Moving transparent statistics forward at CHI

Matthew Kay, Steve Haroz, Shion Guha, Pierre Dragicevic, Chat Wacharamanotham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Transparent statistics is a philosophy of statistical reporting whose purpose is scientific advancement rather than persuasion. We ran a SIG at CHI 2016 to discuss problems and limitations in statistical practices in HCI and options for moving the field towards clearer and more reliable ways of writing about experiments, and received an overwhelming response. This SIG resulted in rough drafts of reviewer guidelines, resources for authors, and other suggestions for advancing a vision of transparent statistics within the field; this year, we propose a concentrated one-day writing workshop to develop those documents into a polished state with input from a diverse cross-section of the CHI community.

Original languageEnglish (US)
Title of host publicationCHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Pages534-541
Number of pages8
ISBN (Electronic)9781450346566
DOIs
StatePublished - May 6 2017
Externally publishedYes
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: May 6 2017May 11 2017

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
VolumePart F127655

Other

Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
CountryUnited States
CityDenver
Period5/6/175/11/17

Keywords

  • Methodology
  • Quantitative methods
  • Statistics
  • Transparent statistics
  • User studies

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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