Problem 1
In addition to determining sample size, ACL can also select a random sample for you. Draw a sample of Accounts Receivable (AR) transactions from the Roger Company AR table assuming the confidence is 95, the upper error limit is 9 percent, and the expected error rate is 5 percent. 1. Open the Roger_Company_AR table 2. Select Sampling >> Sample Records and the Sample window appears 3. Make sure Record is the chosen Sample Type 4. Under Sample Parameters, click on the Random option 5. Click on the Size button so the Size Dialogue box opens 6. Enter the parameters as specified above (Note: The Population field should automatically have a value in it.) 7. Click on Calculate, click on OK 8. In the To field, type “Roger AR Sample” 9. Click OK 10. How many records are in the new Roger Company AR Sample table? There are 175 records in the new Roger Company AR Sample table.
Problem 2
Assuming that the electronic data were difficult to obtain and that the client compiled the electronic data only for the sample you selected in Problem 1, evaluate the effectiveness of the control that the invoice date should always precede the due date. 1. Create a filter in the Roger AR Sample table for the control described above 2. How many exceptions are there to the control above? 3. Select Sampling from the menu toolbar and click on Evaluate Error 4. Make sure Record is the selected sample type 5. Enter the appropriate parameters (i.e., Confidence 95, Sample Size 175, and the number of exceptions you observed) 6. Click OK 7. What is the upper error limit frequency? The upper error limit frequency is: 17.95%.
Based on the results from the operations you completed above, can the control be considered effective? Why or why not?
The control is considered to be ineffective as the upper error limit frequency is 17.95% exceeds the tolerable misstatement, which is