Educational Research - the Ethics and Aesthetics of Statistics

174 P. Smeyers
6. The role of the analyst in the initial choice of method(s) and in the subsequent
development of the particular research application is highly significant in
realizing the possibility of 1–5.
7. As a consequence of 1–6, manipulations can contribute to retroduction [which
explains what conditions in reality may have or could have led to these observations]
to causal mechanisms rather than hypostatising [acting as if, or assuming
that, the relations between things are fixed] variables as chains of events through
interpolation.
8. 1–7 imply that an analytical statistical method may be appropriate as part of a
methodologically pluralist research project. (Olsen & Morgan, 2005, pp. 269–
270)
Olsen and Morgan claim that one need not believe that data represent the world
for them to be useful in constructing arguments (Olsen & Morgan, 2005, p. 277).
Moreover, it may be extremely difficult to disagree with their conclusions (Olsen &
Morgan, 2005, p. 278):
Counterfactual work in analytical statistics requires comparative statistics, and can usefully
bring out findings about minority groups vs. the majority, or different populations
which have common causal mechanisms. The class structure of different countries, and
different policy regimes which together generate different employment outcomes, illustrates
the possibilities for comparative statistics. To throw out statistics as a method would
involve discarding all possibilities for such comparative work, yet such work has been very
illuminating in many disciplines.
Sylvia Walby (who is interested in a more theoretical stance) develops a parallel
argument (2007) where the implications of complexity theory for the analysis
of multiple intersecting social inequalities are investigated and applied. Similarly
Helga Nowotny (2005) draws attention to the fact that we seem ‘to be engaged in
describing and interpreting complexities with the desire to understand and to engage
in both – in building higher-level complexities because they are a more efficient
way of doing things and to reduce complexity in order to minimize undesirable
effects and to be able to cope with the increasing levels of complexity around us’
(Nowotny, 2005, p. 19). Both, she claims, are indicative of a dynamic which points
to the ongoing co-evolutionary processes between science and society.
Evidently, there is a real danger here of committing a logical fallacy, in which one
ignores the original topic of an argument and subtly changes the subject, but still
claims that the conclusion concerning the original subject is reached even though
the argument has little to do with the conclusion. This so-called ‘red herring fallacy’
looms around the corner for statistics. It is committed when the arguer diverts the
attention of the reader or listener by addressing a number of extraneous issues and
ends by presuming that some conclusion has been established. This confuses scientific
with faith-based belief. What can we conclude from this? It seems to me that
when one does not hypostasize (by this I mean formally treat or represent something
abstract as a concrete reality) the results of statistical analyses, they have the
potential to engender better understanding. Of course, statistics may reveal what we
are interested in or point us to something that we were unaware of (for example