| swiss {datasets} | R Documentation |
Swiss Fertility and Socioeconomic Indicators (1888) Data
Description
Standardized fertility measure and socioeconomic indicators for each of 47 French-speaking provinces of Switzerland at about 1888.
Usage
swissFormat
A data frame with 47 observations on 6 variables, each of which
is in percent, i.e., in [0, 100].
| [,1] | Fertility | I_g,
‘common standardized fertility measure’ |
| [,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.
Details
(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 [0, 1].
Note
Files for all 182 districts in 1888 and other years have been available at https://oprdata.princeton.edu/archive/pefp/switz.aspx.
They state that variables Examination and Education
are averages for 1887, 1888 and 1889.
Source
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 Unpublished data assembled under NICHD contract number No 1-HD-O-2077.”
References
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
Examples
require(stats); require(graphics)
pairs(swiss, panel = panel.smooth, main = "swiss data",
col = 3 + (swiss$Catholic > 50))
summary(lm(Fertility ~ . , data = swiss))