HairEyeColor
Hair and Eye Color of Statistics Students
Distribution of hair and eye color and sex in 592 statistics students.
Usage
HairEyeColor
Format
A 3-dimensional array resulting from cross-tabulating 592 observations on 3 variables. The variables and their levels are as follows:
| No | Name | Levels |
| 1 | Hair | Black, Brown, Red, Blond |
| 2 | Eye | Brown, Blue, Hazel, Green |
| 3 | Sex | Male, Female |
Details
The Hair x Eye table comes rom a survey of students at the University of Delaware reported by Snee (1974). The split by Sex was added by Friendly (1992a) for didactic purposes.
This data set is useful for illustrating various techniques for the analysis of contingency tables, such as the standard chi-squared test or, more generally, log-linear modelling, and graphical methods such as mosaic plots, sieve diagrams or association plots.
Source
http://euclid.psych.yorku.ca/ftp/sas/vcd/catdata/haireye.sas
Snee (1974) gives the two-way table aggregated over Sex. The Sex split of the ‘Brown hair, Brown eye’ cell was changed to agree with that used by Friendly (2000).
References
Snee, R. D. (1974) Graphical display of two-way contingency tables. The American Statistician, 28, 9–12.
Friendly, M. (1992a) Graphical methods for categorical data. SAS User Group International Conference Proceedings, 17, 190–200. http://www.math.yorku.ca/SCS/sugi/sugi17-paper.html
Friendly, M. (1992b) Mosaic displays for loglinear models. Proceedings of the Statistical Graphics Section, American Statistical Association, pp. 61–68. http://www.math.yorku.ca/SCS/Papers/asa92.html
Friendly, M. (2000) Visualizing Categorical Data. SAS Institute, ISBN 1-58025-660-0.
See Also
chisq.test, loglin, mosaicplot
Examples
require(graphics) ## Full mosaic mosaicplot(HairEyeColor) ## Aggregate over sex (as in Snee's original data) x <- apply(HairEyeColor, c(1, 2), sum) x mosaicplot(x, main = "Relation between hair and eye color")
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