{"product_id":"end-to-end-data-analytics-for-product-development-isbn-9781119483694","title":"End-to-end Data Analytics for Product Development","description":"\u003cp\u003e\u003cb\u003eAn interactive guide to the statistical tools used to solve problems during product and process innovation\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eEnd to End Data Analytics for Product Development \u003c\/i\u003eis 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.\u003c\/p\u003e \u003cp\u003eThe 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:\u003c\/p\u003e \u003cp\u003e•          Presents a guide to innovation feasibility and formulation and process development\u003c\/p\u003e \u003cp\u003e•          Contains the statistical tools used to solve challenges faced during product innovation and feasibility\u003c\/p\u003e \u003cp\u003e•          Offers information on stability studies which are common especially in chemical or pharmaceutical fields\u003c\/p\u003e \u003cp\u003e•          Includes a companion website which contains videos summarizing main concepts\u003c\/p\u003e \u003cp\u003eWritten for undergraduate students and practitioners in industry, \u003ci\u003eEnd to End Data Analytics for Product Development\u003c\/i\u003e offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.\u003c\/p\u003e \u003cp\u003eBiographies vii\u003c\/p\u003e \u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003eAbout the Companion Website xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Basic Statistical Background 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 The Screening Phase 23\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 23\u003c\/p\u003e \u003cp\u003e2.2 Case Study: Air Freshener Project 24\u003c\/p\u003e \u003cp\u003e2.2.1 Plan of the Screening Experiment 24\u003c\/p\u003e \u003cp\u003e2.2.2 Plan of the Statistical Analyses 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Product Development and Optimization 57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 57\u003c\/p\u003e \u003cp\u003e3.2 Case Study for Single Sample Experiments: Throat Care Project 59\u003c\/p\u003e \u003cp\u003e3.2.1 Comparing the Mean to a Specified Value 60\u003c\/p\u003e \u003cp\u003e3.2.2 Comparing a Proportion to a Specified Value 67\u003c\/p\u003e \u003cp\u003e3.3 Case Study for Two‐Sample Experiments: Condom Project 73\u003c\/p\u003e \u003cp\u003e3.3.1 Comparing Variability Between Two Groups 74\u003c\/p\u003e \u003cp\u003e3.3.2 Comparing Means Between Two Groups 81\u003c\/p\u003e \u003cp\u003e3.3.3 Comparing Two Proportions 85\u003c\/p\u003e \u003cp\u003e3.4 Case Study for Paired Data: Fragrance Project 93\u003c\/p\u003e \u003cp\u003e3.5 Case Study: Stain Removal Project 104\u003c\/p\u003e \u003cp\u003e3.5.1 Plan of the General Factorial Experiment 104\u003c\/p\u003e \u003cp\u003e3.5.2 Plan of the Statistical Analyses 110\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Other Topics in Product Development and Optimization: Response Surface and Mixture Designs 137\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 137\u003c\/p\u003e \u003cp\u003e4.2 Case Study for Response Surface Designs: Polymer Project 138\u003c\/p\u003e \u003cp\u003e4.2.1 Plan of the Experimental Design 139\u003c\/p\u003e \u003cp\u003e4.2.2 Plan of the Statistical Analyses 150\u003c\/p\u003e \u003cp\u003e4.3 Case Study for Mixture Designs: Mix‐Up Project 166\u003c\/p\u003e \u003cp\u003e4.3.1 Plan of the Experimental Design 167\u003c\/p\u003e \u003cp\u003e4.3.2 Plan of the Statistical Analyses 199\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Product Validation 213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 213\u003c\/p\u003e \u003cp\u003e5.2 Case Study: GERD Project 215\u003c\/p\u003e \u003cp\u003e5.2.1 Evaluation of the Relationship among Quantitative Variables 215\u003c\/p\u003e \u003cp\u003e5.3 Case Study: Shelf Life Project (Fixed Batch Factor) 243\u003c\/p\u003e \u003cp\u003e5.4 Case Study: Shelf Life Project (Random Batch Factor) 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Consumer Voice 257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 257\u003c\/p\u003e \u003cp\u003e6.2 Case Study: “Top‐Two Box” Project 259\u003c\/p\u003e \u003cp\u003e6.3 Case Study: DOE – Top Score Project 284\u003c\/p\u003e \u003cp\u003e6.3.1 Plan of the Factorial Design 284\u003c\/p\u003e \u003cp\u003e6.3.2 Plan of the Statistical Analyses 285\u003c\/p\u003e \u003cp\u003e6.4 Final Remarks 291\u003c\/p\u003e \u003cp\u003eReferences 293\u003c\/p\u003e \u003cp\u003eIndex 295\u003c\/p\u003e   \u003cp\u003e\u003cb\u003eROSA ARBORETTI\u003c\/b\u003e is Associate Professor of Statistics at the Department of Civil, Environmental and Architectural Engineering at the University of Padova, Italy. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMATTIA DE DOMINICIS\u003c\/b\u003e is a former R\u0026amp;D Vice-President in Household and Personal Care at Reckitt Benckiser in Venice, Italy. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eCHRIS JONES\u003c\/b\u003e is Vice President of R\u0026amp;D in Hygiene Home at Reckitt Benckiser in Montvale, USA. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eLUIGI SALMASO\u003c\/b\u003e is Full Professor of Statistics and Deputy Chair of the Department of Management and Engineering at the University of Padova, Italy.   \t \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAN INTERACTIVE GUIDE TO THE STATISTICAL TOOLS USED TO SOLVE PROBLEMS DURING PRODUCT AND PROCESS INNOVATION\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eEnd-to-End Data Analytics for Product Development\u003c\/i\u003e 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. \u003c\/p\u003e\u003cp\u003eThe 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. \u003c\/p\u003e\u003cp\u003eThe book: \u003c\/p\u003e\u003cul\u003e \u003cli\u003ePresents a guide to innovation feasibility and formulation and process development\u003c\/li\u003e \u003cli\u003eContains the statistical tools used to solve challenges faced during product innovation and feasibility\u003c\/li\u003e \u003cli\u003eOffers information on stability studies which are common especially in chemical or pharmaceutical fields\u003c\/li\u003e \u003cli\u003eIncludes a companion website which contains videos summarizing main concepts\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eWritten for undergraduate and graduate students or practitioners in the industry, \u003ci\u003eEnd-to-End Data Analytics for Product Development\u003c\/i\u003e offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989131280613,"sku":"NP9781119483694","price":91.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119483694.jpg?v=1761782922","url":"https:\/\/k12savings.com\/products\/end-to-end-data-analytics-for-product-development-isbn-9781119483694","provider":"K12savings","version":"1.0","type":"link"}