Question

Which of the following types of sampling allows an auditor to quantify sampling risk?

Stratified nonstatistical.

Block.

Haphazard.

Attribute.

Answer 1

Meaning of Audit Sampling

Audit sampling is the application of an audit procedure (test of control or substantive testing) to less than 100% of the items within an account balance or class of transactions for the purpose of drawing a general conclusion about the account balance or the entire group of transactions based on the characteristics detected in the sample. Sampling allows an auditor to draw conclusions about transactions or balances without incurring the time and cost of examining every transaction.

When is sampling used?

Sampling is generally used in field audits when it is not efficient to review 100% of the records. Sampling may also be used if records are missing or other circumstances make reviewing all of the records difficult.

Representative Sample

A representative sample is one in which the characteristics in the sample of audit interest are approximately the same as those of the population. Two things cause a sample to be non-representative:

► Non-sampling risk

► Sampling risk

Non-Sampling Risk

Non-sampling risk is the risk that the audit tests do not uncover existing exceptions in the sample. The two causes are:

► Auditor failure to recognize exceptions

► Inappropriate or ineffective audit procedures

Sampling Risk

Sampling risk is the risk that an auditor reaches an incorrect conclusion because the sample is not representative of the population. This can be controlled by:

► Adjusting the sample size

► Using an appropriate method of selecting sample items

Audit Risk

Risk Models Audit Risk = Inherent Risk X Control Risk X Detection Risk

Audit Risk = Sampling Risk + Non-Sampling Risk

Sampling Risk

in Attribute Sampling Risk of Underreliance Control Risk Too High Not relying on the internal controls when, in fact, the auditor should rely on internal control. Risk of Overreliance Control Risk Too Low Relying on internal controls when it is not appropriate.

Methods Of Sample Selection

Sample items should be selected in a way so that the sample can be expected to be representative of the population; therefore, all items in the population should have a chance of being selected. Common methods of selecting samples are:

(a) block sampling;

(b) haphazard sampling;

(c) random number sampling; and

(d) systematic sampling.

Note: Block sampling does not meet the requirements for a representative sample. The other three do. Ordinarily, only the last two methods are used in statistical sampling.

Block Sampling – A block sample is obtained by selecting several items in sequence. Once the first item in the block is selected, the remainder of the block is chosen automatically. For example, the sample may consist of all vouchers processed during a two-week period or all vouchers processed on specific days. Block samples could theoretically be representative samples but are rarely used because they are inefficient. The time and expense to select sufficient blocks so that the sample could be considered representative of the total population is prohibitive.

Haphazard Sampling – A haphazard sample is obtained by selecting, without any conscious bias, items regardless of their size, source, or other distinguishing characteristics. It is not the selection of sample units in a careless manner; the units are selected in a manner so that the sample can be expected to be representative of the population. For example, the sample may consist of vouchers pulled from all vouchers processed for the year. Excluding items from the sample on the basis of judgment invalidates the requirement for a representative sample.

Random Number Sampling – A random sample is obtained by selecting numbers from a random number table or by generating numbers randomly by computer and matching them with document numbers, such as check numbers and invoice numbers.

Systematic Sampling – A systematic sample is obtained by selecting items at uniform intervals. The interval is determined by dividing the number of physical units in the population by the sample size. A starting point is selected at random in the first interval, and one item is selected from the population at each of the uniform intervals from the random starting point. For example, in a population of 20,000 units and a desired sample of 100 units, every two hundredth item will e selected from the starting point. Neither the size nor the unusualness of an item should be allowed to influence selection. The auditor can select large and unusual items in addition to items sampled, however.