the objectives and scope of the survey.The choice between using a probability or a non-probability approach to sampling depends on a variety of factors: These will be looked at later in this chapter.Ĭhoosing Between Probability and Non-Probability Samples The most common sampling techniques, such as simple random, systematic, stratified, multi-stage and cluster sampling, are all examples of probability samples. Probability samples require a frame for selection purposes and thus are relatively expensive in terms of operational costs and frame maintenance. Known probabilities also allow the measurement of the precision of the survey estimates in terms of standard errors and confidence intervals. By knowing the selection probability for each unit, objective selections can then be made which should produce a more representative sample. Judgement sampling is also known as purposive sampling.Ī probability sample is one in which every unit of the population has a known non-zero probability of selection and is randomly selected.Ī probability sample allows inferences about the target population to be made. This form of sampling can be used to choose a sample for a pilot test of a probability survey but inferences about the population should not be made from judgement samples. Judgement sampling is subject to unknown biases but may be justified for very small samples. Judgement sampling is where a 'representative' sample is chosen by an expert in the field of study. There is no control over selecting the sample of respondents in any of these methods, however they are very cheap and easy to administer.
Street corner interviews can be biased depending on the timing and the placement of the interviewer. These surveys also have a tendency to ask questions that are loaded or have a biased wording. These types of surveys are subject to biased or unrepresentative samples as only persons who feel strongly about the topic will respond. Street corner interviews, magazine and newspaper questionnaires and phone-in polls are all examples of convenience or haphazard samples. See also the section on Non-Response in Errors in Statistical Data for further details. This is of particular concern when the data items collected influence the likelihood of response. However, when non-response is significant (which is almost always the case for voluntary surveys), quota sampling can under-represent those portions of the population that are unwilling to respond or hard to contact. When top up units are selected randomly to fill a quota, and no element of judgment is used by the researcher for unit selection, it is very similar to a probability sample. This is the method of sampling commonly used by market researchers and political pollsters as it can produce fairly good estimates if it is properly conducted. the interviewers might select the sample to achieve a certain age/sex breakdown reflective of the target population). To select a quota sample, the interviewers select respondents until a pre-determined number of respondents in certain categories are surveyed (eg. rather than make inferences about the target population.ĭifferent types of non-probability samples are discussed below. If a non-probability sample is carried out carefully, then the bias in the results can be reduced.Īs it is dangerous to make inferences about the target population on the basis of a non-probability sample, non-probability methodology is often used to test aspects of a survey such as questionnaire design, processing systems etc. closeness of estimates under repeated sampling of the same size) of estimates from non-probability samples since there is no control over the representativeness of the sample.
However, it is not possible to accurately evaluate the precision (ie. Non-probability samples are often less expensive, easier to run and don't require a frame. If the probability of selection for each unit is unknown, or cannot be calculated, the sample is called a non-probability sample. The main focus of the discussion will be on determining an appropriate sampling method. The following discussion will give a brief introduction to some basic terms and ideas in sampling and an outline of sample designs commonly used. determining the estimation method to be used.choosing an appropriate data collection method and.defining the population, frame and units.The major concerns that should be addressed at this stage are: When you have a clear idea of the aims of the survey, the particular data requirements, the degree of accuracy required, and have considered the resources and time available, you are in a position to make a decision on the size and form of the collection.
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