SAMPLING PROCESS

According to Terre Blanche et al. (1999:44-45), the sampling process comprises several stages, namely:

• Defining the population of concern.

• Specifying a sampling frame, a set of items or events possible to measure. • Determining the sample size.

• Specifying a sampling method for selecting items or events from the frame. • Implementing the sampling plan, and

• Sampling and data collecting

The decisions regarding the sequential stages in the sampling process normally follow the sequence as stated above, although the actual order of events did not always follow this

Positivistic paradigm Phenomenological paradigm Concerned with hypothesis testing Concerned with generating theories Tends to produce quantitative data Tends to produce qualitative data Uses large samples Uses small samples

Data is highly specific and precise Data is rich and subjective Reliability is high Reliability is low

Validity is low Validity is high

particular sequence. These events are generally highly interrelated (Terre Blanche et al. (1999:44-45; Collis & Hussey, 2003:155-160).

The process of sampling involves any procedure using a small number of parts of the whole population to draw conclusions regarding the population (Terre Blanche et al. 1999:44-45), while the purpose of sampling is to enable researchers to estimate some unknown characteristic of the population (Collis & Hussey, 2003:155-160). In this section the following stages in the sampling process, namely population, sampling frame, sampling unit, sample size and sampling methods will be discussed,

4.4.1 Population

For research purposes, a population can be defined as including all people or items with the characteristics one wish to understand or any complete group or body of people or any collection of items under consideration for the research purpose (Sekaran, 2000:226). The research population is defined as a group that the research wants to generalise about (Cresswell, 1994:119). For the current study, the population (N) refers to all the Alumni of the selected HEI in the Eastern Cape and all potential employers of graduates from the selected HEI.

4.4.2 Sampling frame

Throughout the actual sampling process the elements of the sample frame must be selected according to a certain procedure. The population (N) has to be narrowed down to the sampling frame which comprises the complete group of specific population elements relevant to the research project (Terre Blanche et al. 2006:133). The sampling frame for this study comprised all the Alumni who attained qualifications in the Commerce Faculty at the selected HEI for the Commerce Graduate questionnaire and the all employers who employ these Commerce graduates. About 6 377 (N) alumni from the Faculty of Commerce were identified and also 200 Commerce graduate employers (N) were identified from the database of the selected HEI’s Career Centre which was drafted by the then Head of the Career Centre, Mr Jurgen Kietzmann. Defining the sampling frame is important as it is the source from which the primary data will be obtained.

Because there rarely is enough time or money to gather information from everyone or everything in a population, the goal becomes finding a representative sample (or subset) of

that population (Yates, 2004:25). In Sections 4.4.3 to 4.4.5 the sampling unit, size and method will be discussed respectively.

4.4.3 Sampling unit

The sampling unit is a distinct element or group of elements subject to selection in the sample (Seaberg, 1988:244). The sampling unit for the research in question comprised the Alumni of the Faculty of Commerce who provided the Development and Alumni Relations Division with their electronic mail addresses (N = 1 870) for the Commerce graduate survey and the employers of Commerce graduates who provided the Career Centre with their human resources practitioners’ electronic mail addresses (N = 85).

The Commerce graduates with known email addresses (N = 1 870) were extracted from the alumni database, with a total of 6 377 holding a Baccalaureus of Commercii degree. This was facilitated by the alumni office in the Development and Alumni Relations Division of the selected HEI. The employers with known addresses (n = 85) were extracted from the selected HEIs Career Centre database, with a total of 200 employers identified.

4.4.4 Sample size

The sample size (n) refers to the number of people in a particular sample (De Vos et al. 2005:196). In other words, sample size is the number of observations used for calculating estimates of a given population (Welman & Kruger, 2001:63-65). Larger samples enable researchers to draw more representative and accurate conclusions and to make predictions with greater accuracy than do smaller samples. In contrast, it also holds that the smaller the total population, the relatively larger the sample size should be to ensure satisfactory results. According to Welman and Kruger (2001:63-65), sample sizes may be chosen in the following ways:

• Expedience - for example, including those items readily available or convenient to collect. A choice of small sample sizes, though sometimes necessary, can result in wide confidence intervals or risks of errors in statistical hypothesis testing;

• Using a target variance for an estimate to be derived from the sample eventually obtained; and

• Using a target for the power of a statistical test to be applied once the sample is collected.

employed Commerce graduates from the selected HEI with known email addresses to the selected HEIs Career Centre and 1 870 Commerce graduates (Alumni) whose email addresses were known to the selected HEI’s Development and Alumni Relations Division.

4.4.5 Sampling methods

There are two main categories of sampling methods, namely probability and non-probability sampling (De Vos et al. 2005:192-199). A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined (De Vos et al. 2005:192-199). Considering the aforementioned, it is possible in probability sampling to produce unbiased estimates of population totals by weighting sampled units according to their probability of selection (Welman & Kruger, 2001:43-64). Probability sampling includes: simple random sampling, systematic sampling, stratified sampling, probability proportional to size sampling and cluster or multistage sampling (Terre Blanche et al. 1999:275). This variety of ways of probability sampling have, according to Collis and Hussey (2003:155-160), two things in common, namely, every element has a known non-zero probability of being sampled and it involves random selection at some point.

On the other hand non-probability sampling is any sampling method where some elements of the population have no chance of selection (these are sometimes referred to as 'out of coverage/under covered'), or where the probability of selection cannot be accurately determined (De Vos et al. 2005:198-200). It involves the selection of elements based on assumptions regarding the population of interest, which forms the criteria for selection. In essence, therefore, the units of the sample are selected on the basis of personal judgement. Non-probability sampling includes: accidental sampling, quota sampling, purposive sampling, and convenience sampling (De Vos et al. 2005:198-200).

Based on the merits of the sampling frames and sampling units described above, the non- probability sampling methods were deemed appropriate for this research. More specifically, a combination of convenience sampling and purposive sampling were used in this study.

Convenience sampling is when the researcher uses the most convenient or most economical

sample (Terre Blanche et al. 1999:276). The advantage of convenience sampling is that it is fast and there is no need for a list of the population. Its disadvantages are that variability and bias of estimates cannot be measured or controlled and projecting data beyond the sample is

inappropriate (Terre Blanche et al. 1999:276). In this study, all respondents comprised the Commerce graduates (Alumni) and employers of Commerce graduates at the selected HEI with electronic mail addresses of Alumni and Human Resource practitioners of employers that could be accessed conveniently. From the above, it is evident that convenience sampling pertains to sampling by obtaining units or people who are most conveniently available, in this case, access to respondents with known email addresses (De Vos et al. 2005:198-200).

A purposive sample is one which is selected by the researcher subjectively. The researcher attempts to obtain a sample that appears to him/her to be representative of the population and will usually try to ensure that a range from one extreme to the other is included (De Vos et al. 2005:198-200). Purposive sampling was chosen because the Commerce graduate (Alumi) respondents are familiar with and ideally positioned to assess the Commerce students and programmes of the relevant HEI. They had to state whether their needs and expectations specifically in terms of quality of tuition received in core courses) were met, the extent to which certain skills and traits required for successful job performance were developed, and the outcomes of studies in the Commerce faculty as well as their perceptions on the overall experience as a Commerce graduate.

The human resources practitioners were selected as a respondent group because of their involvement in the selection and recruitment of suitable and competent personnel to meet the needs of business practice. Moreover, they are also involved in assessing the training and development needs of their business firms. Due to their position in business and the recruitment of Commerce graduates from the selected HEI, they were regarded as the most appropriate practitioners to make recommendations pertaining to the Commerce curriculum development in South Africa and to assess the following:

• The relative importance of core courses for the running of a business and the proficiency of the Commerce graduate in these courses.

• The relative importance of management skills and traits as required in the work environment, as well as the proficiency of the Commerce graduate in these skills and traits, and

For the research in question, Commerce graduates (Alumni) with qualifications in the Commerce field and employers who employ these graduates were selected purposely, as they have the knowledge and first-hand experience pertaining to the research topic as explained in this section.