Discovery and Sequential Attributes Sampling. Sydney Siebenthaler, the audit manager for Jennifer’s Running Shirts Inc., has just returned from a continuing education class on audit sampling and now wants to use discovery sampling or sequential sampling on the Jennifer’s audit because the class instructor said that the sample sizes would be significantly smaller. “Talk about a no-brainer!” Siebenthaler exulted.
Jennifer’s has good controls, and the audit team has performed tests of controls over the payroll procedures in previous years to reduce substantive tests of payroll accounts to only analytical procedures. In the previous year, the audit team used the following parameters: risk of overreliance, 10 percent; expected population deviation rate, 2 percent; and tolerable rate of deviation, 10 percent, which resulted in a sample size of 38. The auditors increased (rounded) the sample size to 40 items, and one deviation was found. The resulting ULRD rate was 9.4 percent, and the control was accepted as operating effectively.
Required:
a. Define discovery sampling.
b. Do you agree that discovery sampling should be used on the audit of Jennifer’s?
c. How would discovery sampling be used?
d. Define sequential sampling.
e. Do you agree that sequential sampling should be used on the audit of Jennifer’s?
f. How would sequential sampling be used?
USING IDEA IN ATTRIBUTES SAMPLING
Exercises F.79, F.80, and F.81 require the use of IDEA in an attributes sampling context. Elm Manufacturing Company (ELM) is a small manufacturer of backpacks located in Rochelle, Illinois. You are testing controls related to the authorization of sales made to customers on account and are interested in ensuring that goods are only shipped to customers following a formal credit approval. You have access to ELM’s electronic records in Connect. The appropriate file for these exercises is the Sales 2017–4th Q data set. Detailed information about ELM, instructions for accessing data sets, a data directory for data sets, and a detailed attributes sampling example (with IDEA screenshots) can be found in Connect.
NOTE: The Sales 2017–4th Q data set contains a total of 410 transactions; because you are only examining the credit approval for goods that have been shipped, you would only examine orders through No. 17383 (a total of 388 shipments).
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