Applications of belief functions in business decisions: A review <s> Integrating Statistical and Non-Statistical Evidence <s> The auditing profession: the auditing profession audit report professional ethics legal liability. The auditing process: audit responsibilities and objectives audit evidence audit planning and documentation materiality and risk the study of internal control and assessment of control risk overall audit plan and audit program audit of the sales and collection cycle audit sampling for tests of transactions completing the tests in the sales and collection cycle - accounts receivable audit sampling for tests of details of balances the effect of complex EDP systems on auditing. Application of the auditing process to other cycles: audit of the payroll and personal cycle audit of the acquisition and payment cycle: tests of controls substantive tests of transactions and accounts payable completing the tests in the acquisitions and payments cycle: verification of selected accounts audit of the inventory and warehousing cycle audit of the capital acquisition and repayment cycle audit of cash balances. Completing the audit and offering other services: completing the audit other audit attestation services and compilation engagements internal and governmental financial auditing and operational auditing. <s> BIB001 </s> Applications of belief functions in business decisions: A review <s> Integrating Statistical and Non-Statistical Evidence <s> The Dempster‐Shafer belief function framework has been used to model the aggregation of audit evidence based on subjectively assessed beliefs. This paper shows how statistical evidence obtained by means of attribute sampling may be represented as belief functions, so that it can be incorporated into such models. In particular, the article shows: (1) how to determine the sample size in attribute sampling to obtain a desired level of belief that the true attribute occurrence rate of the population lies in a given interval; (2) what level of belief is obtained for a specified interval, given the sample result. As intuitively expected, we find that the sample size increases as the desired level of belief in the interval increases. In evaluating the sample results, our findings are again intuitively appealing. For example, provided the sample occurrence rate falls in the interval B for a given number of occurrences of the attribute, we find that the belief in B, Bel(B), increases as the sample size increases. ... <s> BIB002 </s> Applications of belief functions in business decisions: A review <s> Integrating Statistical and Non-Statistical Evidence <s> An overview of audit sampling selecting a representative sample attribute sampling compliance auditing with laws and regulations using variable sampling for accounting estimation using variable sampling for audit hypothesis testing probability proportionate to size sampling non-statistical sampling techniques. <s> BIB003
We know that the auditor collects both statistical and non-statistical items of evidence on every engagement. An example of statistical evidence is the procedure to determine the value of inventory using a statistical sampling technique (see, e.g., BIB001 BIB001 BIB003 . At the moment, an auditor often uses an intuitive approach to combine such items of evidence. However, the problem is that the auditor is not able to take full advantage of the strength of evidence that may be non-statistical in nature to save on the extent of work done for statistical tests.  show how one can convert statistical evidence, es-pecially, in a variable sampling technique, to evidence in belief functions. BIB002 extend the work of  to attribute sampling. Auditors use attribute sampling in testing effectiveness of internal controls in accounting information systems.  compare the effectiveness and efficiency of audit procedures using three different approaches. They perform simulation study to determine the audit risk in complex situations and contend that the "belief based audit is always more efficient than a simple one and can be less efficient than the traditional approach." They also mention that the belief-based approach is the most effective among the three models used. is a commonly used statistical test by auditors for predicting the account balances.   provides how statistical evidence obtained through Dollar Unit Sampling can be converted into belief functions. 