Algorithms And Data Structures

Relating Consumer, Descriptive, and Laboratory Data to by Alejandra M. Munoz PDF

By Alejandra M. Munoz

ISBN-10: 0803120737

ISBN-13: 9780803120730

ISBN-10: 0803145357

ISBN-13: 9780803145351

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Extra resources for Relating Consumer, Descriptive, and Laboratory Data to Better Understand Consumer Responses: Manual 30 (Astm Manual Series)

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This type of knowledge would allow tailoring a product to better compete in a specific market. Similarly, when a new product is developed it could be determined whether there was CHAPTER 4 ON STATISTICAL TECHNIQUES 37 a match with one or more of the products from which the discriminant function was generated. The sensory and instrumental data can be used to determine the closeness of match by entering them into the function and finding the probabilities associated with the new product having come from each of the known populations.

Graphic displays are almost always used to assist in the interpretation of the results. Many clustering methods allow for the testing of statistical significance. There are some cases where such testing is neither appropriate nor useful in cluster analysis for data relationships. There are many potential applications for cluster analysis in the study of data relationships. However, it is not universally applicable and requires some skill both in application and interpretation. G. Multidimensional Scaling Methods Multidimensional scaling (MDS) methods cover a broad range of methods to condense data into more meaningful forms [15].

Descriptive Panels Following orientation and training, a group of ten panelists evaluated the twelve dressings for appearance (8 attributes), flavor (21 attributes), and texture (15 attributes). Separate panels were held for appearance, flavor, and texture evaluations, and judgments were replicated over two sessions. For all attributes, intensity was measured using an unstructured line scale ranging from 0 (none) to 15 (extreme). Ratings were averaged across replicates and panelists. Appendix 1 lists all of the descriptive and consumer attributes used in this case study.

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Relating Consumer, Descriptive, and Laboratory Data to Better Understand Consumer Responses: Manual 30 (Astm Manual Series) by Alejandra M. Munoz


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