R Dataset / Package HistData / GaltonFamilies
| Attachment | Size |
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| dataset-71755.csv | 31.71 KB |
| Documentation |
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On this Picostat.com statistics page, you will find information about the GaltonFamilies data set which pertains to Galton's data on the heights of parents and their children, by child. The GaltonFamilies data set is found in the HistData R package. Try to load the GaltonFamilies data set in R by issuing the following command at the console data("GaltonFamilies"). This may load the data into a variable called GaltonFamilies. If R says the GaltonFamilies data set is not found, you can try installing the package by issuing this command install.packages("HistData") and then attempt to reload the data with library("HistData") followed by data("GaltonFamilies"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing GaltonFamilies at the command-line which should display the entire dataset. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the GaltonFamilies R data set. The size of this file is about 32,469 bytes. Galton's data on the heights of parents and their children, by childDescriptionThis data set lists the individual observations for 934 children in 205 families on which Galton (1886) based his cross-tabulation. In addition to the question of the relation between heights of parents and their offspring, for which this data is mainly famous, Galton had another purpose which the data in this form allows to address: Does marriage selection indicate a relationship between the heights of husbands and wives, a topic he called assortative mating? Keen [p. 297-298](2010) provides a brief discussion of this topic. Usagedata(GaltonFamilies) FormatA data frame with 934 observations on the following 8 variables.
DetailsGalton's notebook lists 963 children in 205 families ranging from 1-15 adult children children. Of these, 29 had non-numeric heights recorded and are not included here. Families are largely listed in decending order of fathers and mothers height. SourceGalton's notebook, http://www.medicine.mcgill.ca/epidemiology/hanley/galton/notebook/, transcribed by Beverley Shipley in 2001. ReferencesGalton, F. (1886). Regression Towards Mediocrity in Hereditary Stature Journal of the Anthropological Institute, 15, 246-263 Hanley, J. A. (2004). "Transmuting" Women into Men: Galton's Family Data on Human Stature. The American Statistician, 58, 237-243. See: http://www.medicine.mcgill.ca/epidemiology/hanley/galton/ for source materials. Keen, K. J. (2010). Graphics for Statistics and Data Analysis with R, Boca Raton: CRC Press, http://www.unbc.ca/keen/graphics-for-statistics-and-data-analysis-with-r. See Also
Examples
data(GaltonFamilies)
str(GaltonFamilies)## reproduce Fig 2 in Hanley (2004)
library(car)
scatterplot(childHeight ~ midparentHeight | gender, data=GaltonFamilies,
ellipse=TRUE, levels=0.68, legend.coords=list(x=64, y=78))# multiply daughters' heights by 1.08
GF1 <- within(GaltonFamilies,
{childHeight <- ifelse (gender=="female", 1.08*childHeight, childHeight)} )
scatterplot(childHeight ~ midparentHeight | gender, data=GF1,
ellipse=TRUE, levels=0.68, legend.coords=list(x=64, y=78))# add 5.2 to daughters' heights
GF2 <- within(GaltonFamilies,
{childHeight <- ifelse (gender=="female", childHeight+5.2, childHeight)} )
scatterplot(childHeight ~ midparentHeight | gender, data=GF2,
ellipse=TRUE, levels=0.68, legend.coords=list(x=64, y=78))#########################################
# relationship between heights of parents
#########################################Parents <- subset(GaltonFamilies, !duplicated(GaltonFamilies$family))with(Parents, {
sunflowerplot(mother, father, rotate=TRUE, pch=16,
xlab="Mother height", ylab="Father height")
dataEllipse(mother, father, add=TRUE, plot.points=FALSE,
center.pch=NULL, levels=0.68)
abline(lm(father ~ mother), col="red", lwd=2)
}
)
-- Dataset imported from https://www.r-project.org. |
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| R Output | Date |
|---|---|
| Picostat Output - Simple Linear Regression | Feb 8, 2022 |
| Picostat Output - Simple Linear Regression | Feb 8, 2022 |
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