Learn R Programming

psychTools (version 2.4.3)

cubits: Galton's example of the relationship between height and 'cubit' or forearm length

Description

Francis Galton introduced the 'co-relation' in 1888 with a paper discussing how to measure the relationship between two variables. His primary example was the relationship between height and forearm length. The data table (cubits) is taken from Galton (1888). Unfortunately, there seem to be some errors in the original data table in that the marginal totals do not match the table.

The data frame, heights, is converted from this table.

Usage

data(cubits)

Arguments

Format

A data frame with 9 observations on the following 8 variables.

16.5

Cubit length < 16.5

16.75

16.5 <= Cubit length < 17.0

17.25

17.0 <= Cubit length < 17.5

17.75

17.5 <= Cubit length < 18.0

18.25

18.0 <= Cubit length < 18.5

18.75

18.5 <= Cubit length < 19.0

19.25

19.0 <= Cubit length < 19.5

19.75

19.5 <= Cubit length

Details

Sir Francis Galton (1888) published the first demonstration of the correlation coefficient. The regression (or reversion to mediocrity) of the height to the length of the left forearm (a cubit) was found to .8. There seem to be some errors in the table as published in that the row sums do not agree with the actual row sums. These data are used to create a matrix using table2matrix for demonstrations of analysis and displays of the data.

References

Galton, Francis (1888) Co-relations and their measurement. Proceedings of the Royal Society. London Series,45,135-145,

See Also

table2matrix, table2df, ellipses, heights, peas,galton

Examples

Run this code
data(cubits)
cubits
heights <- psych::table2df(cubits,labs = c("height","cubit"))
psych::ellipses(heights,n=1,main="Galton's co-relation data set")
psych::ellipses(jitter(heights$height,3),jitter(heights$cubit,3),pch=".",
     main="Galton's co-relation data set",xlab="height",
     ylab="Forearm (cubit)") #add in some noise to see the points
psych::pairs.panels(heights,jiggle=TRUE,main="Galton's cubits data set")

Run the code above in your browser using DataLab