Improved Margin of Error Estimates for Proportions in Business: An Educational Example

Autor/inn/en	Arzumanyan, George; Halcoussis, Dennis; Phillips, G. Michael
Titel	Improved Margin of Error Estimates for Proportions in Business: An Educational Example
Quelle	In: American Journal of Business Education, 8 (2015) 3, S.185-192 (8 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1942-2504
Schlagwörter	Business Administration Education; Error of Measurement; Error Patterns; Intervals; Confidence Testing; Computation; Focus Groups; Benchmarking; Sampling; Equations (Mathematics); Measurement Techniques; Mathematical Concepts; Higher Education; Teaching Methods + Suchen Sie Ihr Suchwort? Messfehler; Fehlertyp; Equations; Mathematics; Gleichungslehre; Messtechnik; Hochschulbildung; Hochschulsystem; Hochschulwesen; Teaching method; Lehrmethode; Unterrichtsmethode
Abstract	This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small sample situations. The proposed method may have particular applications to focus group analysis, industry benchmarking, and destructive testing sampling. The paper discusses a computational strategy and several comparison examples. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01