INTRODUCTION Your audit firm, Garrett and Schulzke LLP, is engaged to perform the annual audit of Hooplah, Inc., for the year ending December 31, 2014. Hooplah is a privately-held company that sells electronics components to companies that manufacture various appliances. The company hires a public accounting firm to provide an audit of its financial statements in order to get favorable terms on its bank loans. Your firm has audited Hooplah for the past three years. For the current audit engagement, your team has already performed most of the audit work; however, there are a few loose ends for you to tie up. Portions of Garrett and Schulzkes audit policy relating to audit sampling are provided to assist you in completing the procedures. AUDIT SAMPLING Audit sampling is commonly applied in performing tests of controls and tests of details. Audit sampling involves the application of audit procedures to less than 100 percent of the items in a population of audit relevance, selected in such a way that the auditor expects the sample to be representative of the population and thus likely to provide a reasonable basis for conclusions about the population. A sample is usually selected either randomly (using some form of random-number generator) or haphazardly (where the auditor attempts to select items randomly but without using a formal random-number generator). Auditors often use sampling approaches that involve formal statistical theories and principles, similar to those you may have learned in an introductory statistics class. Statistical sampling applications require the use of random selection, based on a formal random-number generator (such as the one built in to Microsoft Excel or audit software such as ACL). Auditing standards also allow auditors to use non-statistical sampling approaches. Non-statistical audit sampling approaches are based on a foundation of statistical principles, but allow certain departures from formal statistics in order to simplify the auditors task. One such simplification is that non-statistical sampling allows the use of haphazard selection of the items to be examined. When an auditor examines only a sample instead of all of the items in the population, an element of uncertainty enters into the auditors conclusions. This uncertainty, referred to as sampling risk, is due to the possibility that the sample selected is not representative of the population and that as a result the auditor will reach an incorrect conclusion about the population. It is crucial that sampling risk be taken into account when evaluating the results of any audit procedures that involve sampling. Sampling approaches also differ depending on the nature of the items the auditor is examining and the objectives of the auditor. Depending on the method of sampling used, different formulas and tables are available to help you determine the number of items to include in the sample. This case has two parts. In Part A you will be asked to use statistical attribute sampling for testing controls. In Part B you will use non-statistical substantive sampling for testing accounts receivable.

PART B: TESTS OF DETAILS Regardless of what you found in Part A, for Part B assume that you are able to place moderate reliance on the controls tested and that you have already obtained some substantive evidence supporting the fairness of accounts receivable from substantive analytical procedures. While you have already obtained some assurance regarding the fairness of the ending accounts receivable balance, you do not yet have sufficient evidence given the size of accounts receivable and the remaining risk of misstatement. You plan to request that some of Hooplahs customers confirm their accounts receivable balance directly to you. In the prior years audit, aggregate misstatements of less than 0.5% of the accounts receivable balance were discovered via customer confirmation testing. The few misstatements that were found were promptly corrected by Hooplah. The current-year information that follows will help you in determining the nature and extent of detail testing in order to have sufficient appropriate evidence to conclude on the fairness of the accounts receivable balance. Current Year Information: Net income = $9 million Total assets = $85 million Total accounts receivable = $12,881,551 Accounts receivable greater than 90 days past due = $2 million Tolerable misstatement for accounts receivable = $400,000 In most cases, the selection of items to be detail tested is based on two approaches, which can be used singly or in combination to achieve the desired level of assurance with respect to the population being tested: 1 - Directed Testing 2 - Audit sampling Directed testing, also known as targeted testing or key item testing, is a technique that involves selecting items to examine based on a particular characteristic of interest such as size or risk. Unlike audit sampling, the items are not randomly (or haphazardly) selected. Instead, selection is directed or targeted based on a particular characteristic. Thus, directed testing is not considered sampling per se, because the subset of selected items is not expected to be representative of the population. Garrett and Schulzkes audit policy requires that teams direct test all individual items in the account that are greater than tolerable misstatement. Thus, even if the auditor intends to perform audit sampling to test an account (e.g., accounts receivable), the auditor must first examine all items (e.g., individual customer accounts) that are individually greater than tolerable misstatement. After testing all such items, it is often appropriate to expand the directed testing to specifically select relatively high risk items, if such items can be identified. The auditor may also expand directed testing to select relatively large items other than those that are larger than tolerable misstatement in order to achieve coverage of a higher dollar percentage of the total account. Selection criteria for directed testing can include a combination of risk and size components. Expanding the number of items examined in directed testing can often provide sufficient assurance in combination with the assurance already obtained from other audit procedures (e.g., risk assessment, controls testing, substantive analytical procedures, testing in related accounts, etc.). In such cases, the use of an audit sampling approach is unnecessary. Garrett and Schulzkes substantive audit sampling policy uses a nonstatistical sampling approach. Items are selected from the population either randomly or haphazardly, at the auditors discretion. To determine the appropriate sample size, the firm provides the following formula:

The current-year information that follows will help you in determining the nature and extent of detail testing in order to have sufficient appropriate evidence to conclude on the fairness of the accounts receivable balance. Current Year Information: Net income = $9 million Total assets = $85 million Total accounts receivable = $12,881,551 Accounts receivable greater than 90 days past due = $2 million Tolerable misstatement for accounts receivable = $400,000 In most cases, the selection of items to be detail tested is based on two approaches, which can be used singly or in combination to achieve the desired level of assurance with respect to the population being tested: 1 - Directed Testing 2 - Audit sampling Directed testing, also known as targeted testing or key item testing, is a technique that involves selecting items to examine based on a particular characteristic of interest such as size or risk. Unlike audit sampling, the items are not randomly (or haphazardly) selected. Instead, selection is directed or targeted based on a particular characteristic. Thus, directed testing is not considered sampling per se, because the subset of selected items is not expected to be representative of the population. Garrett and Schulzkes audit policy requires that teams direct test all individual items in the account that are greater than tolerable misstatement. Thus, even if the auditor intends to perform audit sampling to test an account (e.g., accounts receivable), the auditor must first examine all items (e.g., individual customer accounts) that are individually greater than tolerable misstatement. After testing all such items, it is often appropriate to expand the directed testing to specifically select relatively high risk items, if such items can be identified. The auditor may also expand directed testing to select relatively large items other than those that are larger than tolerable misstatement in order to achieve coverage of a higher dollar percentage of the total account. Selection criteria for directed testing can include a combination of risk and size componentse.g., select all customer accounts that are more than 15 days past due and that are greater than $50,000. Expanding the number of items examined in directed testing can often provide sufficient assurance in combination with the assurance already obtained from other audit procedures (e.g., risk assessment, controls testing, substantive analytical procedures, testing in related accounts, etc.). In such cases, the use of an audit sampling approach is unnecessary.

Garrett and Schulzkes substantive audit sampling policy uses a nonstatistical sampling approach. Items are selected from the population either randomly or haphazardly, at the auditors discretion. To determine the appropriate sample size, the firm provides the following formula:

The sampling population book value is the total book value of all the items available to be selected in the sample. This total does not include items already removed for direct testing (i.e., all items greater than tolerable misstatement and other items selected based on size and/or risk characteristics). Tolerable misstatement is the greatest amount of misstatement that can be tolerated for the account being tested without concluding that the account is materially misstated. Expected misstatement is the amount of misstatement that the auditor expects to find in the account being tested. The confidence factor included in the above equation is determined based on the assessed risk of material misstatement for the account and the desired level of confidence from the sample. The confidence factor table below is from Garrett and Schulzkes sampling policy.

*see attached photo* The purpose of audit sampling is to draw conclusions about the entire population through testing a subset of the population. To draw inferences about the entire population, sample results must be projected to the population. Garrett and Schulzkes sampling policy provides two projection methods: ratio projection and difference projection. Ratio projection is performed by calculating the ratio of the misstatement to the sample book value and projecting it to the sampling population book value according to the following formula:

Difference projection is performed by calculating the average misstatement per sample item (e.g. individual customer account) and projecting it to the number of items in the sampling population according to the following formula:

REQUIRED: [2] Based on the same background information as was used for question 1, but assuming that in selecting which customer balances to detail test you want to expand directed testing by selecting additional items based on risk and size, reevaluate the mix of directed testing and audit sampling. If you believe it would be efficient and effective to increase your directed testing, prepare a schedule that includes the following: [a] Identify what characteristic can be used to select riskier items. [b] List the customer numbers and related balances you would select for directed testing based on risk and provide the characteristics you used. [c] List the additional customer accounts you would select for directed testing based on size and coverage. [d] Determine whether it would be necessary to test the remaining population using audit sampling; if so, compute your sample size for testing the remaining population through audit sampling and justify the inputs you used in the sample size formula.

[3] Which detail testing approach seems most appropriate in this situation: the minimum level of directed testing together with a larger audit sample, expanded directed testing with no audit sampling, or both expanded directed testing and audit sampling? Be sure to consider the effectiveness and efficiency of the approach, as well as the level of assurance needed in view of the evidence already obtained from controls testing, substantive analytical procedures, etc. [4] Independent of your responses to prior questions, assume that you direct tested customer balances greater than tolerable misstatement and randomly selected a sample of 40 additional customer balances for confirmation. The total book value of the 40 items sampled is $761,030. No differences were noted in the directed testing, and the sample yielded a combined overstatement in Hooplahs records of $4,215. Brian Thompson, the accounts receivable supervisor agrees that the differences noted are misstatements due to pricing errors. Please answer the following questions: [a] How much is the known misstatement in the accounts receivable balance? [b] How much is the projected misstatement in the population (i.e., the total accounts receivable account) using ratio projection?

SampleSize = Sampling Population BookValue *Confidence Factor (Tolerable - Expected Misstatement) Projected Misstatement = Sample Misstatement -* Sampling Population Book Value Sample BookValue SampleSize = Sampling Misstatement *Number ItemsIn Sampling Population SampleSize Low Confidence Factors for Nonstatistical Sampling Assessment of Risk of Desired Level of Confidence Material Misstatement High Moderate High 3.0 2.3 Moderate 2.3 1.6 Low 2.0 1.2 2.0 1.2 1.0 SampleSize = Sampling Population BookValue *Confidence Factor (Tolerable - Expected Misstatement) Projected Misstatement = Sample Misstatement -* Sampling Population Book Value Sample BookValue SampleSize = Sampling Misstatement *Number ItemsIn Sampling Population SampleSize Low Confidence Factors for Nonstatistical Sampling Assessment of Risk of Desired Level of Confidence Material Misstatement High Moderate High 3.0 2.3 Moderate 2.3 1.6 Low 2.0 1.2 2.0 1.2 1.0