Statistical Methods in Food and Consumer Research

1 INTRODUCTION
1.1 A Brief Review of Tools for Statistical Interference
1.2 Principles of Experimental Design
1.3 The Role of the Statistician in Research
Exercises

2 STATISTICAL SENSORY TESTING
2.1 Psychophysical Aspects of Sensory Data
2.2 Scales of Measurement
2.3 Scale Structures
2.4 Construction of a Scale
2.5 Distribution of Sensory Data
2.6 Selection of Panel Members
Exercises

3 THE ANALYSIS OF VARIANCE AND MULTIPLE COMPARISON TESTS
3.1 Analysis of Variance
3.2 Multiple-Comparison Tests
3.3 Sample Size Estimation
Exercises

4 EXPERIMENTAL DESIGN
4.1 Simple Comparative Experiments
4.2 Completly Randomized Designs
4.3 Randomized Complete Block Designs
4.4 Latin Square Designs
4.5 Cross-Over Designs
4.6 Split Plot Designs
Exercises

5 INCOMPLETE BLOCK EXPERIMENTAL DESIGNS
5.1 Balanced Incomplete Block Designs
5.2 Balanced Incomplete Block Designs Augmented with a Control
5.3 Doubly Balanced Incomplete Block Designs
5.4 Composite Complete-Incomplete Block Designs
Exercises

6 FACTORAL EXPERIMENTS
6.1 The 2n Factorial Experiments
6.2 The 3n Factorial Experiments
6.3 The p x q and p x q x k Factorial Experiments
6.4 Simple Confounding and Fractional Factoral Experiments
Exercises

7 RESPONSE SURFACE DESIGNS AND ANALYSIS
7.1 General Concepts
7.2 Fitting of Response Surfaces and Some Design Considerations
7.3 Illustrations of Fittings of First- and Second-Order Models
7.4 Composite Designs
7.5 Rotatable Designs
7.6 A Response Surface Analysis Approach for Sensory Data
Exercises

8 SHELF LIFE TESTING EXPERIMENTS
8.1 Hazard Function
8.2 Shelf Life Models
8.3 Regression Analysis
Exercises

9 NONPARAMETRIC STATISTICAL METHODS
9.1 Some Methods for Binary Data
9.2 Some Methods Based on Ranks
9.3 Some Methods for Categorical Data
9.4 Multidimensional Contingency Tables
Exercises

10 SENSORY DIFFERENCE AND SIMILARITY TESTS
10.1 Sensory Difference Tests
10.2 Sensory Similarity (Equivalence) Tests
10.3 Replicated Difference and Similarity Tests
Exercises

11 THE METHOD OF PAIRED COMPARISONS IN SENSORY TESTS AND THURSTONIAN SCALING
11.1 Paired Comparison Designs
11.2 Paired Comparison Models
11.3 Thurstonian Discriminal Difference d'
11.4 Area Under ROC Curve and R-Index
Exercises

12 DESCRIPTIVE ANALYSIS AND PERCEPTUAL MAPPING
12.1 Descriptive Analysis
12.2 Consumer Tests
12.3 Hedonic and Intensity Rating Scales
12.4 Perceptual Mapping
12.5 Perference Mapping
Exercises

13 SENSORY EVALUATION IN COSMETIC STUDIES
13.1 Experimental Designs
13.2 Regression Analysis
Exercises

Statistical Methods in Food and Consumer Research, Second Edition, continues to be the only book to focus solely on the statistical techniques used in sensory testing of foods, pharmaceuticals, cosmetics, and other consumer products. This new edition includes the most recent applications of statistical methods, and features significant updates as well as two new chapters.

Covering the application of techniques including R-index, the Bayesian approach for sensory differences tests, and preference mapping in addition to several other methodologies, this is the comprehensive reference needed by those studying sensory evaluation and applied statistics in agriculture and biological sciences.

Research professionals working with food, beverages, healthcare, cosmetics, and other related areas will find the book a valuable guide to the variety of statistical methods available.

• Provides comprehensive coverage of statistical techniques in sensory testing
• Includes data compiled from real-world experiments
• Covers the latest in data interpretation and analysis
• Addresses key methods such as R-index, Thursonian Discriminal Distances, group sequential tests, beta-binomial tests, sensory difference and similarity tests, just-about-right data, signal-to-noise ratio, analysis of cosmetic data, Descriptive Analysis, claims substantiation and preference mapping

Students in sensory evaluation courses in both biological and agricultural departments can use this book as a text for their applied statistics requirements. Expanding industrial application of statistics to sensory science, foods, beverages and other related areas make this update ideal for professional reference use as well.