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Line 8: Why introduce several groups of variables active in the same factorial analysis? '' ~~edwin~~data'' Let us consider the case of quantitative variables, that is to say, within the framework of the PCA. An example of data from ecological research provides a useful illustration. There are, for 72 stations, two types ofo f measurements. # The abundance-dominance coefficient of 50 plant species (coefficient ranging from 0 = the plant is absent, to 9 = the species covers more than three-quarters of the surface). The whole set of the 50 coefficients defines the floristic profile of a station. # Eleven pedological measurements (Pedology = soil science): particle size, physical, chemistry, etc. The set of these eleven measures defines the pedological profile of a station.

Multiple factor analysis: Difference between revisions