StatisticalThinking

=Statistical thinking, the basic idea=

Understand the simple chain of thinking below, then enlist or hire a statistician who will use the appropriate "recipe" for the data at hand.

1.	There is a __population__ of individuals. (Population = individuals subject to the same causes of interest. There may also be background, non-manipulatable causes that vary among these individuals.) 2.	For some __measurable attribute__ the individuals have __varying responses__ to these causes (possibly because of the background causes). 3.	You have __observations__ of the measurable attribute for 2 or more subsets ("samples") of the populations. 4.	__Central question__ of statistical analysis: Are the subsets sufficiently different in their varying responses that you __doubt__ that they are from the one population (i.e., subject to all the same foreground causes)? Statisticians answer this question with __recipes__ that are variants of the comparison between the subset averages in relation to the spread around the averages. That is, for the figure below, you are more likely to doubt that subsets A and B are from the same population in the left hand situation than in the right hand one.



5.	If you doubt that the subsets are from the same population, investigate further, drawing on other knowledge about the subsets, with a view to __exposing the causes involved__ and then taking action informed by that knowledge about the causes.