Show simple item record

dc.contributor.authorHubbard, Raymond
dc.contributor.authorArmstrong, J. Scott
dc.date.accessioned2006-09-15T19:29:30Z
dc.date.available2006-09-15T19:29:30Z
dc.date.issued2006-09-15T19:29:30Z
dc.identifier.citationJournal of Marketing Education, Volume 28, no. 2, 2006, Pages 114-120
dc.identifier.issn0273-4753
dc.identifier.otherDOI: 10.1177/0273475306288399
dc.identifier.urihttp://hdl.handle.net/2092/413
dc.descriptionRaymond Hubbard is the Thomas M. Sheehan Distinguished Professor of Marketing in the College of Business and Public Administration at Drake University. He can be contacted at: raymond.hubbard@drake.eduen
dc.description.abstractIn marketing journals and market research textbooks, two concepts of statistical significance - p values and α levels - are commonly mixed together. This is unfortunate because they each have completely different interpretations. The upshot is that many investigators are confused over the meaning of statistical significance. We explain how this confusion has arisen and make several suggestions to teachers and researchers about how to overcome it. © 2006 Sage Publications.en
dc.format.extent158208 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherSage
dc.subjectα levelsen
dc.subject(Overlapping) confidence intervalen
dc.subjectFisheren
dc.subjectNeyman-Pearsonen
dc.subjectp < α criterionen
dc.subjectp valuesen
dc.subjectStatisticsen
dc.subjectMathematical statisticsen
dc.subjectProbabilitiesen
dc.subjectCorrelation (Statistics)en
dc.subjectStatistical hypothesis testingen
dc.title"Why we don't really know what statistical significance means: Implications for educators"en
dc.typeArticleen


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Marketing [4]
    Publications submitted by the faculty members of the Department of Marketing.

Show simple item record