Revisiting the assumptions for inferential statistical analyses: A conceptual guide

Ang Chen, Weirno Zhu

Research output: Contribution to journalArticlepeer-review


Trustworthiness of results from statistical analyses relies on the fulfillment of a set of assumptions made about data. Asurvey of published pedagogy studies in physical education revealed that examining the assumptions has heen overlooked in data analyses and result reporting. The purpose of this article is to provide a conceprual understanding of the assumptions and to summarize available methods to test and address their violations. In the article, we present information to show that it is in appropriate to overlook the assumptions and ignore their violation's impact on interpretation of results. We summarize current findings from theoretical statistical research that start to challenge the conventional belief about the robustness of traditional inferential statistical analyses. Remedial procedures recommended in the latest statistical theories are presented for researchers to adopt in order to gencrate valid results from statistical analyses.

Original languageEnglish (US)
Pages (from-to)418-439
Number of pages22
Issue number4
StatePublished - Nov 2001

ASJC Scopus subject areas

  • Education


Dive into the research topics of 'Revisiting the assumptions for inferential statistical analyses: A conceptual guide'. Together they form a unique fingerprint.

Cite this