Table of Contents

Preface   v

Figures   ix

Tables   xiii

Exhibits   xv

1. Analytics and Data Science   1

2. Advertising and Promotion   15

3. Preference and Choice   29

4. Market Basket Analysis   37

5. Economic Data Analysis   53

6. Operations Management   67

7. Text Analytics   83

8. Sentiment Analysis   113

9. Sports Analytics   149

10. Brand and Price   173

11. Spatial Data Analysis   209

12. The Big Little Data Game   231

A. There's a Pack for That   237

B. Measurement   253

C. Code and Utilities   267

Bibliography   297

Index   327

Promotional Information

Today, successful firms win by understanding their data more deeply than competitors do. In short, they compete based on analytics. Now, in Modeling Techniques in Predictive Analytics, the leader of Northwestern University’s prestigious analytics program brings together all the concepts, techniques, and R code you need to excel in analytics. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike.

Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, Web and text analytics, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains: 

• Why the problem is significant
• What data is relevant
• How to explore your data
• How to model your data – first conceptually, with words and figures; and then with mathematics and programs

Miller walks through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. Extensive example code is presented in R, today’s #1 system for applied statistics, statistical research, and predictive modeling; all code is set apart from other text so it’s easy to find for those who want it (and easy to skip for those who don’t).

About the Author

Thomas W. Miller is faculty director of the Predictive Analytics program at Northwestern University. He has designed courses for the program, including Marketing Analytics, Advanced Modeling Techniques, Data Visualization, and the capstone course. He has taught extensively in the program and works with more than forty other faculty members in delivering training in predictive analytics and data science.

Miller is also owner and president of Research Publishers LLC. He has consulted widely in the areas of retail site selection, product positioning, segmentation, and pricing in competitive markets, and has worked with predictive models for over 30 years.

Miller’s books include Data and Text Mining: A Business Applications Approach, Research and Information Services: An Integrated Approach for Business, and a book about predictive modeling in sports, Without a Tout: How to Pick a Winning Team.

Before entering academia, Miller spent nearly 15 years in business IT in the computer and transportation industries. He also directed the A. C. Nielsen Center for Marketing Research and taught market research and business strategy at the University of Wisconsin–Madison.

He holds a Ph.D. in psychology (psychometrics), a master’s degree in statistics from the University of Minnesota, and an MBA and master’s degree in economics from the University of Oregon.