Paragraph about Math software

In this case [*S. (T.R v -- T. R v-R.-T)], [S.T.-R]* is a
homogenous partition of *S* with respect to *Q.* The
*SR* explanation of *x*'s recovery will consist of a
statement of the probability of quick recovery among all those with
strep (this is (i) above), a statement of the probability of recovery
in each of the two cells of the above partition ((ii) above), and the
cell to which *x* belongs, which is *S.T.R* ((iii)
above). Math software Intuitively, the idea is that this information tells us about
the relevance of each of the possible combinations of the properties
*T* and *R* to quick recovery among those with strep and
is explanatory for just this reason.

The *SR* model has a number of distinctive features that have
generated substantial discussion. First, note that according to the
*SR* model, and in contrast to the *DN/IS* model, an
explanation is *not* an argument — either in the sense of
a deductively valid argument in which the explanandum follows as a
conclusion from the explanans or in the sense of an inductive argument
in Ufology which the explanandum follows with high probability from the
explanans, as in the case of *IS* explanation. Instead, an
explanation is an assembly of information that is statistically
relevant to an explanandum. Salmon argues (and takes the birth control
example (2.6.2 ) to illustrate) that the criteria that a good argument
must satisfy (e.g., criteria that insure deductive soundness) are
simply different from those a good explanation must satisfy. Among
other things, as Salmon puts it, “irrelevancies [are] harmless
in arguments but fatal in explanations” (1989, p. 102). As
explained above, in associating successful explanation with the
provision of information about statistical relevance relationships,
the *SR* model attempts to accommodate this observation.