My biology colleagues know a lot about statistics. They routinely perform hypothesis tests, ANOVA, and perform Box-Cox analyses to be sure that the residuals of a fit to data are normally distributed. Ask many physicists and chemists about these tools and you'll likely be met with a blank stare. It could be argued that this points to a problem in physics and chemistry education. To some extent I agree that we (physicists) are not well trained in the art of proper data analysis.
On the other hand (and based on my limited knowledge of the biological sciences), I wonder if biologists place too much emphasis on statistics. If a student's first thoughts in a data analysis are about which type of regression is valid for the data, then I fear that they may miss obvious trends that may answer that question for them.
My belief is that data analysis is best approached intuitively first and formally second. I'm also afraid that a biology curriculum that focuses on the technicalities of statistics may under-emphasize this "human aspect" of analysis. Likewise, there is a point where rigor must be included and I see many physical scientists unable to provide it.
Again, these thoughts are based on my own limited understanding of the biological sciences. There are biologists, physicists, and chemists who excel in all areas. But differences in curricula and courses may bias us towards one aspect or another when in reality good scientists are capable of both.
A "lab notebook" about my life in science, programming, and philosophy.
