Computing Ideal Number of Test Subjects - Sensorial Map Parametrization

Abstract : A sensory analysis was carried using a special napping table on two different set of products in order to investigate on texture perception of material, the tests were done using a human panel. The data collected were analyzed through multiple factor analysis (MFA) which is a particular case of principal component analysis (PCA). The aim of this study is to know the minimum number of subjects in the human panel that can guarantee a meaningful statistical analysis of data, and so far allows a better understanding of the sensory results. We built a particular function that measures the similarity between two representations (two matrices) which are computed using the output of Napping table. Based on this function and using the whole datasets an algorithm able to measure the robustness is implemented. We found on the two datasets that a minimum number of subjects between 10 and 12 seems to insure a stable and robust statistical analysis of the sensory results.
Type de document :
Communication dans un congrès
8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Nov 2016, Porto, Portugal. pp.437-442, Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. 〈10.5220/0006086404370442〉
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https://hal-emse.ccsd.cnrs.fr/emse-01411915
Contributeur : Florent Breuil <>
Soumis le : mercredi 7 décembre 2016 - 17:06:55
Dernière modification le : dimanche 15 octobre 2017 - 22:44:06

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Jessica Dacleu Ndengue, Mihaela Juganaru-Mathieu, Jenny Faucheu. Computing Ideal Number of Test Subjects - Sensorial Map Parametrization. 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Nov 2016, Porto, Portugal. pp.437-442, Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. 〈10.5220/0006086404370442〉. 〈emse-01411915〉

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