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are spurious, where two or more variables are incorrectly assumed to correlate with one another. Data compared within categories may also be unimportant. For example, figuring out whether proportionally more Canadians have first names starting with the letter 'a' than non-Canadians would be a fairly arbitrary, random exercise. However, the use of comparing nominal data with a frequency distribution to associate gender and political affiliation would be more effective since a correlation between the counts of a particular party affiliation would

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