A sampling method refers to strategies used to obtain a sample, including probability and nonprobability sampling techniques, also called a sampling plan (du-plooy-Cilliers et al., 2014). Various sampling techniques are further discussed below.
3.7.1 Probability Sampling
Probability sampling is the primary method used in selecting a large, representative sample. In this sampling technique, the researcher selects participants for inclusion in the sample, so that all individuals have an equal possibility of being chosen from the population (Creswell, 2014). There are three forms of probability sampling; simple random, stratified and multistage cluster sampling (Creswell, 2014).
Simple Random Sampling
For this form of sampling, the researcher chooses participants for inclusion in the sample so that any individual from the population has an equal probability of being selected for participation. The intent of simple random sampling is to choose individuals who will be representative of the population, thus allowing any bias in the population to be equally distributed among those chosen participants (Creswell, 2014).
Systematic Sampling
Systematic sampling is a small variation of simple random sampling. For this technique the researcher chooses every ninth individual or site in the population, until s/he reaches the desired sample size. Although this procedure lacks the precision and rigour of random number tables, it is more convenient (Creswell, 2014).
Stratified Sampling
In stratified sampling, the researcher divides or stratifies the population based on a specific characteristic, creating subgroups based on each trait. Then through simple random sampling, the researcher obtains samples from each subgroup, thus ensuring that the complete sample includes specific traits required by the researcher in his sample (du Plooy-Cilliers et al., 2014).
3.7.2 Non-probability Sampling
A non-probability sampling technique is used where the researcher is unable to select the kind of probability samples used in comprehensive studies. In this type of sampling the researcher chooses individuals because they are readily available, convenient and represent some characteristic s/he seeks to study (Babbie & Mouton, 2011). Some situations may necessitate that the researcher involves participants who volunteer and agree to be studied (Babbie & Mouton, 2011). Furthermore, the researcher may not be interested in generalising his findings to a population, but only interested in describing a small group of participants in his research. It may also be simpler to calculate descriptive statistics on these samples and compare the results with the bigger population to make extrapolations from the sample to the population. There are three popular approaches to non-probability sampling commonly used by researchers: convenience, snowball and purposive sampling (Babbie & Mouton, 2011).
Convenience Sampling
Convenience sampling is a non-probability sampling technique which involves a conscious subjective selection of certain elements or subjects, to participate in the study by the researcher (Saunders et al., 2009). This technique enables the researcher to select elements of the population that are easily accessible and provides rich information that deepens the study findings (Creswell, 2014; Malhotra, 2010). The selection of elements is primarily left to the researcher (Malhotra, 2010). According to Malhotra (2010), convenience sampling is the least expensive and least time-consuming of all the sampling methods in that the elements are easily accessible, easy to measure and cooperative. The limitation of this type of sampling is that it is prone to bias and influence beyond the control of the researcher as the cases are selected mainly on the easy accessibility of the respondents (Creswell, 2014; Saunders et al., 2009).
Snowball Sampling
Snowballing is an alternative to convenience sampling, which involves the researcher asking the initial participants to identify others to be included in the sample. The advantage of snowball sampling is that it can recruit large numbers of participants. The disadvantages of this form of sampling is that the researcher has no control over exactly which individuals are included in the sample and it is also impossible to identify the participants that do not return questionnaires. Furthermore, respondents may not be representative of the respondent to the study (du-plooy-Cilliers et al., 2014).
Purposive sampling
This study used purposive sampling. According to Saunders, Lewis and Thornhill (2009), purposive sampling allows researchers to use their discretion to select cases that best answer the research questions and meet the study objectives. Purposive sampling is also known as judgemental sampling (Saunders et al., 2009). Furthermore, purposive sampling allows the researcher to rely on their experience, ingenuity and previous research findings to choose elements of the population that are of the study (Malhotra, 2010). This type of sampling technique is often used to select cases that are highly informative about the research problem and is normally used for case study research studies (Saunders et al., 2009). According to Malhotra (2010), judgemental sampling is a low cost, quick and convenient way of collecting primary data. This sampling approach was used in two different ways in this study. Firstly, purposive sampling technique was
used to narrow down the research population, to best fit the focus of the study (third year female students). Secondly, purposive sampling was used to distribute the questionnaire to the research participants of this study. This study used purposive sampling because it helped the researcher to focus on the characteristics of a population that were of interest (third year female students), to address the research objectives of this study.