# HairEyeColor

0th

Percentile

##### Hair and Eye Color of Statistics Students

Distribution of hair and eye color and sex in 592 statistics students.

Keywords
datasets
##### Usage
HairEyeColor
##### 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.

##### 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 No

##### 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.\ifelse{latex}{\out{~}}{ } 61--68. http://www.math.yorku.ca/SCS/Papers/asa92.html

Friendly, M. (2000) Visualizing Categorical Data. SAS Institute, ISBN 1-58025-660-0.

chisq.test, loglin, mosaicplot
library(datasets) 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")