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Russel-Research-Method-in-Anthropology

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456 Chapter 16<br />

TABLE 16.2<br />

Profile Matrix for Two Cases and Six Variables<br />

Variable<br />

Spent on Spent on Years How How many<br />

Spent on meat, fish, other <strong>in</strong> many <strong>in</strong> under 15<br />

Respondent vegetables or poultry foods Age school Married house <strong>in</strong> house<br />

1 330 420 215 34 8 1 4 2<br />

2 195 250 300 60 6 0 7 3<br />

Proximity Matrices<br />

Profile matrices conta<strong>in</strong> measurements of variables for a set of items. Proximity<br />

matrices conta<strong>in</strong> measurements of relations, or proximities, between<br />

items. If the measurements <strong>in</strong> a proximity matrix tell how close th<strong>in</strong>gs are to<br />

each other then you have a similarity matrix. If the measurements <strong>in</strong> a proximity<br />

matrix tell how far apart th<strong>in</strong>gs are from each other, then you have a<br />

dissimilarity matrix.<br />

If you’ve ever read one of those tables of distances between cities that you<br />

see on road maps, you’ve had experience with a dissimilarity matrix. The bigger<br />

the number <strong>in</strong> the cells, the more ‘‘dissimilar’’ two cities are. In this case,<br />

dissimilarity means that the larger the number <strong>in</strong> any cell, the further apart<br />

two cities are on the map.<br />

If you’ve had a course <strong>in</strong> statistics and seen a correlation matrix, then<br />

you’ve had experience with a similarity matrix. The bigger the number <strong>in</strong> each<br />

cell—the higher the correlation—the more alike two th<strong>in</strong>gs are.<br />

Figure 16.1(b) shows a similarity matrix of variables. Imag<strong>in</strong>e the list of<br />

variable names stretch<strong>in</strong>g several feet to the right, off the right-hand marg<strong>in</strong><br />

of the page, and several feet down, off the lower marg<strong>in</strong>. That is what would<br />

happen if you had, say, 100 variables about each of your respondents. For each<br />

and every pair of variables <strong>in</strong> the matrix of data, you could ask: Are these<br />

variables related?<br />

We’ll need the concept of a proximity matrix when we get to multivariate<br />

analysis <strong>in</strong> chapter 21.<br />

Present<strong>in</strong>g Results <strong>in</strong> Matrices and Tables<br />

An important part of all analysis, qualitative and quantitative, is the production<br />

of visual displays. Lay<strong>in</strong>g out your data <strong>in</strong> table or matrix form and draw<strong>in</strong>g<br />

your theories out <strong>in</strong> the form of a flow chart or map helps you understand

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