File: tea.Rd

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r-cran-factominer 2.4-1
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\name{tea}

\alias{tea}

\docType{data}

\title{tea (data)}

\description{
The data used here concern a questionnaire on tea.
We asked to 300 individuals how they drink tea (18 questions), what are their product's perception (12 questions) and some personal details (4 questions).
}

\usage{data(tea)}

\format{
A data frame with 300 rows and 36 columns. Rows represent the individuals,
columns represent the different questions. The first 18 questions are active ones,
the 19th is a supplementary quantitative variable (the age) and the last variables 
are supplementary categorical variables.
}

\examples{
\dontrun{
data(tea)
res.mca=MCA(tea,quanti.sup=19,quali.sup=20:36)
plot(res.mca,invisible=c("var","quali.sup","quanti.sup"),cex=0.7)
plot(res.mca,invisible=c("ind","quali.sup","quanti.sup"),cex=0.8)
plot(res.mca,invisible=c("quali.sup","quanti.sup"),cex=0.8)
dimdesc(res.mca)
plotellipses(res.mca,keepvar=1:4)

## make a hierarchical clustering: click on the tree to define the number of clusters
## HCPC(res.mca)
}
}

\keyword{datasets}