Institute for Language Sciences Labs

Statistics

In the field of Humanities, experimental research is becoming more and more common. Doing experimental research and analyzing data requires at least a basic knowledge of quantitative methodology and statistics.

Statistical consultation – who is it for?

Kirsten Schutter is the go-to statistics adviser for researchers affiliated with the faculty of Humanities. She can guide you through the many different possibilities and resources, advise you on research design, and on which methods and statistical analyses to use..

If you are a BA, MA or RMA student in need of statistical advice, your supervisor is your first helpline. If more insight is required, you are welcome to schedule a consult together with your supervisor(s).

We advise that you consult the adviser in an early stage of your research project. You are very welcome to plan a brainstorm session to discuss the methodological strengths and weaknesses of your ideas. The better your research design, the greater the use you can make of statistical analysis.

How does statistical consultation work?

What to expect when you make an appointment with our statistics adviser

First, we assess what stage your research is in, and what level your methodological and statistical skill you have. Then, an overview of your research is established, focusing on methodology and use of statistics:

  • Methodology: What does your research design look like? This includes your research question, hypotheses/predictions, research population, variables of interest, operationalization of variables.
  • Statistics: What type of analysis do you need in order to answer your research question(s)? If you have already collected data: Is your data appropriate for answering your research question and the desired statistical analysis?

You can expect the statistics adviser to help you to:

  • Optimize your research question.
  • Create a study design that is optimal for answering your research question.
  • Decide on the appropriate statistical analysis.
  • Decide what statistical software to use (e.g., JASP or R).
  • Interpret the results of statistical analyses.
  • Find relevant literature and/or (online) courses on methodology/statistics.

The following basics are implied when you apply for a consult:

  • You should have some basic statistical knowledge to build on. Some references to get you started can be found below.
  • You have matched your research questions to your statistical skill. The statistics adviser can look through your questions with you to check that you have adequate knowledge to deal with them.

Disclaimer:

The statistics adviser provides help, coaching, and advice. She does not provide finished statistical analyses.

You as a researcher bear full responsibility for your study, including any methodological and statistical aspect of it. Familiarize yourself with the methodological and statistical topics concerning your study. The adviser can provide references but will not write you a map and will not provide you with complicated methods that go beyond your own knowledge.

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Some references to get you started:

Books on quantitative research methods:

  • A book on experimental methods (in Language acquisition research):
    Blom, E., & Unsworth, S. (Eds.). (2010). Experimental methods in language acquisition research. Amsterdam/Philadelphia: John Benjamins Publishing.
  • Field, A., & Hole, G. (2002). How to design and report experiments. London: Sage.
  • Litosseliti, L. (2018). Research methods in linguistics (Second edition). Bloomsbury Academic, Bloomsbury Publishing Plc.

Books on statistics:

  • Baayen, R. H. (2008). Analyzing linguistic data: A practical introduction to statistics using R. Cambridge university press.
  • Field, A.P., Miles, J. & Field, Z. (2012). Discovering statistics using R. London: Sage.
  • Quené, H. & Van den Bergh, H. (2021). Quantitative Methods and Statistics. Open textbook, available at https://hugoquene.github.io/QMS-EN, 290+ pp. [Multiple formats, source code, and supplementary materials are available at doi:10.5281/zenodo.4479620]
  • Weinberg, S. L., Harel, D., & Abramowitz, S. K. (2023). Statistics Using R: An Integrative Approach (2nd ed.). Cambridge: Cambridge University Press.
  • Winter, B. (2019). Statistics for linguists: An introduction using R. Routledge.

Online resources (tutorials/courses/software etc.):

  • Tutorials from Bodo Winter.
  • Free Coursera course in quantitative methods.
  • Open source statistical software: JASP
  • Handy website ‘Choosing the correct statistical test in SAS, Strata, SPSS and R’
  • A free online Multilevel modelling course from Bristol University.
  • An introduction to the theory of mixed models.
  • Quené, H. (2021). Quantitative Research Cheat Sheet. [doi:10.13140/RG.2.2.11392.15365].

Articles about some important concepts in statistics:

  • Anderson et al. (2017). Sample-Size Planning for More Accurate Statistical Power: A Method Adjusting Sample Effect Size for Publication Bias And Uncertainty. Psychological Science, 28, 1547-1562.
  • Cohen, J. (1992). Things I have learned (so far). In Annual Convention of the American Psychological Association, 98th, Aug, 1990, Boston, MA, US; Presented at the aforementioned conference.. American Psychological Association.
  • Cumming, G. (2008). Replication and p intervals: p values predict the future only vaguely, but confidence intervals do much better. Perspectives on psychological science, 3(4), 286-300.
  • Lenth, R. V. (2001). Some Practical Guidelines for Effective Sample Size Determination. The American Statistician, 55, 187-193