Students frequently confuse convenience sampling with random sampling. As we have stressed repeatedly, random selection is based on a conscious, deliberate plan that removes any choice on the part of the investigator. In contrast, a convenience sample is based on whatever criteria the investigator happens to use. On the positive side, convenience sampling is quick, easy, and inexpensive. It may be appropriate for exploratory research or for testing scales, for example, but never for developing estimates of parameters.

Quota samples

A quota is a share or an allocation of something.   Some universities, for example, have quotas for the number of students from various parts of the country.   Students from each region are accepted until a certain number, their quota or ratio to the total enrollment, is reached.    Quota sampling works on the same idea. A certain number of persons is selected to represent subgroups that make up the population.   The number or quota for each subgroup is set in advance and persons having the right characteristics are selected until that number is met.

An example may help explain quota sampling.   Imagine that we wanted a sample of male heads of households in a village and we decided to use a quota sample design. Further, let's say we discovered that social status is an important variable for this study. Therefore, we want to be sure that our sample represents the population of male heads a well as possible with respect to social status.    In talking with village elders, we learn that about 25% of the heads are considered poor, about 60% are in the middle range, and 15% are thought to be well off by local standards.    We want a sample, let's say, of 50 men: so we find the quota we need for each status group by multiplying the percentage in each group by the total.   Thus, for the low status group the quota would be 25% times 50 or 12.5, which we could round to 12 men; the quota for the middle group would be 60(50) or 30 men; and the quota for the high group would be 15% times 50 or 7.5 men, which could be rounded up to 8 men.    Using these quotas you could walk around the village, talk with men, and then select and interview enough men to the meet the quota for each group.

Quota sampling can be based on more than one selection factor, but this can get pretty complicated.   If you want to use more than one factor, you will need to consult a book on sampling.

Quota sampling represents an improvement over convenience sampling. It is based on some definition of the intended population. Also, sub-groups of a population are consciously included in the sample. In our illustration, the quota sample would at least include male household heads for all three important social strata. If we had used a convenience sample, we might have included few poor heads because they probably would be less convenient to locate than middle or high status heads. But once the quotas are set, operationally, quota sampling becomes another instance of convenience sampling. Within each quota, the investigator uses personal judgment in selecting sampling elements, resulting in all the biases that occur with convenience sampling.

Quota sampling has another important limitation. The investigator has to know how the variable used for estimating quotas is distributed in the target population. In our illustration, we took the word of local elders for the proportions of low, middle, and high status heads in the village population. If reasonably accurate information is not available for establishing quotas, the sample becomes another form of convenience sampling, with all it limitations.

The idea behind quota sampling can be adapted to limit some of the disadvantages of nonprobability samples. Hassan and others (1988), for example, wanted to analyze possible differences toward male/female equality between men and women with different levels of education. The sample design for this study was based on seeking 30 adults of each gender who met the criteria of either having less than a secondary school certificate (the low education level for this study) or at least having graduated from secondary school (defined as the high education level). In effect, Hassan and her colleagues set a quota of 30 males with low education and similar number with high education and the same for females. The first 30 persons they found in each of the four defined sets became the sample for their investigation.