End-to-end Data Analytics for Product Development
A Practical Guide for Fast Consumer Goods Companies, Chemical Industry and Processing Tools Manufacturers
- English
- ePUB (mobile friendly)
- Available on iOS & Android
End-to-end Data Analytics for Product Development
A Practical Guide for Fast Consumer Goods Companies, Chemical Industry and Processing Tools Manufacturers
About This Book
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 ā noted experts in the field ā 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:
ā¢ Presents a guide to innovation feasibility and formulation and process development
ā¢ Contains the statistical tools used to solve challenges faced during product innovation and feasibility
ā¢ Offers information on stability studies which are common especially in chemical or pharmaceutical fields
ā¢ 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.
Frequently asked questions
Information
1
Basic Statistical Background
1.1 Introduction
Topics | Stat tools |
Statistical variables and types of data | 1.1 |
Statistical Units, populations, samples | 1.2 |
Introduction to descriptive and inferential analyses | 1.3, 1.12, 1.13 |
Data distributions | 1.4, 1.5 |
Mean values | 1.6, 1.7 |
Measures of variability | 1.8, 1.9, 1.10 |
Boxplots | 1.11 |
Introduction to confidence intervals | 1.14 |
Introduction to hypothesis testing procedures, including the pāvalue approach | 1.15, 1.16 |
Learning Objectives and Outcomes
- Recognize and distinguish between different types of variables.
- Distinguish between a population and a sample and know the meaning of random sampling.
- Detect the shape of data distributions.
- Calculate and interpret descriptive measures (means, measures of variability).
- Understand the basic concept and interpretation of a confidence interval.
- Understand the general idea of hypothesis testing.
- Understand the pāvalue approach to hypothesis testing.
Stat Tool 1.1 Statistical Variables and Types of Data
Table of contents
- Cover
- Table of Contents
- Biographies
- Preface
- About the Companion Website
- 1 Basic Statistical Background
- 2 The Screening Phase
- 3 Product Development and Optimization
- 4 Other Topics in Product Development and Optimization: Response Surface and Mixture Designs
- 5 Product Validation
- 6 Consumer Voice
- References
- Index
- End User License Agreement