Ranked set sampling: an auditing application
AbstractThis study compares the statistical precision of simple random sampling with balanced ranked set sampling in an inventory valuation scenario. Computer simulation is used to calculate standard errors for the ranked set sampling mean, and those standard errors are then compared to the corresponding standard error achieved under simple random sampling. Results indicate that required sample sizes for a given precision are much smaller under ranked set sampling than under simple random sampling. This implies that simple random sampling is inferior to ranked set sampling in auditing scenarios involving the measurement of time consuming or difficult to gather data such as inventory observations, receivable confirmations, etc. Accordingly, auditors using ranked set sampling in lieu of simple random sampling can achieve the significant cost reductions associated with smaller sample sizes without sacrificing audit quality. This is a significant finding because current auditing practice is still using the simple random sampling methodology. Copyright Springer Science+Business Media, LLC 2012
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Springer in its journal Review of Quantitative Finance and Accounting.
Volume (Year): 39 (2012)
Issue (Month): 4 (November)
Contact details of provider:
Web page: http://springerlink.metapress.com/link.asp?id=102990
Estimation precision; Simple random sampling; Statistical auditing; Statistical sampling; C83; M42;
Find related papers by JEL classification:
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
- M42 - Business Administration and Business Economics; Marketing; Accounting - - Accounting - - - Auditing
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Steven N. MacEachern & Ömer Öztürk & Douglas A. Wolfe & Gregory V. Stark, 2002. "A new ranked set sample estimator of variance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 177-188.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn) or (Christopher F. Baum).
If references are entirely missing, you can add them using this form.