Standardized fertility measure and socio-economic indicators for each of 47 French-speaking provinces of Switzerland at about 1888.
A data frame with 47 observations on 6 variables, each of which
is in percent, i.e., in
|[,2]||Agriculture||% of males involved in agriculture as occupation|
|[,3]||Examination||% draftees receiving highest mark on army examination|
|[,4]||Education||% education beyond primary school for draftees.|
|[,5]||Catholic||% ‘catholic’ (as opposed to ‘protestant’).|
|[,6]||Infant.Mortality||live births who live less than 1 year.|
All variables but ‘Fertility’ give proportions of the population.
(paraphrasing Mosteller and Tukey):
Switzerland, in 1888, was entering a period known as the demographic transition; i.e., its fertility was beginning to fall from the high level typical of underdeveloped countries.
The data collected are for 47 French-speaking “provinces” at about 1888.
Here, all variables are scaled to
[0, 100], where in the
original, all but
"Catholic" were scaled to
Files for all 182 districts in 1888 and other years have been available at https://opr.princeton.edu/archive/pefp/switz.aspx.
They state that variables
are averages for 1887, 1888 and 1889.
Project “16P5”, pages 549–551 in
Mosteller, F. and Tukey, J. W. (1977) Data Analysis and Regression: A Second Course in Statistics. Addison-Wesley, Reading Mass.
indicating their source as “Data used by permission of Franice van de Walle. Office of Population Research, Princeton University, 1976. Unpublished data assembled under NICHD contract number No 1-HD-O-2077.”
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
require(stats); require(graphics) pairs(swiss, panel = panel.smooth, main = "swiss data", col = 3 + (swiss$Catholic > 50)) summary(lm(Fertility ~ . , data = swiss))