CHAPTER 4: RESEARCH METHODOLOGY AND DESIGN
4.3 Population 112
4.3.1 Sampling 112
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A sample is any subset of the elements of the population that is obtained (by some process) for the purpose of being studied. The process by which elements are drawn from the population is known as sampling (Fox and Bayat, 2007:54). There are two sampling methods that researchers can choose from: one is probability and the other one is non-probability sampling. Fox and Bayat (2007:54) define a probability sample as a sample in which each element in the population has a known and not-zero chance of being included in the sample. According to Maree and Pietersen (2007:172), probability samples satisfy the requirements for the use of probability theory to accurately generalise to the population, while this is not the case with non-probability samples. In non-probability sampling, units of analysis in the population do not each have an equal chance and sometimes have no chance, of being included in the sample (Fox and Bayat, 2007:58). For the purpose of this study, both the probability and non-probability sampling method will be selected.
4.3.1.1 Non-probability sampling
In non-probability sampling, according to Fox and Bayat (2007:58), units of analysis in the population do not each have an equal chance and sometimes have no chance of being included in the sample. Various types of non-probability sampling techniques are discussed below. These techniques include purposive sampling, convenience sampling, snowball sampling and quota sampling.
4.3.1.2 Purposive sampling
A purposive sampling technique will be used for councillors and senior managers.
According to Bless, Higson-Smith and Sithole (2013:173), purposive sampling is based on the judgement of the researcher regarding the characteristics of the representative sample. According to Andres (2012:96), purposive sampling involves the intentional, careful selection and matching of the sample to the study. The strategy is to select units that are judged to be most common in the population under investigation. The purpose of interviewing councillors is that they are the ones who approve the budget based on the needs of the community and they are collectively responsible for playing an oversight role regarding the implementation
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of projects outlined in the Integrated Development Plan. The other reason for interviewing all councillors is that they are at the forefront of service delivery as they are accountable to both their respective political parties and to communities for delivery and non-delivery of basic services.
Other non-probability sampling techniques but which are not relevant to this study are discussed. These include: convenience sampling, snowball sampling and quota sampling.
4.3.1.3 Convenience sampling
Bryman et al (2015:179) maintain that a convenience sample is one that is available to the researcher by virtue of its accessibility. The researcher might want to interview one hundred people at a shopping mall on their perception about a certain product. The questionnaire drafted could be given to any person who is ready available until the required sample is reached. Although this technique is widely used, it is prone to bias. Bryman et al (2015:178) contend that the data collected will not allow definitive findings to be generated because of the problem of generalisation but it could provide a springboard for further research or allow links to be forged with existing findings in the area.
4.3.1.4 Snowball sampling
With snowball sampling, the researcher makes initial contact with a small group of people who are relevant to the research topic and then uses these people to establish contacts with others. A snowball sample is not random because there is no way of knowing the precise extent of the population from which it would have to be drawn (Bryman et al. 2015:179). This type of sampling is also referred to as
“referral”. Snowball sampling is done in phases. In the first phase the researcher approaches a few individuals from the population concerned. Those individuals who are approached then act as informants and identify other members from the same population to be included in the sample (Fox and Bayat, 2007:59). This sampling technique is mostly used by insurance companies and chain stores in selling their product where a targeted client gets an anonymous call from the company and with whom he or she has no relationship or knowledge of trying to sell the product.
117 4.3.1.5 Quota sampling
In the case of quota sampling, the researcher makes an effort to have the same proportion of units of analysis in important strata such as gender, age, socio- economic and ethnicity as reflected in the population. Once the categories and the number of people to be interviewed within each category (quota) have been decided upon, the researcher then selects people who fit these categories. The numbers to be interviewed in each subgroup will reflect the population (Bryman et al., 2015:180). As much as quota sampling is used, it has its disadvantages because:
• The choice of respondents is left to the interviewer, however the proponents of probability sampling argue that a quota sample cannot be representative.
It is believed that interviewers may be influenced by a respondent’s perceptions such as eye contact.
• People who are available in an interviewer’s vicinity at the time interviews are conducted may not be typical.
• The interviewer may make incorrect judgements about certain characteristics in deciding whether or not to approach a person based on looks or age.
• It is impossible to calculate the range of possible values of a population. The researcher cannot calculate a standard error of the mean from a quota sample because the method of selection is non-random (Bryman et al., 2015:180).
As much as there are disadvantages with quota sampling, there are advantages that it possesses.
• It is very useful when the researcher has the demographic profile of the population but does not have access to a database from which to draw a representative sample.
• It is cheaper and quicker than an interview survey on a comparable probability sample.
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• Interviewers do not have to keep on calling back on people who were not available at the time they were first approached.
• A quota sample is easier to manage because it is not necessary to keep track of people who need to be re-contacted or to keep track of refusals.
• When speed is of the essence, a quota sample is invaluable when compared to the more cumbersome probability sample.
• It is useful for conducting development work on new measures on research instruments. It can also be used for exploratory work to generate new theoretical ideas (Bryman et al., 2015:181).