The theme of this book is simple. The price, the number someone puts on a product to help consumers decide to buy that product, comes from data. Specifically, it comes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly provide the background and framework for the models. Therefore, this book emphasizes two interlocking components of modeling: economic theory and statistical principles.
The theme of this book is simple. The price, the number someone puts on a product to help consumers decide to buy that product, comes from data. Specifically, it comes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly provide the background and framework for the models. Therefore, this book emphasizes two interlocking components of modeling: economic theory and statistical principles.
Walter R. Paczkowski, Ph.D., worked at AT&T, AT&T Bell Labs, and AT&T Labs. He founded Data Analytics Corp., a statistical consulting company, in 2001. Dr. Paczkowski is also a part- time lecturer of economics at Rutgers University. He published Market Data Analysis Using JMP in 2016.
Inhaltsangabe
List of Figures List of Tables 1 Preface I Background 1 Introduction 2 Elasticities - Background and Concept 3 Elasticities - Their Use in Pricing II Stated Preference Models 4 Conjoint Analysis 5 Discrete Choice Models 6 MaxDiff Models 7 Other Stated Preference Methods III Price Segmentation 8 Price Segmentation: Basic Models 9 Price Segmentation: Advanced Models IV Big Data and Econometric Models 10 Working with Big Data 11 Big Data Pricing Models 12 Big Data and Nonlinear Prices References
List of Figures List of Tables 1 Preface I Background 1 Introduction 2 Elasticities - Background and Concept 3 Elasticities - Their Use in Pricing II Stated Preference Models 4 Conjoint Analysis 5 Discrete Choice Models 6 MaxDiff Models 7 Other Stated Preference Methods III Price Segmentation 8 Price Segmentation: Basic Models 9 Price Segmentation: Advanced Models IV Big Data and Econometric Models 10 Working with Big Data 11 Big Data Pricing Models 12 Big Data and Nonlinear Prices References
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