liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The Continued Prevalence of Dichotomous Inferences at CHI
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
INRIA, France.
2019 (English)In: CHI EA 19 EXTENDED ABSTRACTS: EXTENDED ABSTRACTS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, ASSOC COMPUTING MACHINERY , 2019Conference paper, Published paper (Refereed)
Abstract [en]

Dichotomous inference is the classification of statistical evidence as either sufficient or insufficient. It is most commonly done through null hypothesis significance testing (NHST). Although predominant, dichotomous inferences have proven to cause countless problems. Thus, an increasing number of methodologists have been urging researchers to recognize the continuous nature of statistical evidence and to ban dichotomous inferences. We wanted to see whether they have had any influence on CHI. Our analysis of CHI proceedings from the past nine years suggests that they have not.

Place, publisher, year, edition, pages
ASSOC COMPUTING MACHINERY , 2019.
Keywords [en]
Dichotomous inferences; NHST; p-values; confidence intervals; dichotomous thinking; statistics
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-160451DOI: 10.1145/3290607.3310432ISI: 000482042100014ISBN: 978-1-4503-5971-9 (electronic)OAI: oai:DiVA.org:liu-160451DiVA, id: diva2:1353414
Conference
CHI Conference on Human Factors in Computing Systems (CHI)
Available from: 2019-09-23 Created: 2019-09-23 Last updated: 2019-09-23

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Besancon, Lonni
By organisation
Media and Information TechnologyFaculty of Science & Engineering
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 32 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf