Michael Fischer Reading and Analyzing Cross-cultural Data from tables Considerations:

1)

Look at the marginal totals for the row category and column category.

These give the internal distribution of societies across these categories. This is useful to contextualise later thoughts. For example, looking at the table below we can see that 117 of 186 societies in the sample have the wife residing with the husband’s group after marriage. We would therefore expect to see some of our larger cross-comparison totals to be in the cells in this column. Likewise for Bride-price or wealth. Indeed the cell which includes both of these values is the largest in the table, which we would expect.

2)

“Read” some of the results by translating the totals and cells for the table

into expressions in your native language, e.g. English, French, Japanese etc. You must read the table before you can say much about it.

3)

Now look at the distribution of values down the columns and across the

rows. Compare rows. Compare columns. Do values seem to be evenly distributed (accounting for the differences in marginal totals). Are their any inversions (eg larger values to the left for Bride-price, to the right for Dowry).

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4)

The following table (which you get by checking the “Expected” box on the

opening screen, helps to access the distribution. It relays how many more or less societies we find in a cell than we would expect if the two categories did not interact or relate to each other.

5)

Here we have removed columns to make the relationship more explicit. I

did this using the merge facility, keeping the three most divergent row and column values.

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6) Another Example...

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