View/Open - University of Zululand Institutional Repository
View/Open - University of Zululand Institutional Repository View/Open - University of Zululand Institutional Repository
affairs and activities of these five rural areas was interviewed using open-ended questions about the socio-economic conditions and development in these areas. Also interviewed were the ward councillors responsible for these rural areas on the sustainability of community development projects and job creation using the landscape and cultural attributes. The digital spatial data were then obtained from the current census as well as other secondary sources of information. This served as the spatial basis for evaluating the level of effectiveness and efficiency in landscape and cultural attributes on the local economic development of the Ulundi Local Municipality. 4.2.4.2 Attribute data The attributes of spatial objects allowed for spatial analysis by defining the different characteristics ofobjects. Data on variables such as: • Awareness level ofexisting tourism products e.g., game reserves • Monthly income ofhousehold heads were used to create pie-charts and or bar graphs in order to compare and differentiate the responses ofhousehold heads between the five spatial units ofthe study area. 4.3 ANALYSIS OF DATA Analysis in research means the breakdown, categorisation, ordering and summarising of data so as to get answers to research questions. The purpose of analysis is to reduce data into intelligible and interpretable form, which can be achieved through the process of description. explanation and prediction, and these vary with the statistical measures used (Magi, 2005). In this study, statistical analyses of frequencies, cross tabulations and of association between attributes were used to complement the qualitative discussion. 4.3.1 Frequency Simple counts of various attributes were determined both in actual figures and percentages. For example, various tables and figures were created to describe the frequencies of chosen variables among the various household heads. For instance. simple statistical frequencies were constructed to determine the importance and impacts of the landscape and cultural 97
attributes in the development of Ulundi. In doing so, the level of knowledge of household heads (hh) about the landscape and cultural features was also determined. This was supplemented by other statistical approaches such as cross tabulation and analysis of association. 4.3.2 Cross tabulation The data base was set initially using Microsoft Excel (Windows Xp). The data were then exported into the Statistical Package for the Social Sciences (SPSS) programme This software enables the determination of statistical cross tabulation as well as analysis of association. The key attributes in the data base were cross-tabulated to determine if any relationship existed between them. For instance, the relationship between gender and the level of education of household heads, their occupation and number of children were analysed. This statistical exercise is deemed important for the study, since it gives insight into the degree to which the variables are related both in strength and direction. Most of the variables that were cross-tabulated in this research were demographic in orientation and objective data on landscape and cultural attributes were obtained at focused interviews with open-ended questions. Establishing an objective perspective of the landscape and cultural attributes as land use was crucial in this research in order to buttress the views of household heads. In order to advance this objective, documented pieces of information were obtained from resourced individuals, relevant government institutions, representatives of civic organisations as well as other developmental stakeholders. 4.3.3 Analysis ofrelationsbips or association The Pearson's chi-square measure is used to test the level of dependence between variables. It is a most widely used measure of association (Otty, 1974). It is applied to situations in which either a single sample of items are categorised in two or more different ways or, equivalently, where two or more samples are classified according to the same attribute. In the course ofworking out the relational analyses, the degree ofassociation between variables was computed. • The relationship between occupation and education level ofhousehold heads. 98
- Page 65 and 66: a service, or solving a mutual prob
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attributes in the development <strong>of</strong> Ulundi. In doing so, the level <strong>of</strong> knowledge <strong>of</strong> household<br />
heads (hh) about the landscape and cultural features was also determined. This was<br />
supplemented by other statistical approaches such as cross tabulation and analysis <strong>of</strong><br />
association.<br />
4.3.2 Cross tabulation<br />
The data base was set initially using Micros<strong>of</strong>t Excel (Windows Xp). The data were then<br />
exported into the Statistical Package for the Social Sciences (SPSS) programme This<br />
s<strong>of</strong>tware enables the determination <strong>of</strong> statistical cross tabulation as well as analysis <strong>of</strong><br />
association. The key attributes in the data base were cross-tabulated to determine if any<br />
relationship existed between them. For instance, the relationship between gender and the<br />
level <strong>of</strong> education <strong>of</strong> household heads, their occupation and number <strong>of</strong> children were<br />
analysed. This statistical exercise is deemed important for the study, since it gives insight<br />
into the degree to which the variables are related both in strength and direction. Most <strong>of</strong> the<br />
variables that were cross-tabulated in this research were demographic in orientation and<br />
objective data on landscape and cultural attributes were obtained at focused interviews with<br />
open-ended questions. Establishing an objective perspective <strong>of</strong> the landscape and cultural<br />
attributes as land use was crucial in this research in order to buttress the views <strong>of</strong> household<br />
heads. In order to advance this objective, documented pieces <strong>of</strong> information were obtained<br />
from resourced individuals, relevant government institutions, representatives <strong>of</strong> civic<br />
organisations as well as other developmental stakeholders.<br />
4.3.3 Analysis <strong>of</strong>relationsbips or association<br />
The Pearson's chi-square measure is used to test the level <strong>of</strong> dependence between variables.<br />
It is a most widely used measure <strong>of</strong> association (Otty, 1974). It is applied to situations in<br />
which either a single sample <strong>of</strong> items are categorised in two or more different ways or,<br />
equivalently, where two or more samples are classified according to the same attribute. In the<br />
course <strong>of</strong>working out the relational analyses, the degree <strong>of</strong>association between variables was<br />
computed.<br />
• The relationship between occupation and education level <strong>of</strong>household heads.<br />
98
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