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Against statistical significance testing in corpus linguistics

Alexander Koplenig
  • Corresponding author
  • Department of Lexik, Institute for the German language (IDS), Mannheim, Germany
  • Email:
Published Online: 2017-06-03 | DOI: https://doi.org/10.1515/cllt-2016-0036

Abstract

In the first volume of Corpus Linguistics and Linguistic Theory, Gries (2005. Null-hypothesis significance testing of word frequencies: A follow-up on Kilgarriff. Corpus Linguistics and Linguistic Theory 1(2). doi:10.1515/cllt.2005.1.2.277. http://www.degruyter.com/view/j/cllt.2005.1.issue-2/cllt.2005.1.2.277/cllt.2005.1.2.277.xml: 285) asked whether corpus linguists should abandon null-hypothesis significance testing. In this paper, I want to revive this discussion by defending the argument that the assumptions that allow inferences about a given population – in this case about the studied languages – based on results observed in a sample – in this case a collection of naturally occurring language data – are not fulfilled. As a consequence, corpus linguists should indeed abandon null-hypothesis significance testing.

Keywords: corpus linguistic methodology; statistical significance; quantitative approaches; representativeness; null-hypothesis testing

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Published Online: 2017-06-03



Citation Information: Corpus Linguistics and Linguistic Theory, ISSN (Online) 1613-7035, ISSN (Print) 1613-7027, DOI: https://doi.org/10.1515/cllt-2016-0036. Export Citation

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