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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.
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