Managerial Applications of Multivariate Analysis in Marketing
Butterworth-Heinemann (Publisher)
Published on 31. March 2003
Book
Hardback
395 pages
978-0-87757-301-2 (ISBN)
Description
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.
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.
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.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 231 mm
Width: 160 mm
Thickness: 38 mm
Weight
800 gr
ISBN-13
978-0-87757-301-2 (9780877573012)
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Schweitzer Classification
Content
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