How to Fool Yourself—And Others—With Statistics | William M. Briggs http://wmbriggs.com/blog/?p=2179 --- The use of statistical analysis to draw conclusions from seemingly confused data is one of my biggest concerns about the studies we read and (try to) believe. I really wonder how valid much of the statistical analysis used to arrive at conclusions we use for bee management actually was. I seldom see the details and often the statistical work is mentioned with a quick phrase that sounds authoritative, but does not tell us the details. We often base economically important decisions on the results of studies, (although actual commercial beekeepers who live or go broke by the results of their beekeeping tend to be highly skeptical about what they read, and often, it seems, consider beekeeper coffee clatche scuttlebutt more trustworthy). Personally, I have had a problem reconciling my real world experience with what I would have expected from some studies I have read. Often we don't see the data or how the data was selected, then filtered, or the distributions and assumptions used. Often we don't know whether the researchers actually understood the requirements for proper use of the tools and did the job themselves, or just farmed out the job to an expert who did not actually understand the intricacies of bee biology and behaviour or how the data was collected and possibly previously filtered and/or selected. I also wonder how qualified reviewers are to critique the statistical aspect of studies they read -- or if they are given sufficient data to do so. *********************************************** The BEE-L mailing list is powered by L-Soft's renowned LISTSERV(R) list management software. For more information, go to: http://www.lsoft.com/LISTSERV-powered.html Guidelines for posting to BEE-L can be found at: http://honeybeeworld.com/bee-l/guidelines.htm