quota sampling

Quota sampling: Difition, application, advantages and disadvantages

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Quota sampling is a non-probability sampling technique where in the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits, or focused phenomenon. This sampling procedure is completely opposite to probability sampling.

 

Example of Quota sampling

Suppose that you are required to conduct a survey regarding the choice of colors by females for a fashion designer. To get an accurate view of the data, you will need to collect data from different sections of the population of different age groups. If you do this randomly, it can be a difficult task because the place where you can find the samples for each group is different. Teenagers hang out at completely different places than old people and their preferences are greatly shaped by their age as well. To make life easier, what you can do is divide the whole sample size into several fractions and assigning each of them to a section of the population.

 

When to Use Quota Samples

The main reason why researchers choose quota samples is that it allows the researchers to sample a subgroup that is of great interest to the study. If a study aims to investigate a trait or a characteristic of a certain subgroup, this type of sampling is the ideal technique.

Quota sampling also allows the researchers to observe relationships between subgroups. In some studies, traits of a certain subgroup interact with other traits of another subgroup. In such cases, it is also necessary for the researcher to use this type of sampling technique.

 

Connection to stratified sampling

 

Quota sampling is the non-probability version of stratified sampling. In stratified sampling, subsets of the population are created so that each subset has a common characteristic, such as gender. Random sampling chooses a number of subjects from each subset with, unlike a quota sample, each potential subject having a known probability of being selected.

In the process of sampling these subgroups, other traits in the sample may be overrepresented. In a study that considers gender, socioeconomic status, and religion based on the subgroups, the final sample may have a skewed representation of age, race, educational attainment, marital status, and a lot more.

 

Steps in Quota Sampling

Quota Sampling is a technical job and requires some steps to be handled carefully. The steps are explained below:

Step-1: Assess the Data and Determine the Traits to be chosen for Classification

In this step, we analyze our data and choose the traits or characteristics to be chosen for the classification of the data. Traits can be:

  • Country of Origin
  • Caste
  • Height
  • Level of Education
  • Sex
  • Age Group
  • Level of Employment

Step-2: Determine the number of Samples to be taken from each Group

In this step, we calculate the number of samples that are to be taken from each of the groups. This is done proportionally with the formula:

Number of Samples taken from a group= Number of Items in the Group (Total number of Samples to be taken /Total number of Items in the population)

step-3: Selection of Samples

In this step, we select the samples in proportion to the number of samples from each group as calculated in Step 2.

The Advantages of Quota Sampling

  • Relatively easy to administer
  • Can be performed quickly
  • Cost-effective
  • Accounts for population proportions
  • A useful method when probability sampling techniques are not possible

The Disadvantages of Quota Sampling

  • Sample selection is not random
  • There is a potential for selection bias, which can result in a sample that is unrepresentative of the population
  • Transgender and transsexual Issues occur
  • Other issues related with items that can not be clearly categorized to certain groups
 

 

 

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