Managament accounting

Drawbacks of random sampling (a) Selected items are subject to the full range of variation inherent in the population. (b) An unrepresentative sample may result. (c) An adequate sampling frame might not exist. (d) The numbering of the population might be laborious. (e) It might be difficult to obtain the data if the selected items cover a wide area. (f) It might be costly to obtain the data if the selected items cover a wide area.

Stratified random sampling is a method of sampling which involves dividing the population into strata or categories. Random samples are then taken from each stratum or category.

Advantages: 1) The sample selected will be representative since it guarantees that every important category will have elements in the final sample. 2) The structure of the sample will reflect that of the population if the same proportion of individuals is chosen from each stratum. 3) Each stratum is represented by a randomly chosen sample and therefore inferences can be made about each stratum. 4) Precision is increased. Sampling takes place within strata and, because the range of variation is less in each stratum than in the population as a whole and variation between strata does not enter as a chance effect, higher precision is obtainable

Disadvantages: The main disadvantage of stratification is that it requires prior knowledge of each item in the population; sampling frames do not always contain such information.