Data-Driven Business Decisions

Contents

Preface

To the Student

To the Teacher: How to Build a Course Around This Book

Chapter 1 How Are We Doing? Data-Driven Views of Business Performance

1.1 Setting Out Business Data

1.2 Different Kinds of Variables

1.3 The Idea of a Distribution

1.4 Typical Performance: The Sample Mean

1.5 Uncertainty in Performance: SD

1.6 Changing Units

1.7 Shapes of Distributions

Chapter 2 What Stands Out and Why? Who Wins? Data-Driven Views of Performance Dynamics

2.1 Different Layouts of Business Data

2.2 Comparing Performance across Different Segments

2.3 Complex Comparisons: Using Pivotables

2.4 Unusually High or Low Outcomes: z-Scores

2.5 Homogeneous Peer Groups

2.6 Combining Different Performance Measures

Chapter 3 Dealing with Uncertainty and Chance

3.1 Framing What Could Happen: Outcomes and Events

3.2 How Likely Is It? Probability Basics

3.3 Market Segments and Behavior; Probability Tables

3.4 Example in Health Care: Testing for a Disease

3.5 Conditional Probability

3.6 How Strong Is the Relationship? Measuring Dependence

3.7 Probability Trees

Chapter 4 Let the Data Change Your Views: The Bayes Method

4.1 The Bayes Method in Pictures

4.2 The Bayes Method as an Algorithm

4.3 Example 1: A Simple Gambling Game

4.4 Example 2: Bayes in the Courtroom

4.5 Some Typical Business Applications

Chapter 5 Valuing an Uncertain Payoff

5.1 What Is a Probability Distribution?

5.2 Displaying a Probability Distribution

5.3 The Mean of a Distribution

5.4 Example: Fines and Violations

5.5 Why Use the ...