| Summary: | The pervasiveness of international conflict makes of it one of the main topics of discussion
among IR scholars. The discipline has extensively attempted to model the conditions and
settings under which armed conflict emerges, at sometimes resorting to formal models as tools
to generate hypotheses and predictions. In this paper, I analyse two distinct approaches to
formal modelling in IR: one that fits data into mathematical models and another that derives
statistical equations directly from a model’s assumption. In doing so, I raise the following
question: how should maths and stats be linked in order to consistently test the validity of
formal models in IR? To answer this question, I scrutinise James Fearon’s audience costs
model and Curtis Signorino’s strategic interaction game, highlighting their mathematical
assumptions and implications to testing formal models. I argue that Signorino’s approach
offer a more consistent set of epistemological and methodological tools to model testing,
for it derives statistical equations that respect a model’s assumptions, whereas the data-fit
approach tends to ignore such considerations.
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