Data in tabular form are ubiquitous in the social sciences. Cross-tabulations are used by criminologists, political scientists, archaeologists, sociologists, biologists, linguistics, to cite a few, as a convenient way of reporting and summarising data. However, tabular data can be thought of as being more than just summaries. Many patterns can be indeed embedded in such data, and bringing those patterns to the fore can provide many interesting insights.
From the position of the points representing the row and column categories, we can see that as the town size increases (moving from left to right along the horizontal line) the feeling of safety after dark worsens. For both genders, the smallest town size goes hand in hand (i.e., is close in space on the chart) to the highest level of perceived safety. The lowest feeling of safety is associated to larger town sizes (500,000-1,000,000 and 1,000,000 plus). It is worth noting that women start feeling unsafe (‘bit unsafe’ category) in town of size 100,000-500,000 where men feel ‘fairly safe’ instead. Overall, it is apparent how the analysis can provide insights into the data and help revealing hidden patterns.
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