Choose the Proper Statistical Method for Your Sensory Data Issue Analyzing Sensory Data with R gives you the foundation to analyze and interpret sensory data. The book helps you find the most appropriate statistical method to tackle your sensory data issue. Covering quantitative, qualitative, and affective approaches, the book presents the big picture of sensory evaluation. Through an integrated approach that connects the different dimensions of sensory evaluation, you'll understand: * The reasons why sensory data are collected * The ways in which the data are collected and analyzed * The intrinsic meaning of the data * The interpretation of the data analysis results Each chapter corresponds to one main sensory topic. The chapters start with presenting the nature of the sensory evaluation and its objectives, the sensory particularities related to the sensory evaluation, details about the data set obtained, and the statistical analyses required. Using real examples, the authors then illustrate step by step how the analyses are performed in R. The chapters conclude with variants and extensions of the methods that are related to the sensory task itself, the statistical methodology, or both.
Quantitative Descriptive Approaches When panelists rate products according to one single list of attributes Data, sensory issues, notations In practice For experienced users: Measuring the impact of the experimental design on the perception of the products? When products are rated according to one single list of attributes Data, sensory issues, notations In practice For experienced users: Adding supplementary information to the product space When products are rated according to several lists of attributes Data, sensory issues, notations In practice For experienced users: Comparing different panels with Hierarchical Multiple Factor Analysis (HMFA) Qualitative Descriptive Approaches When products are depicted by comments Data, sensory issues, notations In practice For experienced users: Comparing free comments from different panels, the Rorschach test revisited When two different products are put in various experimental contexts Data, sensory issues, notations In practice For experienced users: the Thurstonian approach When products are grouped into homogeneous clusters Data, sensory issues, notations In practice For experienced users: the Hierarchical Sorting Task When products are positioned onto a projective map Data, sensory issues, notations In practice For experienced users: The Sorted Napping(R) Affective Descriptive Approaches When products are solely assessed by liking Data, sensory issues, notations In practice For experienced users: Dealing with multiple hedonic variables and supplementary consumer data When products are described by both liking and external information "independently" Data, sensory issues, notations In practice For experienced users: Finding the best correspondence between the Sensory and Hedonic matrices, using PrefMFA When products are described by a mix of liking and external information Data, sensory issues, notations In practice For experienced users: Assessing the consistency of ideal data in IPM Appendix A: The R survival guide Appendix B: Glossary Index Exercises and Recommended Readings appear at the end of each chapter.
