Archive for March, 2011
As you can see from this photo taken Friday while cross-country skiing, Spring has not sprung in my neck of the woods. However, just overhead as I took this shot were several dozen robins perched in the birch. They were chattering a great deal – I imagine in complaint about which bird brain thought it was time to migrate back north.
A couple of years ago at this seasonal juncture I wrote about phenology – the study of timing for nature’s ways. For us in Minnesota the robins’ arrival is a sure sign of warmer weather around the corner.
Having just returned from a Spring break in Florida, I wondered how these southerners can detect seasonal changes. My searching on internet reveals little, other than this announcement of the first phenology workshop in Florida in 2009. The one sure sign of Spring for Floridians is the hordes of Minnesotans coming down for a break. They probably trump anything more subtle from Mother Nature.
Check out this link* to an interview by Fareed Zakaria of “gap minder” Hans Rosling. This Swedish statistician, with a focus on global health, uses dynamic bubble graphs to dramatize world developments that are closing the gap to USA’s lead in well-being.
It really is mesmerizing to see Rosling dramatize statistics via his moving graphs. See his recent hour-long BBC special “The Joy of Stats” at this GapMinder website. You will find it very entertaining and enlightening, I am sure.
“I kid you not – statistics is now the sexiest subject around.”
- Hans Rosling
Fortunately for all of us, Google bought the technology for these motion charts to make them widely available. For example, fiddle with the graph correlating life expectancy and fertility at this Google Labs’ Public Data Explorer posting.
Who would have ever thought that statistics could be so much fun!
*Thanks to Paul Sheldon, an independent consultant specializing in quality and productivity tools, who provided me the heads-up.
I found it amusing that, when forced to try modeling my weight data (see previous blog), my DOE software recommended a fifth order polynomial* model! That’s a bit more ‘tayloring’ (Ha ha – inside joke) than I really needed. In fact, just to show how silly this is (5th order!) I offer the following scenario as a cautionary tale. Perhaps it may help to dissuade others who make similarly nonsensical models from what is really just (naturally) randomly generated data.
Looking forward to a work/vacation trip to Tampa in late March (I really will be going there, I am happy to say!), let’s pretend that I use this fifth-order model to help me decide whether to bring a swimming suit. Hmmm, extrapolating out to day 75, when I finish my conference and head for the Gulf shore, the over-fitted model (really should just use the mean!) predicts that by then I will balloon to nearly 100 pounds over my norm. In this case I may easily be mistaken for a beached whale!
It’s just not right to apply model-fitting tools to what is not a DOE, but rather simply a process run-out at steady-state conditions. Extrapolation makes this even more dangerous by far. See the graph for a case in point.
*(A math-phobic person I am acquainted with, whom I will not identify, mockingly refers to these equations as “poly moles” — hence my title for this blog.)