Galton {HistData} | R Documentation |
Galton (1886) presented these data in a table, showing a cross-tabulation of 928 adult children born to 205 fathers and mothers, by their height and their mid-parent's height. He visually smoothed the bivariate frequency distribution and showed that the contours formed concentric and similar ellipses, thus setting the stage for correlation, regression and the bivariate normal distribution.
data(Galton)
A data frame with 928 observations on the following 2 variables.
parent
child
The data are recorded in class intervals of witdth 1.0 in. He used non-integer values for the center of each class interval because of the strong bias toward integral inches. All of the heights of female children were multiplied by 1.08 before tablulation to compensate for sex differences.
Galton, F. (1886). Regression Towards Mediocrity in Hereditary Stature Journal of the Anthropological Institute, 15, 246-263
Friendly, M. & Denis, D. (2005). The early origins and development of the scatterplot. Journal of the History of the Behavioral Sciences, 41, 103-130.
Galton, F. (1869). Hereditary Genius: An Inquiry into its Laws and Consequences. London: Macmillan.
Stigler, S. M. (1986). The History of Statistics: The Measurement of Uncertainty before 1900. Cambridge, MA: Harvard University Press, Table 8.1
Wachsmuth, A. W., Wilkinson L., Dallal G. E. (2003). Galton's bend: A previously undiscovered nonlinearity in Galton's family stature regression data. The American Statistician, 57, 190-1922. http://www.cs.uic.edu/~wilkinson/Publications/galton.pdf
data(Galton) # sunflower plot with regression line and data ellipses with(Galton, { sunflowerplot(parent,child, xlim=c(62,74), ylim=c(62,74)) reg <- lm(child ~ parent) abline(reg) if(require(car)) { data.ellipse(parent,child, xlim=c(62,74), ylim=c(62,74), plot.points=FALSE) } })