David, 

 

Along this theme, I highly recommend the book "How to Lie with Statistics". I read it when I was taking statistics in graduate school. Very useful and a fun read, even though it was written in the 50's. 

(http://www.amazon.com/How-Lie-Statistics-Darrell-Huff/dp/0393310728)

"How to Lie with Statistics is a book written by Darrell Huff in 1954 presenting an introduction to statistics for the general reader. It is a brief, breezy, illustrated volume outlining common errors, both intentional and unintentional, associated with the interpretation of statistics, and how these errors can lead to inaccurate conclusions. It has become one of the most widely read statistics books in history (even though Huff was not a statistician), with over one and a half million copies sold in the English-language edition^[1]. It has also been widely translated.

Themes of the book include "Correlation does not imply causation" and "Using Random Sampling". It also shows how statistical graphs can be used to distort reality, for example by truncating the bottom of a line or bar chart, so that differences seem larger than they are, or by representing one-dimensional quantities on a pictogram by two- or three-dimensional objects to compare their sizes, so that the reader forgets that the images don't scale the same way the quantities do."

From http://en.wikipedia.org/wiki/How_to_Lie_with_Statistics

science proper is corrupted by bias and power- bias is filtered out through peer review- this is the inherent problem with internet info- power is filtered out through democratization- this is why we need government and university science research to offset special interest influence on study direction- checking for peer review and sponsorship are the pillars we can use to surmise if the science is bad or good