Simon Black –
This blog title is provocatively paradoxical. The assumption is that somthething measured is something proved. this is a habit of thinking which we are trained to establish in our minds as scientists.
This is not the case.
In practice, when we decide to define a fact, we then define what it is, how it is to be measured, then measure to verify.
In deciding the measurement, we simply place a judgement – our opinion of reality, onto something that isn’t there. For example:
The label on a blanket reads “50 per cent wool” What does this mean? Half wool, on the average, over this blanket, or half wool over a month’s production? What is half wool? Half by weight? If so, at what humidity? By what method of chemical analysis? How many analyses? The bottom half of the blanket is wool and the top half is something else. Is it 50 per cent wool? Does 50 per cent wool mean that there must be some wool in any random cross-section the size of a half dollar? If so, how many cuts shall be tested? How select them? What criterion must the average satisfy? And how much variation between cuts is permissible? Obviously, the meaning of 50 per cent wool can only be stated in statistical terms (Deming 1975).
Is it now becoming clear?
“Without theory (hypothesis), data are meangingless or nonexistent. There is thus no true value of anything: true value is undefinable operationally. There are, however, numerical values that people can use with confidence if they understand their meaning (for the tensile strength of a batch of wire, for example, or for the proportion of the labor force unemployed last month).” (Deming 1967).
The trick is to understand the meaning of numbers. this is clearly important if we are conudcting a population census (which individuals, where, within what boundaries, at what point in time, by what method of observation, how to record etc.) buit more so when we consider more nebulous things, like the ‘perceptions of local communities’, or ‘support for conservation action’ or the ‘involvement of local partners’.
Not everything that can be counted counts.
Not everything that counts can be counted.
So the first useful question about somethnig is:
“what do we know about this?”
Think about this next time you set a goal, or measure results…
Deming W.E. (1967) Walter A. Shewhart, 1891-1967. The American Statistician, 21(2): 39-40
Deming (1974) On probability as a basis for action. The American Statistician, 29 (4): 146-152