Managerial Applications of Multivariate Analysis in Marketing

Overview

Multivariate statistical analysis techniques are now an integral part of most large-scale strategic market studies, so marketing practitioners must learn what these techniques can do and how to apply them. However, most marketers have little or no formal training in complex analytical methods, and many have neither the time nor the interest in acquiring this knowledge. If you are one of them, this book is for you. Managerial Applications of Multivariate Analysis in Marketing is written for marketing research ...

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Overview

Multivariate statistical analysis techniques are now an integral part of most large-scale strategic market studies, so marketing practitioners must learn what these techniques can do and how to apply them. However, most marketers have little or no formal training in complex analytical methods, and many have neither the time nor the interest in acquiring this knowledge. If you are one of them, this book is for you. Managerial Applications of Multivariate Analysis in Marketing is written for marketing research practitioners—even those who don't have time to read it cover to cover. Each chapter is as self-contained as possible so that researchers and decision makers can more quickly understand the fundamentals of any one statistical technique. It is a reference book, not a textbook, so it does not focus on the statistical techniques themselves and leave you to wonder how they apply to marketing. Most of the calculations in this book can be done by a personal computer, so the authors only cover the math you need while focusing on the marketing implications.

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Product Details

  • ISBN-13: 9780877573012
  • Publisher: Cengage Learning
  • Publication date: 3/1/2003
  • Pages: 395
  • Product dimensions: 6.10 (w) x 9.10 (h) x 1.30 (d)

Meet the Author

James H. Myers, Ph.D. was professor of marketing at the Drucker School at Claremont Graduate University, for 22 years. Prior to that, he taught for 20 years at the Graduate School of Business Administration, University of Southern California. Before entering academia, Myers was manager of the Management Research Division at the Prudential Insurance Company¿s regional headquarters in Los Angeles. Myers is the author or coauthor of 7 books and more than 60 articles in the areas of marketing management, strategic marketing research, and customer satisfaction. He has also given many presentations on these and other topics to business and professional groups throughout the country. Myers has done extensive consulting in the areas of marketing research, market segmentation, product/service positioning, and new product opportunity identification. His clients have included Eastman Kodak, British Telecom, Frito-Lay, Gemini Management Consulting, and Pacific Gas & Electric Co.

Gary M. Mullet, Ph.D. is the principal of Gary Mullet Associates, Inc. He has taught at the University of Michigan, where he received his Ph.D., the University of Cincinnati, and Georgia Institute of Technology. His work experience includes Dow Chemical Company, Burke Marketing Research, and SDR. Mullet has published refereed papers in a diverse set of academic journals, including Journal of Marketing Research, Journal of the American Statistical Association, Australian Economic Papers, Decision Sciences, Public Personnel Management and Science, and several others. He is also coauthor of a long forgotten book in the field of thermodynamics. He has given several presentations at professional society meetings. A self-described recovering academic, Mullet¿s current client list includes both full-service marketing research firms of all sizes and end user¿corporate marketing research departments.

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Table of Contents

I. INTRODUCTION 1. Introduction to Multivariate Statistical Analysis 2. Some Basic Concepts and Definitions II. DEPENDENCE METHODS 3. Basic Regression Analysis: Linear 4. Basic Regression Analysis: Nonlinear 5. Multiple Regression Analysis 6. Logistic Regression 7. Discriminant Analysis and Canonical Analysis 8. Conjoint Analysis: Full-Profile and Pairwise Trade-Offs 9. Conjoint Analysis: Choice Models 10. Interaction Detection Methods: AID and CHAID III. INTERDEPENDENCE METHODS 11. Factor Analysis 12. Cluster Analysis: Hierarchical Clustering 13. Cluster Analysis: Partition Clustering 14. Correspondence Analysis 15. Structural Equation Models 16. Multidemensional Scaling of Similarities Data IV. PUTTING IT ALL TOGETHER 17. Squeezing More Useful Information Out of Expensive Consumer Surveys Index

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