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In order to demonstrate why it is important to correctly account for the(serial dependent) structure of temporal data, we document an apparentlyspectacular relationship between population size and lexical diversity: forfive out of seven investigated languages, there is a strong relationshipbetween population size and lexical diversity of the primary language in thiscountry. We show that this relationship is the result of a misspecified modelthat does not consider the temporal aspect of the data by presenting a similarbut nonsensical relationship between the global annual mean sea level andlexical diversity. Given the fact that in the recent past, several studies werepublished that present surprising links between different economic, cultural,political and (socio-)demographical variables on the one hand and cultural orlinguistic characteristics on the other hand, but seem to suffer from exactlythis problem, we explain the cause of the misspecification and show that it hasprofound consequences. We demonstrate how simple transformation of the timeseries can often solve problems of this type and argue that the evaluation ofthe plausibility of a relationship is important in this context. We hope thatour paper will help both researchers and reviewers to understand why it isimportant to use special models for the analysis of data with a naturaltemporal ordering.

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Population size predicts lexical diversity, but so does the mean sea  level - why it is important to correctly account for the structure of  temporal data