Burt (1950) Data on Hair, Eyes, Head and Stature

Cyril Burt (1950) gave these data, on a sample of 100 people from Liverpool, to illustrate the application of a method of factor analysis (later called multiple correspondence analysis) applied to categorical data.

He presented these data initially in the form that has come to be called a "Burt table", giving the univariate and bivariate frequencies for an n-way frequency table.

Usage

data("Burt")

Format

A frequency data frame (representing a 3 x 3 x 2 x 2 frequency table) with 36 cells on the following 5 variables.

Hair: hair color, a factor with levels Fair Red Dark
Eyes: eye color, a factor with levels Light Mixed Dark
Head: head shape, a factor with levels Narrow Wide
Stature: height, a factor with levels Tall Short
Freq: a numeric vector

Details

Burt says: "In all, 217 individuals were examined, about two-thirds of them males. But, partly to simplify the calculations and partly because the later observations were rather more trustworthy, I shall here restrict my analysis to the data obtained from the last hundred males in the series."

Head and Stature reflect a binary coding where people are classified according to whether they are below or above the average for the population.

Source

Burt, C. (1950). The factorial analysis of qualitative data, British Journal of Statistical Psychology, 3(3), 166-185. Table IX.

Examples

data(Burt)
mosaic(Freq ~ Hair + Eyes + Head + Stature, data=Burt, shade=TRUE)
#> Error in eval(predvars, data, env): object 'Hair' not found

#or
burt.tab <- xtabs(Freq ~ Hair + Eyes + Head + Stature, data=Burt)
#> Error in eval(predvars, data, env): object 'Freq' not found
mosaic(burt.tab, shade=TRUE)
#> Error: object 'burt.tab' not found