Moving Transparent Statistics Forward at CHI - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Documents Associated With Scientific Events Year : 2017

Moving Transparent Statistics Forward at CHI

Matthew Kay
  • Function : Author
  • PersonId : 994704
Steve Haroz
Shion Guha
  • Function : Author
  • PersonId : 994705
Pierre Dragicevic

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.
Fichier principal
Vignette du fichier
chi2017_workshop_proposal-transparent-statistics.pdf (167.01 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01656942 , version 1 (06-12-2017)

Licence

Identifiers

Cite

Matthew Kay, Steve Haroz, Shion Guha, Pierre Dragicevic, Chat Wacharamanotham. Moving Transparent Statistics Forward at CHI. CHI 2017 - ACM Conference on Human Factors in Computing Systems, May 2017, Denver, Colorado, United States. ACM, Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp.534-541, ⟨10.1145/3027063.3027084⟩. ⟨hal-01656942⟩
204 View
273 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More