BeersProjectiveMapping:
7 (fictitious) assessors evaluated 7 Beers using
Projective Mapping (with verbal description).
data("BeersProjectiveMapping")a list with 3 elements:
1) ProjectiveMapping:
a matrix of dimensions 7 beers by 7*2
assessors-dimensions of the coordinates of the beers on the sheet
of paper;
2) Vocabulary: a Beers (rows) by Assessors (columns)
data.frame
where each element of Vocabulary
stores
the words used by one assessor to describe a beer
(words are separated with spaces);
and 3) CT.vocabulary a matrix storing
the \(I\) Products by \(N\)
words (from the Vocabulary) contingency table,
in CT.vocabulary the number at the intersection
of a row (beer) and a column (word) is the number
of assessors who used this word to describe that beer.
Hervé Abdi
First, Each assessor positioned the 7 beers on a sheet of paper according to the perceived similarity between the beers. For each assessor, the position of the beers was recorded from the \(X\) and \(Y\) coordinates. Second, the assessors were asked if they could describe each beer with some freely chosen descriptors. These descriptors are stored in a dataframe with 7 elements (one per assessor) where each element of the dataframe is a 7 component vector (one per beer) where each element stores the words used to describe a beer (words are separated with spaces).
Abdi, H., & Valentin, D., (2007). Some new and easy ways to describe, compare, and evaluate products and assessors. In D., Valentin, D.Z. Nguyen, L. Pelletier (Eds) New trends in sensory evaluation of food and non-food products. Ho Chi Minh (Vietnam): Vietnam National University & Ho Chi Minh City Publishing House. pp. 5-18.