This oenological data frame concerns the amount of bitterness in 78 bottles of white wine.
A data frame with 4 rows on the following 7 variables.
temperature, with levels cold and warm.
whether contact of the juice with the skin was allowed or avoided, for a specified period. Two levels: no or yes.
numeric vectors, the counts. The order is none to most intense.
The data set comes from Randall (1989) and concerns a factorial experiment for investigating factors that affect the bitterness of white wines. There are two factors in the experiment: temperature at the time of crushing the grapes and contact of the juice with the skin. Two bottles of wine were fermented for each of the treatment combinations. A panel of 9 judges were selected and trained for the ability to detect bitterness. Thus there were 72 bottles in total. Originally, the bitterness of the wine were taken on a continuous scale in the interval from 0 (none) to 100 (intense) but later they were grouped using equal lengths into five ordered categories 1, 2, 3, 4 and 5.
Christensen, R. H. B. (2013) Analysis of ordinal data with cumulative link models—estimation with the R-package ordinal. R Package Version 2013.9-30. https://CRAN.R-project.org/package=ordinal.
Randall, J. H. (1989). The analysis of sensory data by generalized linear model. Biometrical Journal 31(7), 781–793.
Kosmidis, I. (2014). Improved estimation in cumulative link models. Journal of the Royal Statistical Society, Series B, Methodological, 76(1): 169–196.
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