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Russel-Research-Method-in-Anthropology

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682 Chapter 21<br />

TABLE 21.25<br />

Matrix of Association among Four Variables<br />

A B C D<br />

A X 0.5 0.8 0.3<br />

B X 0.4 0.64<br />

C X 0.35<br />

D<br />

X<br />

.8<br />

A<br />

C<br />

a.<br />

.8<br />

.4<br />

A<br />

.5<br />

B<br />

C<br />

.35<br />

b.<br />

.4<br />

.3<br />

.5<br />

.65<br />

B<br />

D<br />

Figure 21.3. Two-dimensional plot of the relation among three variables (a) and<br />

among four variables (b).<br />

With just three variables, it is easy to plot these distances <strong>in</strong> proper proportion<br />

to one another. For example, the physical distance between B and C is<br />

twice that of A and C <strong>in</strong> figure 21.3a. In fact, figure 21.3a conta<strong>in</strong>s precisely<br />

the same <strong>in</strong>formation as the <strong>in</strong>side box of table 21.25, but <strong>in</strong> graphic form.<br />

With four variables, th<strong>in</strong>gs get considerably more complicated. With four<br />

variables, there are six relations to cope with. These relations are shown <strong>in</strong> the<br />

large box of table 21.25. Only one two-dimensional graph (apart from rotations<br />

and enlargements) can represent the relative distances among the six<br />

relations <strong>in</strong> table 21.25. The graph is shown <strong>in</strong> figure 21.3b.<br />

Figure 21.3b is a two-dimensional graph of six relations <strong>in</strong> almost proper<br />

proportions. When we have only two dimensions to work with, it is often<br />

impossible to achieve perfect proportionality <strong>in</strong> a graph of six relations. One<br />

way out of this is to depict the six relations <strong>in</strong> table 21.25 <strong>in</strong> three dimensions,

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