Statistical Sampling in Auditing Defense

All important business organizations are often required by the government to perform audits annually using statistical sampling. Statistical sampling mostly allows auditors to have the authority of implementing several analytical procedures for developing an appropriate sampling plan for an organization. Moreover, the board of any organization has the obligation of ensuring that all audit samples are critically planned and evaluated. The auditor, on the other hand, should make it his or her duty to educate any taxpayer concerning the objectives of sampling processes in addition to encouraging the taxpayer to offer suggestions on designing better sampling plans (California State Board of Equalization, 2000). While working with the taxpayer to provide solutions to any given situations, an auditor should ensure that adequate tests that provide the auditor with an assurance of records accuracy are conducted. At times when an auditing process goes wrong, and a misunderstanding ensues between an auditor and taxpayer that may warrantee suing of the auditor, statistical sampling will provide him or her with a better defense. Mostly, statistical sampling estimations require sample sizes, objectives of projections and evaluation of results from statistical samples. When a sample is obtained statistically, there is always a higher possibility of stating with a given level of confidence that sample results are no further away than calculable amounts from results attainable from thoroughly examining all statistical items (California State Board of Equalization, 2000). These properties often provide sample results that are objective and defensible in that all sampling plans are randomly unstratified and all items in any given population have equal chances of being selected as sample items.  This random selection process of statistical sampling often eliminates biases of sample results and further reduces any arguments that may arise and state that samples are not representatives (Jokovich, 2013). Therefore all samples that are gotten statistically are not the only objective but also provides auditors with solid defenses when presented before a court of law. Consequently, statistical sampling provides an advance estimation of necessary sample sizes that are mostly computed by basing them on mathematical principles (Simon, 2011).  This estimation predominantly gives auditors defenses for reasonableness of sample sizes and justifications for all expenditures involved in the sampling processes (Cplusglobal, 2014). Although these sampling sizes always call for good analytical skills and decisions by the auditor, they are not purely mechanical. Moreover, statistical sampling mostly provides estimations for sampling errors, which cannot be estimated by using non-statistical samples which do not produce reliable and accurate results (California State Board of Equalization, 2000).  In cases where probability sample is used, effects are evaluated regarding how far sample projections might deviate from values that can be obtained by examining a population entirely using statistical sampling. These two methods do not provide credible defenses for auditors when presented before a court of law which thus leaves statistical sampling as the only method that can allow an auditor to come up with a good defense. Furthermore, statistical sampling has no accurate answer since they are presented in a range of values (Jokovich, 2013). This property of statistical sampling that does not give room for one figure that in "the answer" often offers auditors with opportunities to create credible defenses if they are sued.  For example, a random sample that provides evidence that a medical provider overcharged Medicare by between $5million and $7 million, one can be confident that the actual amount of overcharge lies in this range, but they cannot get their hands on the exact value as the actual amount. Therefore if an auditor is sued, they can give a defense that the results can be interpreted in many ways and that no concrete evidence can point to an actual value (Simon, 2011). Statistical samples often carry great evidential weights when used as a defense in a court of law since any conclusions that are drawn from statistical samplings provide room for objectively determined risk of error in any given population (Jokovich, 2013).

References

California State Board of Equalization. (2000, January). Statistical Sampling. Retrieved 2018, from www.mtc.gov/uploadedFiles/.../Audit.../Chapter%2013%20Statistical%20Sampling.pdf/ Cplusglobal. (2014, April 15). Statistical Sampling in Auditing. Retrieved June 2018, from Wordpress: https://cplusglobal.wordpress.com/2014/04/15/statistical-sampling/ Jokovich, G. (2013). Statistical Sampling in Auditing. International Journal of Accounting and Financial Management, 16, 892-898. Simon, P. (2011, March 22). Pros and Cons of Statistical Sampling. Retrieved June 2018, from Law360: http://www.law360.com/