For the following three control attributes, you want to be 90 percent confident that the population deviation rate does not exceed 7.5 percent.

Attribute 1-The purchase order was approved (purchasing department stamp provides evidence)

Attribute 2-The purchase order, receiving report, and vendor invoice are included in each voucher packet

Attribute 3-The accounts payable department compared product and quantities across the three documents (initials by an accounts payable clerk and auditor reperformance provide evidence)

You tested a sample of 52 voucher packages and discovered the following deviations:

• Attribute 1: 2 deviations
• Attribute 2: 1 deviation
• Attribute 3: 0 deviations

Evaluate the results of your testing by:

1. In the Analysis tab, Sample group, choose Attribute to open the Attribute Sampling window.

2. Click on the Sample Evaluation tab

3. Enter the applicable parameters (e.g., % Desired confidence level is 90 and Sample size is 52, Number of deviations in sample listed above. Enter 1000 for the population size.

4. Click Compute

What is the 1-Sided Upper Limit for each attribute? (Note: Ignore 2-Sided Limits when answering this question) (Round your "1-Sided Upper Limit" to 1 decimal place.)

IDEA is able to generate a random sample. With the Accounts_Receivable file open, select Random in the Sample grouping of the Analysis tab. Enter 25 for the Number of records to select. Enter 7 for the Random number seed. Rename the File name to AR Rand Sample leave the other settings as they are and click OK. IDEA will generate a new tab displaying your random sample. Assuming that the electronic data were difficult to obtain and that the client compiled the electronic data only for the sample you selected, evaluate the effectiveness of the control that is designed to ensure that the invoice date always precedes the due date.

How many exceptions did you observe in your sample of 25 (Recall the AR file has a population of 454 records)? Evaluate the sample at 90% confidence. Record the sample deviation rate and the 1-sided upper limit. If you can tolerate a deviation rate of 15% would you accept this control as effective? (Round your "1-Sided Upper Limit" to 2 decimal places.)

How would the sample size change if all sample-size inputs listed in Problem 1 stayed the same with the exceptions listed below? Please evaluate each item independently by resetting the inputs to those listed in Problem 1 and changing only the one factor listed in each item below. Record what the new sample size would be for each scenario.

a. Confidence level dropped to 90 percent?

b. Population size increased to 500,000?

c. Expected deviation rate increased to 4%?

d. Tolerable deviation rate decreases to 7%?

e. Tolerable deviation rate increases to 15%?