Parametric and Nonparametric Statistics for Sample Surveys and Customer Satisfaction Data -
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Brand new, In English, Fast shipping from London, UK; Tout neuf, en anglais, expédition rapide depuis Londres, Royaume-Uni;ria9783319917399_dbm
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Présentation Parametric And Nonparametric Statistics For Sample Surveys And Customer Satisfaction Data de Collectif Format Broché
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Résumé : This book deals with problems related to the evaluation of customer satisfaction in very different contexts and ways. Often satisfaction about a product or service is investigated through suitable surveys which try to capture the satisfaction about several partial aspects which characterize the perceived quality of that product or service. This book presents a series of statistical techniques adopted to analyze data from real situations where customer satisfaction surveys were performed. The aim is to give a simple guide of the variety of analysis that can be performed when analyzing data from sample surveys: starting from latent variable models to heterogeneity in satisfaction and also introducing some testing methods for comparing different customers. The book also discusses the construction of composite indicators including different benchmarks of satisfaction. Finally, some rank-based procedures for analyzing survey data are also shown.
Biographie: Rosa Arboretti received her PhD in Statistical Methodology for Scientific Research at the University of Bologna. She is currently Associate Professor at the Department of Civil, Architectural and Environmental Engineering of the University of Padova. Her main research interests are related to Statistical Methods applied to Biomedicine and Engineering. Arne Bathke?is Full Professor of Statistics at the University of Salzburg. His main research interests are related to Nonparametric and Multivariate Statistics applied in different fields from Social Sciences to Biomedicine and Engineering.
Sommaire: Chapter 1. The CUB models.- Chapter 2. Customer satisfaction heterogeneity.- Chapter 3. Ranking multivariate populations.- Chapter 4. Composite indicators and satisfaction profiles.- Chapter 5. Analyzing Survey Data Using Multivariate Rank-Based Inference
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