From Controversies in the Foundations of Statistics by Bradley Efron:
Statistics seems to be a difficult subject for mathematicians, perhaps because its elusive and wide-ranging character mitigates against the traditional theorem-proof method of presentation. It may come as some comfort then that statistics is also a difficult subject for statisticians.
The title is intriguing. Does it go far beyond the Bayesian vs. frequentist battles?
One of my all-time favorite TED talk : http://www.ted.com/talks/peter_donnelly_shows_how_stats_fool_juries.html
@Richard,
To me one interesting new thing in this was adding Fisher’s point of view as unhappy with both Bayesian and frequentist approaches to various problems. This was especially interesting (to me) in the section on conditional inference.
That is because statistics is better placed under the aegis of science (and taught like a science) rather than mathematics. William Gosset was a chemist trying to figure out how to brew a more consistent batch of Guinness when he came up with the t-test. To me, that says it all about where statistics truly belongs.