End-to-end Data Analytics for Product Development. Chris Jones

Чтение книги онлайн.

      1  Cover

      2  Biographies

      3  Preface

      4  About the Companion Website

      5  1 Basic Statistical Background 1.1 Introduction

      6  2 The Screening Phase 2.1 Introduction 2.2 Case Study: Air Freshener Project

      7  3 Product Development and Optimization 3.1 Introduction 3.2 Case Study for Single Sample Experiments: Throat Care Project 3.3 Case Study for Two‐Sample Experiments: Condom Project 3.4 Case Study for Paired Data: Fragrance Project 3.5 Case Study: Stain Removal Project

      8  4 Other Topics in Product Development and Optimization: Response Surface and Mixture Designs 4.1 Introduction 4.2 Case Study for Response Surface Designs: Polymer Project 4.3 Case Study for Mixture Designs: Mix‐Up Project

      9  5 Product Validation 5.1 Introduction 5.2 Case Study: GERD Project 5.3 Case Study: Shelf Life Project (Fixed Batch Factor) 5.4 Case Study: Shelf Life Project (Random Batch Factor)

      10  6 Consumer Voice 6.1 Introduction 6.2 Case Study: “Top‐Two Box” Project 6.3 Case Study: DOE – Top Score Project 6.4 Final Remarks

      11  References

      12  Index

      13  End User License Agreement

      1 Chapter 5Table 5.1 Raw data.Table 5.2 Raw data.

      2 Chapter 6Table 6.1 Cross‐tabulation.Table 6.2 Cross‐tabulation of purchase intent by gender.Table 6.3 Counts and conditional percentages.Table 6.4 Cross‐tabulation of purchase intent by gender and chi‐square test re...Table 6.5 Odds ratios.

      1 Chapter 1Figure 1.1 Population, samples, sampling units.Figure 1.2 Shapes of distributions.Figure 1.3 Shapes of distributions (symmetric and skewed distributions).Figure 1.4 Other shapes of distributions.Figure 1.5 Mean and median in symmetric distributions.Figure 1.6 Mean and median in skewed distributions.Figure 1.7 Quartiles.Figure 1.8 Frequency distributions and variability.Figure 1.9 Dotplot.Figure 1.10 Histograms and boxplots.

      2 Chapter 2Figure 2.1 Process variables and conditions.Figure 2.2 Response, factors, and levels.Figure 2.3 Factors, levels, and treatments.Figure 2.4 Full and fractional designs and treatments.Figure 2.5 Advantages and disadvantages of full and fractional designs treat...Figure 2.6 Randomized design for plastic tensile strength (Example 2.1).Figure 2.7 Advantages of randomization.Figure 2.8 Advantages of blocking.Figure 2.9 RCBD for plastic tensile strength.Figure 2.10 Presence of replications for plastic tensile strength (Example 2...Figure 2.11 Advantages of replication.Figure 2.12 Model assumptions for ANOVA (Example 2.4).Figure 2.13 Residuals versus order plots.Figure 2.14 Normal probability plots.Figure 2.15 Normal distribution.Figure 2.16 Residuals versus fitted values plots.

      3 Chapter 3Figure 3.1 Desirability plots with different goals.

      4 Chapter 4Figure 4.1 Response surface plot for a first‐order (linear) model (graph A) ...Figure 4.2 Central composite designs for k = 2 and k = 3.Figure 4.3 Spherical CCD for k = 2 with α =

      5 Chapter 5Figure 5.1 Scatterplot of thickness vs. CEW; each point representing one obs...Figure 5.2 Scatterplot of thickness vs. CEW showing a moderate linear relati...Figure 5.3 Strength and direction of correlations.Figure 5.4 Scatterplot of thickness vs. CEW showing a strong, positive relat...Figure 5.5 Scatterplot of thickness vs. CEW showing a very strong relationsh...Figure 5.6 Scatterplot of thickness vs. CEW with regression line.Figure 5.7 Scatterplot of thickness vs. CEW with regression line, CEW = 6.25...Figure 5.8 Scatterplot of thickness vs. CEW showing a statistically signific...Figure 5.9 Residuals.Figure 5.10 Residuals versus order plots.Figure 5.11 Normal distribution.Figure 5.12 Normal probability plots.Figure 5.13 Residuals versus fitted values plots.

      6 Chapter 6Figure 6.1 Bar chart of purchase intent by gender (%).Figure 6.2 Scatterplots.Figure 6.3 Different categorical response variables.

      1  Cover

      2 Table of Contents

      3  СКАЧАТЬ