Quota sampling
Encyclopedia
Quota sampling is a method for selecting survey participants. In quota sampling, a population is first segmented into mutually exclusive
sub-groups, just as in stratified sampling
. Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting)
This second step makes the technique non-probability sampling. In quota sampling, the selection of the sample is non-random sample
and can be unreliable
. For example, interviewers might be tempted to interview those people in the street who look most helpful, or may choose to use accidental sampling
to question those closest to them, for time-keeping sake. The problem is that these samples may be biased because not everyone gets a chance of selection. This non-random element is a source of uncertainty about the nature of the actual sample and quota versus probability has been a matter of controversy for many years.
Quota sampling is useful when time is limited, a sampling frame
is not available, the research budget is very tight or when detailed accuracy is not important. Subsets are chosen and then either convenience or judgment sampling is used to choose people from each subset. The researcher decides how many of each category is selected.
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.
Mutually exclusive
In layman's terms, two events are mutually exclusive if they cannot occur at the same time. An example is tossing a coin once, which can result in either heads or tails, but not both....
sub-groups, just as in stratified sampling
Stratified sampling
In statistics, stratified sampling is a method of sampling from a population.In statistical surveys, when subpopulations within an overall population vary, it is advantageous to sample each subpopulation independently. Stratification is the process of dividing members of the population into...
. Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting)
This second step makes the technique non-probability sampling. In quota sampling, the selection of the sample is non-random sample
Random sample
In statistics, a sample is a subject chosen from a population for investigation; a random sample is one chosen by a method involving an unpredictable component...
and can be unreliable
Reliability (statistics)
In statistics, reliability is the consistency of a set of measurements or of a measuring instrument, often used to describe a test. Reliability is inversely related to random error.-Types:There are several general classes of reliability estimates:...
. For example, interviewers might be tempted to interview those people in the street who look most helpful, or may choose to use accidental sampling
Accidental sampling
Accidental sampling is a type of nonprobability sampling which involves the sample being drawn from that part of the population which is close to hand. That is, a sample population selected because it is readily available and convenient...
to question those closest to them, for time-keeping sake. The problem is that these samples may be biased because not everyone gets a chance of selection. This non-random element is a source of uncertainty about the nature of the actual sample and quota versus probability has been a matter of controversy for many years.
Quota sampling is useful when time is limited, a sampling frame
Sampling frame
In statistics, a sampling frame is the source material or device from which a sample is drawn. It is a list of all those within a population who can be sampled, and may include individuals, households or institutions....
is not available, the research budget is very tight or when detailed accuracy is not important. Subsets are chosen and then either convenience or judgment sampling is used to choose people from each subset. The researcher decides how many of each category is selected.
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.