RESEARCH METHODOLOGY
5.5 Target population
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was an open-ended section of the questionnaire which was designed to further gather quantitative data among participants from the three districts in order to get a general consensus on what the youths feel influences psychological factors, political environment and information awareness on entrepreneurial behaviour in the province; while the closed ended led respondents to a predetermined direction to infer causation and general perception. The design also, allowed insights into the impact of government intervention strategies (political environment) and how this has not adequately arrived at a lasting solution. Review of related literature that adopted this approach serve as a basis for adopting this approach.
120 5.5.1 Sample size
Sample size for this study was selected based on the objective of the study, the precision of desired outcome, cost factor and time frame. The research was conducted in the three districts of Mpumalanga to ensure proper coverage of the province; three locations were selected from each district due to the concentration of youths, proximity to Mpumalanga capital (Nelspruit), and level of unemployment. 500 unemployed youths were considered at these locations as advised by Department of Labour local offices and the administrative department of GS- College in the selected locations. Krejcie and Morgan sample size table was used to determine appropriate sample size from the population. In addition to this, the sample size was calculated using the formula to calculate size when population size is known, thereby removing any form of ambiguity in sample size calculation.
FORMULA FOR DERTERMINING SAMPLE SIZE WHEN POPULATION SIZE IS KNOWN
SIZE = _____X2 NP (1-P)____________
d2 (N-1) + X2 P (1-P) Where:
X2 = table value of Chi-Square @ d.f. =1 for desired confidence level .10 = 2.71 .05 = 3.84 .01 = 6.64 .001 = 10.83
N = population size
P = population proportion (assumed to be .50)
d = degree of accuracy expressed as a proportion (.05)
Illustration: If the population size of unemployed youths in Barberton population equals 120 then to get sample size for Barberton:
SIZE = _____X2 NP (1-P)____________
d2 (N-1) + X2 P (1-P)
= ____(3.84) (120) (0.5) (1-0.5)___
(0.05)2 (120-1) + (3.84) (0.5) (1-0.5)
= _______115.2_______
0.2975 + 0.96
= _______115.2________
1.2575
= 91.61
= 92
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Therefore if the population size is equal to 120 the sample size will be 92, which is the same figure obtained on Krejcie and Morgan sample size population table. In line with this, Barberton population of 120 equals 92 samples, Gert-Sibande population of 146 equals sample size of 108 and Kriel population of 260 gave sample size of 155. In total, the population equals 500 and sample size equals 355.
A total of 355 unemployed youths were randomly selected from the three locations as an appropriate sample size for primary data collection purposes facilitated by questionnaires.
5.5.2 Sampling designs
Sampling is a means of choosing a subset of components from a target population with the aim of getting information and drawing inferences from the information about the entire population (Statistics Canada, 2015). There are two types of sampling: probability and non- probability sampling. Non-probability sampling adopts a subjective approach in selection of components from the population, because it is relatively easy and quick approach, it is best suited for preliminary studies or follow-up studies. It includes quota, convenience sampling and snowball (Wilson, 2010). Probability sampling on the other hand is best suited to draw inferences from the entire population and quantify the error of estimates, therefore more acceptable for statistical programs. There are three principles that must be observed in probability sampling according to Stats Canada, (2003 modified in 2015), (a) randomisation- selection of units at random, (b) positive possibility selection of all the units from the target population, (c) the probability can be calculated- which facilitates the calculation of sampling error (Sekaran & Bougie, 2013).
5.5.3 Simple random sampling
A simple random sampling gives equal opportunity of selection to every unit in the population thereby reducing bias. A simple illustration of how participants were selected from each location using random sampling was explained below.
Formula to select participants randomly = INT (N *RAND ( ))+1 using Microsoft excel sheet.
Where N is the sample size needed, therefore to select participants randomly in Barberton with sample size of 92, = INT (92*RAND ( ) )+1, which gave series of random numbers.
Prospective participants were numbered from 1 to 120 (population of unemployed youths in the location), out of which only 92 were needed, so as the table generates random numbers like 91, 29, 87, 65, 36, 10, 19, 27, 8, 66, 23……..51, each persons with such numbers were
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picked until 92 participants were completely selected thereby reducing biases as every prospective participants have equal chance of being picked.
This approach gives equal chance to every participant in the target population to be selected, which makes selection largely objective and reduces biases, increase reliability and produces a balanced subset that represents the entire target population (Wilson, 2010; Bryman & Bell, 2015).
It important to mention some of the difficulty associated with simple random, which are (a) time factor- it takes time to get a complete list of a target population- researcher travelled to the different locations in Mpumalanga before list of unemployed youths were made available.
(b) It is expensive – the associated cost is high. (c) Biases –although simple random sampling is supposed to be largely unbiased to give adequate inference of the entire population however, where selected sample is too small the outcome will not represent the entire population. This study used Krejcie and Morgan (1970) sample population table to calculate sample size and selected the exact number from the population.
Table 5.3 Sample size population
After determining the study locations as stated above, and calculating the sample size of 355, simple random sampling was used to select the sample size per location, for Kriel of 260 populations, 1 in every 2 was used to select 155 respondents, and this applied to other locations too to minimise bias. Questionnaires were distributed to the selected respondents at designated location and at a predetermined date.