R Dataset / Package psych / galton
On this Picostat.com statistics page, you will find information about the galton data set which pertains to Galton's Mid parent child height data. The galton data set is found in the psych R package. Try to load the galton data set in R by issuing the following command at the console data("galton"). This may load the data into a variable called galton. If R says the galton data set is not found, you can try installing the package by issuing this command install.packages("psych") and then attempt to reload the data with library("psych") followed by data("galton"). 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 galton 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 galton R data set. The size of this file is about 9,261 bytes.
Galton's Mid parent child height data
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.
A data frame with 928 observations on the following 2 variables.
Female heights were adjusted by 1.08 to compensate for sex differences. (This was done in the original data set)
This is just the galton data set from UsingR, slightly rearranged.
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.
The other Galton data sets:
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")
Dataset imported from https://www.r-project.org.
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