Principal component analysis (PCA) is a popular technique for summarizing and exploring multivariate data sets. We propose how to conduct PCA of results from sensory studies that have a special structure, where only a subset of the product paired comparisons are of interest. We illustrate the proposed approach with two data sets, both from trained sensory panels. In the first
This workshop explores current topics and trends in sensometrics, and includes engaging presentations, arguments, and a panel discussion. Focus is on general concepts rather than technical details, making the workshop of interest to a general audience with an introductory knowledge of statistics.
Discrimination Testing in Sensory Science: A Practical Handbook is a one-stop-shop for practical advice and guidance on the performance and analysis of discrimination testing in sensory science. The book covers all aspects of difference testing: the history and origin of different methods, the practicalities of setting up a difference test, replications, the statistics behind each test, dealing with the analysis,