Parametric and Nonparametric Statistics for Sample Surveys and Customer Satisfaction Data

• Κύριοι συγγραφείς: Arboretti, Rosa (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Bathke, Arne (http://id.loc.gov/vocabulary/relators/aut), Bonnini, Stefano (http://id.loc.gov/vocabulary/relators/aut), Bordignon, Paolo (http://id.loc.gov/vocabulary/relators/aut), Carrozzo, Eleonora (http://id.loc.gov/vocabulary/relators/aut), Corain, Livio (http://id.loc.gov/vocabulary/relators/aut), Salmaso, Luigi (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: SpringerBriefs in Statistics,
• Θέματα: Statistics .; Mathematical statistics.; Computer mathematics.; Statistical Theory and Methods.; Probability and Statistics in Computer Science.; Computational Mathematics and Numerical Analysis.

 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. 

 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.