Abstract
Abstract
As a usage-based approach to the study language, cognitive linguistics is theoretically well poised to apply
quantitative methods to the analysis of corpus and experimental data. In this article, I review the historical circumstances that
led to the quantitative turn in cognitive linguistics and give an overview of statistical models used by cognitive linguists,
including chi-square test, Fisher test, Binomial test, t-test, ANOVA, correlation, regression, classification and regression
trees, naïve discriminative learning, cluster analysis, multi-dimensional scaling, and correspondence analysis. I stress the
essential role of introspection in the design and interpretation of linguistic studies, and assess the pros and cons of the
quantitative turn. I also make a case for open access science and appropriate archiving of linguistic data.
© John Benjamins Publishing Company
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2019-08-20
2024-03-28
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