A Comparative Study on Statistics Based on Binary Data and Fuzzy Data in Office Chair Design

Abstract

Consumers’ product style perceptions and preference are vague and uncertain. In order to identify consumers’ needs more accurately, this paper established a questionnaire based on fuzzy data, carried out a spot check to consumers’ style preference and perceptions of twelve office chairs with typical form style, then conducted the mean, distances calculation and fuzzy clustering analysis by Excel, SPSS, and Matlab. Comparing with statistics results of traditional questionnaire data, this paper points out that fuzzy data statistics are suitable for the mean calculation of small sample and the clustering algorithm of few preference variables.