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You must have come across tabular layouts of information many times. Just like the one you see in a report card or the ingredients behind a chips packet and so on. You can see two-dimensional or even three-dimensional tables spreading out such information. In short, cross-tabulation states the relationship between variables.
Talking in survey terms, cross-tabulation refers to the number of respondents having the mentioned characters as table cells. And cross-tabulation analysis is nothing but studying the tabulated information to derive conclusions out of it. Cross-tabulation analysis also uses terms like banners, stubs, chi-square statistics and expected values.
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The above image shows a report of frequency of visits by people further bifurcated by age group. Cross-tabulation analysis will bring out a conclusion that people form the age group “Under 18” have comparatively more percentages of visiting in every category on the left hand-side.
The chart can be put into visual representation as:
Surveys can be cross tabulated only when you have categorized variables or data. Meaning, your data needs to be able to divide into groups having something in common. Let us look at some areas where you can use cross-tabulation analysis for your survey:
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