"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