HairEyeColor {datasets} R Documentation

Hair and Eye Color of Statistics Students

Description

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 from 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

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. doi: 10.2307/2683520.

Friendly, M. (1992a). Graphical methods for categorical data. SAS User Group International Conference Proceedings, 17, 190–200. http://datavis.ca/papers/sugi/sugi17.pdf

Friendly, M. (1992b). Mosaic displays for loglinear models. Proceedings of the Statistical Graphics Section, American Statistical Association, pp. 61–68. http://www.datavis.ca/papers/asa92.html

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

`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")
```

[Package datasets version 4.1.0 Index]