sixteenGums4Descriptors | R Documentation |
sixteenGums4Descriptors
:
the average data obtained
from ten tasters who evaluated
sixteen chewing gums on
the intensity of four descriptors.
These data can be used to illustrate:
un-normed (or normed)
Principal Component Analysis (PCA)
and Correspondence Analysis (MCA).
The data are the averages
(computed
over the 10 judges) of the
intensity ratings of the 4 descriptors for
the 16 gums.
data("sixteenGums4Descriptors",
package = 'data4PCCAR')
A list
(of class: sixteenGums
)
containing
one data frame,
and several vectors:
ratingsIntensity:
A data frame of dimension
I =
16 rows (Beers) by
J =
4 columns
(descriptors) with
the average intensity ratings performed using
different scales per variables
(respectively: 10, 5, 5, 100
points).
longNames:
a 16 element vector with the long names of the gums.
color4Products
a 16 element vector with the
color names of the gums.
color4Descriptors
a 4 element vector with the
color names of the descriptors.
scale
a 4 element vector with the
number of points of the scales used
to describe the gums.
Hervé Abdi & Carlos Gomez.
These data are used in Abdi H, Gomez, C., & Delmas, M. (2022). Méthodes Statistiques Multivariées pour l'Analyse Sensorielle et les Etudes Consommateurs.
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