Sampling methods - Systematic Sampling
Systematic Sampling involves selecting items using a constant interval between selections, the first interval having a random start. The interval might be based on a certain number of items (for example every 20th voucher) or monetary total (for example every AED 1,000 in the cumulative value of the population).
When using systematic selection, the auditor should determine that the population is not structured in such a manner that the sampling interval corresponds with a particular pattern in the population. For example, in a population of branch sales, particular branch sales occur only as every 100th item and the sampling interval selected is 100. The result would be that either the auditor would have selected all or none of the sales of that particular branch. To minimize the effect of the possible known buyers through a pattern in the population, more than one starting point may be taken. The multiple random starting points are taken because it minimizes the risk of interval sampling pattern with that of the population being sampled.
There are mainly two methods by which auditor can select samples from the basic data on population.
(I) Block Sampling: - This method involves the selection of a defined block of consecutive items. For example take the first 200 sales invoices from the sales day book in the month of September; alternatively take any four blocks of 50 sales invoices. Therefore, once the first item in the block is selected, the rest of the block follows an items to the completion. There is a close similarity between this method and judgmental sampling. Consequently it has similar characteristics, namely, simplicity and economy. On the other hand there is a risk of bias and of establishing a pattern of selection which may be noted by the auditees. This method would not be an appropriate sample selection technique when the auditors intend to draw valid inferences about the entire population, based on the sample.
(II) Cluster Sampling: - This method involves dividing the population into groups of items known as cluster. A number of clusters are randomly selected from all the clusters rather than individual items of the population. Cluster sampling can be used together with both unrestricted random and stratified sampling, for example 500 to 540, 2015 to 2055 etc. The first item i.e., 500, 2015 is randomly selected from random number tables. The items of selected cluster can either be checked completely or a randomly selected proportion of them can be examined.
The cluster is less effective for a given sample size than unrestricted random and stratified samples as items are not individually selected. However, the time saved can be utilized to have a larger sample to make the sample results more reliable. Ideally the clusters chosen should be dissimilar so that the sample is as representative of the population as possible.
Merits and limitations of systematic sampling:
» This method is convenient.
» Time and work is reduced much.
» If proper care is taken result will accurate.
» It can be used in infinite population.
» Systematic sampling may not represent the whole population.
» There is a chance of personal bias of the investigators.