Leseprobe
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End-to-end Data Analytics for Product Development
Mattia De Dominicis, Rosa Arboretti Giancristofaro, Luigi Salmaso, et al.
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Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik
Beschreibung
An interactive guide to the statistical tools used to solve problems during product and process innovation End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction. The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors - noted experts in the field - explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book: * Presents a guide to innovation feasibility and formulation and process development * Contains the statistical tools used to solve challenges faced during product innovation and feasibility * Offers information on stability studies which are common especially in chemical or pharmaceutical fields * Includes a companion website which contains videos summarizing main concepts Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.
Kundenbewertungen
Versuchsplanung, Experimental Design, Datenanalyse, Statistics, Statistik in den Ingenieurwissenschaften, Statistik, Data Analysis, Engineering Statistics