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Chapter 2 - Testing the Null

from Part I - Why We Use Statistics

Published online by Cambridge University Press:  26 January 2019

Paul Cairns
Affiliation:
University of York
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Summary

Traditional statistical testing, sometimes called null hypothesis significance testing (NHST), and the use of p-values has come under strong criticism. This chapter looks at the social issues of achieving significance in statistics that has led to the problems of NHST. It also discusses, though, how the framework of severe testing provides a way to understand NHST as a means of uniting experiments, statistics and evidence for research ideas. When viewed this way, NHST can still be an important approach to data analysis in HCI.

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Publisher: Cambridge University Press
Print publication year: 2019

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  • Testing the Null
  • Paul Cairns, University of York
  • Book: Doing Better Statistics in Human-Computer Interaction
  • Online publication: 26 January 2019
  • Chapter DOI: https://doi.org/10.1017/9781108685139.003
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  • Testing the Null
  • Paul Cairns, University of York
  • Book: Doing Better Statistics in Human-Computer Interaction
  • Online publication: 26 January 2019
  • Chapter DOI: https://doi.org/10.1017/9781108685139.003
Available formats
×

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.

  • Testing the Null
  • Paul Cairns, University of York
  • Book: Doing Better Statistics in Human-Computer Interaction
  • Online publication: 26 January 2019
  • Chapter DOI: https://doi.org/10.1017/9781108685139.003
Available formats
×