According to Parahoo (2006, p.375), data analysis is “an integrated part of the research design”, which is a way of appreciating the data before presenting them in an understandable manner. While Authors(De Vos, 2005:333; Neuman, 2006:16) describes data analysis as a way in which the data was captured, analysed, and the statistical procedures used in order to bring meaning and measure to it. For the purpose of this mix method, study both qualitative and quantitative data collected from the field will be analysed.
Content analysis will be used to analyze the data that will be gathered from focus group interviews. The process of analysing the qualitative data will start immediately after the focus group discussions is concluded. Therefore, the aim of this study is to follow the process outlined by Babbie and Mouton (2010:493, 494, 495);
Creswell and Plano Clark (2007:129); Schurink, Fouché & De Vos (2011:403-404); Singh (2007:82); Welman, Kruger and Mitchell (2005:211) to achieved the following: managed or organised data so as to make it easily retrievable and managed; analysed, described, and classified data; represented and visualised data so as to be able to present and place them in the form of themes and statements.
The Data will also be validated and interpreted (Alasuutari et al., 2008:362, 363; Creswell & Plano Clark, 2007:35; Flick, 2008:16; Schurink, Fouché & De Vos, 2011:417). According to Moore & McCabe (2005), this is the type of research whereby data gathered is categorized in themes and sub-themes, will be able to be comparable. This will help us to reduce and simplify the data collection processes, while at the same time producing results to assist in the measurement of using quantitative techniques.
Another aim of the content analysis in this research is to assist us to structure the qualitative data collected in a way that satisfies the accomplishment of research objectives. However, human error can be highly involved in the content analysis process, since there is the risk for researchers to misinterpret the data gathered, thereby generating false and unreliable conclusions (Krippendorff & Bock, 2008).Thus, in additional to content analysis, the Statistical weighted mean will be used to answer the research questions.
Most of the response options in the questionnaire instrument will be weighted as shown below:Table xx: Likert Scale of SignificanceStrongly Agree Agree Undecided/ Neutral Strongly Disagree DisagreeSA A U/N SD D5 Points 4 Points 3 Points 2 Points 1 PointThe acceptance point for the items will be 2.50. Nworgu, (1991), purports that the t-test is testing hypothesis about the differences between means when the sample size is small.
Therefore, we will be using, the t-test statistical analysis to test the three null hypotheses used in this study. On the other hand, if the calculated t-value is greater than the critical value of t, the null hypothesis will be rejected and the alternative, which is “significance” will be accepted. By extension if the calculated t-value is lesser than the critical t-value, the null hypothesis (Research questions) will be accepted and the alternative rejected.
However, the null hypotheses will be tested at 0.05 (5 %) level of significance. This means 5 chances of being in error out of every 100 cases. Therefore, any chances of error will be very low.The statistical weight mean will be supported and complemented by the use of IBM SPSS Statistics 19 (Singh, 2007:83).
According to some authors(Babbie& Mouton, 2010:459; Fouché & Bratley, 2011:251) the researcher will be using descriptive methods to describe, analyse, and summarise numerical data into major characteristics of the study without distorting or losing too much of valuable information, so that it is simple, manageable, and more understandable and to facilitate eventual processing of data, the researcher will also be analysed quantitative data according to different themes of the measuring instrument (Delport & Roestenburg, 2011:196). Most importantly data will be presented and displayed in the form of table/s and graphic/s. (Fouché & Bratley, 2011:257).