visual representations of data, descriptive statistical measures, probability distributions and data modeling, sampling and estimation, and statistical inference.

· Part 3: Predictive Analytics. Chapters 8 through 12 develop approaches for applying trendlines and regression analysis, forecasting and introductory data mining techniques, building and analyzing models on spreadsheets, and simulation and risk analysis.

· Part 4: Prescriptive Analytics. Chapters 13 and 14 explore linear, integer, and nonlinear optimization models and applications. Chapter 15 focuses on what-if and sensitivity analysis in optimization, and visualization of Solver reports.

· Part 5: Making Decisions. Chapter 16 focuses on philosophies, tools, and techniques of decision analysis.

In-text features aid in student understanding

· New - Numbered Chapter Sections, with Check Your Understanding questions, provide a means to review fundamental concepts.

· New - Analytics in Practice describes real applications in business.

· Learning Objectives help students guide their learning efforts.

· Key terms and their definitions assist students as they review the chapter and study for exams.

· Updated - End-of-Chapter Problems and Exercises help reinforce the material covered throughout the chapter and have been revised for added clarity.

· Integrated Cases encourage students to think independently and apply the tools at a higher level of learning.

· New - Appendix in Chapter 1 reviews basic Excel skills, and is used throughout the book.

Updated material ensures students are well versed in the latest business analytics principles and techniques

· New - The application of Excel for dealing with spreadsheet data (Chapter 2);

· New - Combinations and permutations (Chapter 5);

· New - The use of data visualization for confidence interval comparison (Chapter 6);

· New - Excel approaches for double exponential smoothing and Holt-Winters models for seasonality and trend (Chapter 9);

· New - Simple data mining techniques for spreadsheets using Excel (Chapter 10); and

· New - What-if and sensitivity analysis, visualization of Solver reports, and how Solver handles models with bounded variables (Chapter 15).

Complete software support

· New - Technology Help in every chapter provides students with useful summaries of key Excel functions and procedures. Also, the 3rd Edition now relies solely on native Excel, and is independent of platforms, allowing it to be easily used by students with either PCs/Macs.

· Updated - Online supplements provide detailed information and examples for using StatCrunch and Analytic Solver for Education, which provides more powerful tools for data mining, Monte-Carlo simulation, optimization, a

• Numbered Chapter Sections, with Check Your Understanding questions, provide a means to review fundamental concepts.
• Analytics in Practice describes real applications in business.
• End-of-Chapter Problems and Exercises help reinforce the material covered throughout the chapter and have been revised for added clarity.
• Appendix in Chapter 1 reviews basic Excel skills, and is used throughout the book.
• Updated material ensures students are well versed in the latest business analytics principles and techniques
  • The application of Excel for dealing with spreadsheet data (
  • Combinations and permutations
  • The use of data visualisation for confidence interval comparison
  • Excel approaches for double exponential smoothing and Holt-Winters models for seasonality and trend
  • Simple data mining techniques for spreadsheets using Excel; and
  • What-if and sensitivity analysis, visualisation of Solver reports, and how Solver handles models with bounded variables
• Technology Help in every chapter provides students with useful summaries of key Excel functions and procedures. Also, the 3rd Edition now relies solely on native Excel, and is independent of platforms, allowing it to be easily used by students with either PCs/Macs.
• Online supplements provide detailed information and examples for using StatCrunch and Analytic Solver for Education, which provides more powerful tools for data mining, Monte-Carlo simulation, optimisation, and decision analysis.