The integration of fuzzy sets and statistics: toward strict falsification in the social sciences

Ben Heylen () and Mike Nachtegael

Quality & Quantity: International Journal of Methodology, 2013, vol. 47, issue 6, 3185-3200

Abstract: Whilst statistics take up a prominent place in the social science research toolkit, some old problems that have been associated there with have not been fully resolved. These problems include bias through the inclusion of irrelevant variation and the exclusion of relevant variation, which may lead to hidden and spurious correlations in more extreme—however not at all unthinkable—cases. These issues have been addressed by Ragin by building a case for the usage of fuzzy set theory in social science. In this paper, we take a complementary view, insofar as we incorporate fuzzy set theory in current statistical analyses. Apart from shedding new light on the main issues associated with (population based) statistics, this approach also offers interesting prospects for the falsification of theories—rather than single relations between variables—in the social sciences. Copyright Springer Science+Business Media B.V. 2013

Keywords: Statistical modeling; Fuzzy logic; Configurations; Falsification (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s11135-012-9711-6

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