Part I: Exploring and Collecting Data

 

1. Data and Decisions(E-Commerce)

1.1 What Are Data?

1.2 Variable Types

1.3 Data Sources: Where, How, and When

Ethics in Action

Technology Help: Data

Brief Case: Credit Card Bank

 

2. Displaying and Describing Categorical Data(KEEN, Inc.)

2.1 Summarizing a Categorical Variable

2.2 Displaying a Categorical Variable

2.3 Exploring Two Categorical Variables: Contingency Tables

2.4 Segmented Bar Charts and Mosaic Plots

2.5 Simpson’s Paradox

Ethics in Action

Technology Help: Displaying Categorical Data

Brief Case: Credit Card Bank

 

3. Displaying and Describing Quantitative Data(AIG)

3.1 Displaying Quantitative Variables

3.2 Shape

3.3 Center

3.4 Spread of the Distribution

3.5 Shape, Center, and Spread–A Summary

3.6 Standardizing Variables

3.7 Five-Number Summary and Boxplots

3.8 Comparing Groups

3.9 Identifying Outliers

3.10 Time Series Plots

*3.11 Transforming Skewed Data

Ethics in Action

Technology Help: Displaying and Summarizing Quantitative Variables

Brief Cases: Detecting the Housing Bubble and Socio-Economic Data on States

 

4. Correlation and Linear Regression(Amazon.com)

4.1 Looking at Scatterplots

4.2 Assigning Roles to Variables in Scatterplots

4.3 Understanding Correlation

4.4 Lurking Variables and Causation

4.5 The Linear Model

4.6 Correlation and the Line

4.7 Regression to the Mean

4.8 Checking the Model

4.9 Variation in the Model and R2

4.10 Reality Check: Is the Regression Reasonable?

4.11 Nonlinear Relationships

Ethics in Action

Technology Help: Correlation and Regression

Brief Cases: Fuel Efficiency, Cost of Living, and Mutual Funds

Case Study I: Paralyzed Veterans of America

 

Part II: Modeling with Probability

 

5. Randomness and Probability(Credit Reports and the Fair Isaacs Corporation)

5.1 Random Phenomena and Probability

5.2 The Nonexistent Law of Averages

5.3 Different Types of Probability

5.4 Probability Rules

5.5 Joint Probability and Contingency Tables

5.6 Conditional Probability

5.7 Constructing Contingency Tables

5.8 Probability Trees

*5.9 Reversing the Conditioning: Bayes’ Rule

Ethics in Action

Technology Help: Generating Random Numbers

Brief Case: Global Markets

 

6. Random Variables and Probability Models(Metropolitan Life Insurance Company)

6.1 Expected Value of a Random Variable

6.2 Standard Deviation of a Random Variable

6.3 Properties of Expected Values and Variances

6.4 Bernoulli Trials

6.5 Discrete Probability Models

Ethics in Action

Technology Help: Random Variables and Probability Models

Brief Case: Investment Options

 

7. The Normal and Other Continuous Distributions(The NYSE)

7.1 The Standard Deviation as a Ruler

7.2 The Normal Distribution

7.3 Normal Probability Plots

7.4 The Distribution of Sums of Normals

7.5 The Normal Approximation for the Binomial

7.6 Other Continuous Random Variables

Ethics in Action

Technology Help: Probability Calculations and Plots

Brief Case: Price/Earnings and Stock Value

 

8. Surveys and Sampling(Roper Polls)

8.1 Three Ideas of Sampling

8.2 Populations and Parameters

8.3 Common Sampling Designs

8.4 The Valid Survey

8.5 How to Sample Badly

Ethics in Action

Technology Help: Random Sampling

Brief Cases: Market Survey Research and The GfK Roper Reports Worldwide Survey

 

9. Sampling Distributions and Confidence Intervals for Proportions(Marketing Credit Cards: The MBNA Story)

9.1 The Distribution of Sample Proportions

9.2 The Sampling Distribution for Proportions

9.3 A Confidence Interval for a Proportion

9.4 Margin of Error: Certainty vs. Precision

9.5 Choosing the Sample Size

Ethics in Action

Technology Help: Confidence Intervals for Proportions

Brief Cases: Has Gold Lost Its Luster? and Forecasting Demand

Case Study II: Real Estate Simulation

 

Part III: Inference for Decision Making

 

10. Testing Hypotheses about Proportions(Dow Jones Industrial Average)

10.1 Hypotheses

10.2 A Trial as a Hypothesis Test

10.3 P-Values

10.4 The Reasoning of Hypothesis Testing

10.5 Alternative Hypotheses

10.6 Alpha Levels and Significance

10.7 Critical Values

10.8 Confidence Intervals and Hypothesis Tests

10.9 Two Types of Errors

10.10 Power

Ethics in Action

Technology Help: Hypothesis Tests

Brief Cases: Metal Production, Loyalty Program, and Confidence Intervals and Hypothesis Tests

 

11. Confidence Intervals and Hypothesis Tests for Means(Guinness & Co.)

11.1 The Central Limit Theorem

11.2 The Sampling Distribution of the Mean

11.3 How Sampling Distribution Models Work

11.4 Gosset and the t-Distribution

11.5 A Confidence Interval for Means

11.6 Assumptions and Conditions

11.7 Testing Hypotheses about Means–the One-Sample t-Test

Ethics in Action

Technology Help: Inference for Means

Brief Cases: Real Estate and Donor Profiles

 

12. Comparing Two Means(Visa Global Organization)

12.1 Comparing Two Means

12.2 The Two-Sample t-Test

12.3 Assumptions and Conditions

12.4 A Confidence Interval for the Difference Between Two Means

12.5 The Pooled t-Test

12.6 Paired Data

12.7 Paired t-Methods

Ethics in Action

Technology Help: Comparing Two Groups

Brief Cases: Real Estate and Consumer Spending Patterns (Data Analysis)

 

13. Inference for Counts: Chi-Square Tests(SAC Capital)

13.1 Goodness-of-Fit Tests

13.2 Interpreting Chi-Square Values

13.3 Examining the Residuals

13.4 The Chi-Square Test of Homogeneity

13.5 Comparing Two Proportions

13.6 Chi-Square Test of Independence

Ethics in Action

Technology Help: Chi-Square

Brief Cases: Health Insurance and Loyalty Program

Case Study III: Investment Strategy Segmentation

 

Part IV Models for Decision Making

 

14. Inference for Regression(Nambé Mills)

14.1 A Hypothesis Test and Confidence Interval for the Slope

14.2 Assumptions and Conditions

14.3 Standard Errors for Predicted Values

14.4 Using Confidence and Prediction Intervals

Ethics in Action

Technology Help: Regression Analysis

Brief Cases: Frozen Pizza and Global Warming?

 

15. Multiple Regression(Zillow.com)

15.1 The Multiple Regression Model

15.2 Interpreting Multiple Regression Coefficients

15.3 Assumptions and Conditions for the Multiple Regression Model

15.4 Testing the Multiple Regression Model

15.5 Adjusted R2 and the F-statistic

*15.6 The Logistic Regression Model

Ethics in Action

Technology Help: Regression Analysis

Brief Case: Golf Success

 

Part V: Selected Topics in Decision Making

 

16. Introduction to Data Mining(Paralyzed Veterans of America)

16.1 The Big Data Revolution

16.2 Direct Marketing

16.3 The Goals of Data Mining

16.4 Data Mining Myths

16.5 Successful Data Mining

16.6 Data Mining Problems

16.7 Data Mining Algorithms

16.8 The Data Mining Process

16.9 Summary

Ethics in Action

Case Study V: Marketing Experiment

 

Appendices

A. Answers

B. Tables and Selected Formulas

C. Photo Acknowledgments

Index

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