Gacula Jr. / Singh / Jr. Statistical Methods in Food and Consumer Research

2. Auflage 2008
ISBN: 978-0-08-092033-7
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 888 Seiten

Reihe: Food Science and Technology

Statistical Methods in Food and Consumer Research 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 receent 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.
Key Features:
* 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

Autoren/Hrsg.

Gacula Jr., Maximo C.

Singh, Jagbir

Jr.,

Bi, Jian

Altan, Stan

Inhaltsverzeichnis

1;Front Cover;1
2;Statistical Methods in Food and Consumer Research;4
3;Copyright Page;5
4;Dedication Page;6
5;Table of Contents;8
6;Preface to the Second Edition;14
7;Chapter 1: Introduction;16
7.1;1.1 A Brief Review of Tools for Statistical Inference;16
7.1.1;Notation and Symbolism;17
7.1.2;The Normal Distribution;19
7.1.3;Estimation;23
7.1.4;Testing of Hypotheses;24
7.1.5;Experimental Significance;31
7.2;1.2 Principles of Experimental Design;31
7.2.1;Randomization;32
7.2.2;Replication;32
7.2.3;Local Control;32
7.2.4;Blinding;33
7.2.5;Planning the Test Program;34
7.3;1.3 The Role of the Statistician in Research;36
7.3.1;Partnership;36
7.3.2;Client-Consultant Relationship;36
7.4;Exercises;37
8;Chapter 2: Statistical Sensory Testing;40
8.1;2.1 Psychophysical Aspects of Sensory Data;40
8.1.1;Weber´s Law;42
8.1.2;Fechner´s Law;42
8.1.3;Stevens´ Power Law;43
8.1.4;Thurstone´s Law of Comparative Judgment;44
8.2;2.2 Scales of Measurement;45
8.2.1;Hedonic Scale;47
8.2.2;Intensity Rating Scale;49
8.2.3;Rankings;50
8.3;2.3 Scale Structures;50
8.4;2.4 Construction of a Scale;52
8.4.1;Edwards´ Method of Successive Intervals;53
8.4.2;Scaling of Categories;61
8.5;2.5 Distribution of Sensory Data;65
8.5.1;Measures of Shape Distribution;65
8.5.2;Statistical Properties of Subjective Data;67
8.5.3;Transformation;70
8.6;2.6 Selection of Panel Members;72
8.6.1;Criteria Based on Binomial Response;72
8.6.2;Criteria Based on Rating Scale;78
8.6.3;Sequential Analysis;79
8.6.4;Quality Control Chart for Degree of Difference;84
8.7;Exercises;89
9;Chapter 3: The Analysis of Variance and Multiple Comparison Tests;92
9.1;3.1 Analysis of Variance;92
9.1.1;Assumptions in the Analysis of Variance;95
9.1.2;Fixed- and Random-Effects Models;96
9.2;3.2 Multiple-Comparison Tests;113
9.2.1;Least Significant Difference Test;114
9.2.2;Dunnett's Test for Multiple Comparisons with a Control;115
9.2.3;Tukey's Studentized Range Test;116
9.2.4;Duncan's Multiple-Range Test;118
9.2.5;Choice of Multiple-Comparison Tests;120
9.3;3.3 Sample Size Estimation;122
9.3.1;Sample Size for Confidence Interval Estimation;124
9.3.2;Sample Size for Dichotomous Responses;125
9.4;Exercises;126
10;Chapter 4: Experimental Design;128
10.1;4.1 Simple Comparative Experiments;128
10.1.1;Group-Comparison Designs;128
10.1.2;Paired Comparison Designs;130
10.2;4.2 Completely Randomized Designs;136
10.3;4.3 Randomized Complete Block Designs;139
10.3.1;Randomized Complete Block Designs with More Than One Observation per Experimental Unit;143
10.4;4.4 Latin Square Designs;146
10.4.1;Replicating LS Designs;149
10.4.2;Partially Replicated Latin Square;153
10.5;4.5 Cross-Over Designs;157
10.6;4.6 Split Plot Designs;168
10.7;Exercises;181
11;Chapter 5: Incomplete Block Experimental Designs;184
11.1;5.1 Balanced Incomplete Block Designs;184
11.1.1;Parameters of Balanced Incomplete Block Designs;185
11.1.2;Intrablock Analysis;186
11.1.3;Interblock Analysis;192
11.1.4;Combining Intrablock and Interblock Estimates;192
11.2;5.2 Balanced Incomplete Block Designs Augmented with a Control;197
11.3;5.3 Doubly Balanced Incomplete Block Designs;202
11.4;5.4 Composite Complete-Incomplete Block Designs;209
11.4.1;Intrablock Analysis;213
11.5;Exercises;217
12;Chapter 6: Factorial Experiments;220
12.1;6.1 The 2n Factorial Experiments;221
12.2;6.2 The 3n Factorial Experiments;231
12.3;6.3 The p x q and p x q x k Factorial Experiments;240
12.3.1;Confounding in 2n Factorial Experiments;249
12.3.2;Fractional Factorial;252
12.4;Exercises;259
13;Chapter 7: Response Surface Designs and Analysis;262
13.1;7.1 General Concepts;262
13.1.1;Construction of Response Surfaces;266
13.2;7.2 Fitting of Response Surfaces and Some Design Considerations;271
13.3;7.3 Illustrations of Fittings of First- and Second-Order Models;278
13.4;7.4 Composite Designs;290
13.4.1;Composite Designs from Fractional Factorials;297
13.4.2;A 1/2 Replicate of 24;297
13.4.3;A 1/2 Replicate of 26;298
13.5;7.5 Rotatable Designs;301
13.5.1;Composite Rotatable Designs;307
13.5.2;Arrangements of Composite Designs in Blocks;309
13.6;7.6 A Response Surface Analysis Approach for Sensory Data;319
13.7;Exercises;323
14;Chapter 8: Shelf Life Testing Experiments;326
14.1;8.1 Hazard Function;327
14.2;8.2 Shelf Life Models;331
14.2.1;Normal Distribution;332
14.2.2;Lognormal Distribution;333
14.2.3;Weibull Distribution;335
14.2.4;Graphical Test for Failure Distributions;343
14.3;8.3 Regression Analysis;346
14.3.1;Confidence Intervals;355
14.3.2;Nonlinear Relationships;360
14.4;Exercises;363
15;Chapter 9: Nonparametric Statistical Methods;366
15.1;9.1 Some Methods for Binary Data;366
15.1.1;Tests for Independent Proportions;366
15.1.2;Tests for Dependent Proportions;374
15.1.3;Combining 2 x 2 Contingency Tables;379
15.1.4;Measure of Association for 2 x 2 Tables;384
15.2;9.2 Some Methods Based on Ranks;385
15.2.1;Rank Tests for Single and Paired Samples;386
15.2.2;Rank Tests for Two Independent Samples;393
15.2.3;Rank Tests for Multiple Independent Samples;404
15.2.4;Rank Tests for Multiple Related Samples;410
15.2.5;Measures of Association for Ranking Data;419
15.3;9.3 Some Methods for Categorical Data;429
15.3.1;Contingency Tables and Chi-square Statistics;429
15.3.2;Goodness of Fit Tests;433
15.3.3;Analysis of r x c Contingency Tables;437
15.3.4;Measures of Association for r x c Contingency Tables;445
15.3.5;Analysis of Square (r x r) Contingency Tables;448
15.4;9.4 Multidimensional Contingency Tables;453
15.4.1;Introduction;453
15.4.2;Simpson´s Paradox;454
15.4.3;Tests for Independence;456
15.4.4;Numerical Example for Tests for Independence;458
15.5;Exercises;464
16;Chapter 10: Sensory Difference and Similarity Tests;470
16.1;10.1 Sensory Difference Tests;470
16.1.1;Triangle Test;470
16.1.2;Duo-Trio Test;486
16.1.3;Pair Difference Test (2-AFC);488
16.1.4;Three-Alternative Forced-Choice Test (3-AFC);492
16.1.5;A-Not A Test;493
16.1.6;Same-Different Test;499
16.1.7;Comparisons of Difference Test Designs;500
16.2;10.2 Sensory Similarity (Equivalence) Tests;511
16.2.1;Introduction;511
16.2.2;Similarity Tests Using Forced-Choice Methods;512
16.2.3;Similarity Tests Using the Paired Comparison Method;513
16.2.4;Similarity Tests Using A-Not A and Same-Different Methods;516
16.2.5;Similarity Tests for Continuous Data;518
16.2.6;Similarity Tests for Correlated Data;521
16.2.7;Hypothesis Test and Confidence Interval for Similarity Evaluation;525
16.3;10.3 Replicated Difference and Similarity Tests;529
16.3.1;Introduction;529
16.3.2;The Beta-Binomial (BB) Model;530
16.3.3;Tests Based on the BB Model;537
16.3.4;The Corrected Beta-Binomial (CBB) Model;547
16.3.5;Tests Based on the CBB Model;551
16.3.6;The Dirichlet-Multinomial (DM) Model;555
16.3.7;Tests Based on the DM Model;560
16.4;Exercises;567
17;Chapter 11: The Method of Paired Comparisons in Sensory Tests and Thurstonian Scaling;574
17.1;11.1 Paired Comparison Designs;574
17.1.1;Completely Balanced Paired Comparison Designs;574
17.1.2;Incomplete Balanced Paired Comparison Designs;579
17.2;11.2 Paired Comparison Models;586
17.2.1;The Scheffacute Model;586
17.2.2;The Bradley-Terry Model;597
17.2.3;The Thurstone-Mosteller Model;611
17.2.4;Choice of Models;620
17.3;11.3 Thurstonian Discriminal Distance d´;622
17.3.1;Introduction;622
17.3.2;Estimation of d´;624
17.3.3;Variance of d´;629
17.3.4;Tables and S-PLUS Codes for d´ and Variance of d´;635
17.3.5;Confidence Intervals and Tests for d´;636
17.4;11.4 Area Under ROC Curve and R-Index;639
17.4.1;Introduction;639
17.4.2;Estimating R-Index and Its Variance;640
17.4.3;Difference Testing Using R-Index;642
17.4.4;Similarity Testing Using R-Index;644
17.4.5;Linking R-Index with d´;645
17.4.6;Same-Different Area Theorem;647
17.4.7;Exercises;650
18;Chapter 12: Descriptive Analysis and Perceptual Mapping;656
18.1;12.1 Descriptive Analysis;656
18.2;12.2 Consumer Tests;657
18.2.1;In-House Consumer Test;657
18.2.2;Home-Use Consumer Test;658
18.2.3;Central Location Consumer Test;659
18.3;12.3 Hedonic and Intensity Rating Scales;659
18.3.1;Just-About-Right Rating Scale;660
18.3.2;Signal-to-Noise Ratio;661
18.3.3;Questionnaire Design;668
18.4;12.4 Perceptual Mapping;674
18.4.1;Factor Analysis;675
18.4.2;Principal Component Analysis;689
18.5;12.5 Preference Mapping;694
18.6;Exercises;700
19;Chapter 13: Sensory Evaluation in Cosmetic Studies;702
19.1;13.1 Experimental Designs;702
19.1.1;Clinical Study Data;703
19.1.2;Self-Controlled Design;706
19.1.3;Parallel Design;713
19.1.4;Cross-Over Design;716
19.2;13.2 Regression Analysis;721
19.2.1;Polynomial Regression;721
19.2.2;Nonlinear Regression;725
19.2.3;Fit of Nonlinear Regression Model;733
19.3;Exercises;734
20;Appendix: Statistical Tables;736
20.1;Tables;736
21;References;844
22;Index;860
23;Food Science and Technology International Series;866