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Data Relationships and Multivariate Applications

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Sensory Evaluation of Food

Abstract

Descriptive sensory tests are often performed to determine the effects of changes in raw material, processing, and packaging on the sensory qualities of products. It is also frequently desirable to relate the hedonic results of a study to the sensory and/or instrumental results of the same study. In all of these cases, multiple attributes on a single set of samples were evaluated and must now be related. To do this, one must use a group of analysis tools known as multivariate statistics. During the last 20 years, the widespread access to computers and the increasing sophistication in statistical packages have expanded the use and utility of multivariate statistical analyses. However, this “easy access” has tempted novices to use them with often surprising (and suspect) results. Before using any of these techniques, the user must be sure that the method is used appropriately and correctly. Many multivariate techniques require additional statistical assumptions beyond those of the simple univariate tests. This leads to additional liabilities and potential pitfalls when using multivariate methods.

The researcher will find that there are certain costs associated with benefits of using multivariate procedures. Benefits from increased flexibility in research design, for instance, are sometimes negated by increased ambiguity in interpretation of results.—Tabachnick and Fidell, 1983, p. 8.

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Authors and Affiliations

  1. Cornell University, USA

    Harry T. Lawless

  2. University of Missouri, USA

    Hildegarde Heymann

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  1. Harry T. Lawless
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  2. Hildegarde Heymann
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© 1999 Springer Science+Business Media New York

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Lawless, H.T., Heymann, H. (1999). Data Relationships and Multivariate Applications. In: Sensory Evaluation of Food. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-7843-7_17

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  • DOI: https://doi.org/10.1007/978-1-4615-7843-7_17

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4615-7845-1

  • Online ISBN: 978-1-4615-7843-7

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