Stats

My career in biotech has been maddening.  But it is not biotechnology that is the issue.  The issue is statistical analysis of data.  This became very clear last week when some of us sat through a course in a software product that analyzes data.  A lot of time was spent debating what a sample was versus what a population was.  We even had people arguing over the term bogus results versus "not validated".  The useful aspect of statistics was not of interest to our group.  

There was a simple illustration about a lady who could tell the difference between tea with milk added versus milk with tea added.  The design of the experiment to test this lady was rigorous.  The people testing the lady were highly skeptical about her claim.  The design of experiment however, left out the possibility of bias on either side of the question.  In the end they all agreed, the lady could tell the order in which her tea and milk were combined.

When Feynman said, "So we really ought to look into theories that don't work, and science that isn't science." he seemed to touching on the powers of statistics to analyze experimental design.  Psychics and people who speak to the dead are best exposed using statistics.  Biotechnology can also be analyzed this way.  The real trick for our future is to find ways to get Biotech and the pharmaceutical industry to allow outside groups to analyze their data and their analysis of their data.  The thought of a group of MDs locking themselves in a conference room to make a recommendation to the FDA regarding research seems absurd to me.  The Design of Experiments is the whole issue behind the Cargo Cult Scientist.