psych (version 1.7.8)

galton: Galton's Mid parent child height data

Description

Two of the earliest examples of the correlation coefficient were Francis Galton's data sets on the relationship between mid parent and child height and the similarity of parent generation peas with child peas. This is the data set for the Galton height.

Usage

data(galton)

Arguments

Format

A data frame with 928 observations on the following 2 variables.

parent

Mid Parent heights (in inches)

child

Child Height

Details

Female heights were adjusted by 1.08 to compensate for sex differences. (This was done in the original data set)

References

Stigler, S. M. (1999). Statistics on the Table: The History of Statistical Concepts and Methods. Harvard University Press. Galton, F. (1886). Regression towards mediocrity in hereditary stature. Journal of the Anthropological Institute of Great Britain and Ireland, 15:246-263. Galton, F. (1869). Hereditary Genius: An Inquiry into its Laws and Consequences. London: Macmillan.

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, 190-192.

See Also

The other Galton data sets: heights, peas,cubits

Examples

Run this code
# NOT RUN {
data(galton)
describe(galton)
 #show the scatter plot and the lowess fit 
pairs.panels(galton,main="Galton's Parent child heights")  
#but this makes the regression lines look the same
pairs.panels(galton,lm=TRUE,main="Galton's Parent child heights") 
 #better is to scale them 
pairs.panels(galton,lm=TRUE,xlim=c(62,74),ylim=c(62,74),main="Galton's Parent child heights") 
# }

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