Nonparametrics in Sensory Science is written to complement existing parametric methodology.

Features:

• Outlines innovative new techniques and complements them with real examples
• Includes the most commonly occurring and important experimental designs
• Techniques described may be applied to data where the traditional, most frequently applied nonparametric tests, such as the Kruskal-Wallis, the Friedman and the Spearman tests are applied

Contents

• The Completely Randomized Design
• The Randomized Block Design
• Balanced Incomplete Block Designs
• Correlation Effects
• Categorical Data for Randomized Block Designs
• Goodness of Fit

Index

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