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11 - A Robust t-Test

from Part II - How to Use Statistics

Published online by Cambridge University Press:  26 January 2019

Paul Cairns
Paul Cairns
Affiliation:
University of York
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Summary

The t-test is a work horse of a lot of statistical analysis in HCI. There are a lot of myths about how robust it is to deviations from normality and other assumptions. However, when faced with practical data, particularly those coming from usability studies, the claims of robustness do not stand up. This chapter reevaluates the t-test as a test for an effect on the location of data. This leads to considering robust measures of location, such as trimmed or Winsorized means and associated Yuen–Welch test as a robust alternative to the traditional t-test.

Keywords

t-testrobustnessassumptionsnormalityhomogeneity of variancehomoscedasticitytrimmed meanWinsorizationYuen–Welch test
Type
Chapter
Information
Doing Better Statistics in Human-Computer Interaction , pp. 125 - 138
Publisher: Cambridge University Press
Print publication year: 2019

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  • A Robust t-Test
  • Paul Cairns, University of York
  • Book: Doing Better Statistics in Human-Computer Interaction
  • Online publication: 26 January 2019
  • Chapter DOI: https://doi.org/10.1017/9781108685139.012
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  • A Robust t-Test
  • Paul Cairns, University of York
  • Book: Doing Better Statistics in Human-Computer Interaction
  • Online publication: 26 January 2019
  • Chapter DOI: https://doi.org/10.1017/9781108685139.012
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • A Robust t-Test
  • Paul Cairns, University of York
  • Book: Doing Better Statistics in Human-Computer Interaction
  • Online publication: 26 January 2019
  • Chapter DOI: https://doi.org/10.1017/9781108685139.012
Available formats
×