Cause and effect

["vu" <vu@as.nida.ac.th>]

There's recently a very interesting article on the philosophical
foundations of statistics that may be of interest to  statisticians, or
economists or social scientists who extensively use statistical methods in
their everyday professional life. The author is Professor Judea Pearl, one
of the founding fathers of Bayesian network technology that has recently
had revolutionary impacts on modern expert systems and, in general,
artificial intelligence. Below is the abstract of the paper.

Title: The New Challenge: From a Century of Statistics to an Age of
Causation.
Author: J. Pearl, Professor of Computer Science, UCLA.

Abstract:

	Some of the main users of statistical methods - economists, 
	social scientists, and epidemiologists - are discovering that 
	their fields rest not on statistical but on causal foundations. 
	The blurring of these foundations over the years follows from  
	the lack of mathematical notion capable of distinguishing 
	causal from equational relationships. By providing formal 
	and natural explications of such relations, graphical methods 
	have the potential to revolutionize how statistics is used in 
	knowledge-rich applications. Statisticians, in response, are 
	beginning to realize that causality is not a metaphysical 
	deadend but a meaningful concept with clear mathematical
	underpinning. This paper survey these developements and 
	outline future challenges. 


For those who are interested, the article can be retrieved at

	http://singapore.cs.ucla.edu/jp_home.html 

Cheers,
--  Vu~