The use of statistics has long been important in the human sciences. An early example is an analysis by William Sealy Gosset (alias “Student”) of biometric data obtained by Scotland Yard around 1900. The heights of 3,000 male criminals fit a bell curve almost perfectly:
Histogram © A. H. Dekker, produced using R software
Standard statistical methods allow the identification of correlations, which mark possible causal links:
Argylesock says: It's been too long since I wrote about numbers here. It may be some more time before I do it again, partly because when not blogging I'm analysing data in R (among other things, obviously.) Meanwhile here's what Igor at Human Sciences Explored has said about R.
The geospatial features of R probably make it really useful for agricultural applications too, I guess.
Yes. I’d like somebody to let me loose on a dataset on which I’d learn and use ArcGIS. How about you, do you do geospatial analysis?