The present thesis explores how statistical methods are conceptualized, used, and interpreted in quantitative Hispanic sociolinguistics in light of the group of statistical methods espoused by Kline (2013) and named by Cumming (2012) as the “new statistics.” The new statistics, as a conceptual framework, repudiates null hypothesis statistical testing (NHST) and replaces it with the ESCI method, or Effect Sizes and Confidence Intervals, as well as meta-analytic thinking. In this thesis, a descriptive review of 44 studies found in three academic journals over the last decade (2005 – 2015), NHST was found to have a tight grip on most researchers. NHST, much discredited outside of linguistics, confused authors who conflated the theories of Fisher and Neyman-Pearson, who themselves battled acrimoniously until the end of their publishing lives. Within the studies reviewed, with exceptions, dichotomous thinking ruled the quantitative approach, and binary reporting ruled the results and discussions. In addition, this thesis revealed that sociolinguistics, at least within the studies reviewed, is not exactly a “statistical monoculture” as suspected by Gorman and Johnson (2013), rather ANOVAs have joined Goldvarb’s logistic regression in its dominance. As described insightfully by Plonsky (2015), these two methods are exposed as extensions of the dichotomous thinking that attaches itself to NHST. Further, little evidence was found that the methods of the new statistics were being implemented in a coordinated fashion, including far too few meta-analyses. As such, quantitative Hispanic sociolinguistics, and linguistics in general, were shown to be vulnerable to problems with reliable quantitative theory building.
- New directions in quantitative Hispanic sociolinguistics