"Why we don't really know what statistical significance means: Implications for educators"

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dc.contributor.author Hubbard, Raymond
dc.contributor.author Armstrong, J. Scott
dc.date.accessioned 2006-09-15T19:29:30Z
dc.date.available 2006-09-15T19:29:30Z
dc.date.issued 2006-09-15T19:29:30Z
dc.identifier.citation Journal of Marketing Education, Volume 28, no. 2, 2006, Pages 114-120
dc.identifier.issn 0273-4753
dc.identifier.other DOI: 10.1177/0273475306288399
dc.identifier.uri http://hdl.handle.net/2092/413
dc.description Raymond 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.edu en
dc.description.abstract In 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.extent 158208 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Sage
dc.subject α levels en
dc.subject (Overlapping) confidence interval en
dc.subject Fisher en
dc.subject Neyman-Pearson en
dc.subject p < α criterion en
dc.subject p values en
dc.subject Statistics en
dc.subject Mathematical statistics en
dc.subject Probabilities en
dc.subject Correlation (Statistics) en
dc.subject Statistical hypothesis testing en
dc.title "Why we don't really know what statistical significance means: Implications for educators" en
dc.type Article en


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    Publications submitted by the faculty members of the Department of Marketing.

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