Cross tabulation data (cross-tabs)

During the process of data analysis, researchers will often choose to have the statistical results compiled into a cross tabulation or cross-tab, which in simple terms, is a table containing columns and rows of information.

The tables are often tabbed out against the individual questions asked, with the results split by the total audience response and any other form of cross breaks required for the analysis, allowing for the observation of data changes across a number of variables. In addition to the total base of respondents, common variables include demographics, awareness levels of the product/brand concerned, and other key factors determined by the questioning (e.g. business-class travellers in an airline survey or regular shoppers in a retail study).

Cross-tabs are in general the most commonly used form of data presentation, allowing researchers to quickly and clearly identify the results of the research conducted and pick out any key themes or stories. This clearer form of data is often preferred as it allows for the observation of complex sets of data, with insights perhaps being overlooked if more complicated forms of analysis are utilised. Therefore, the main benefit of cross tabulation data is its simplicity, with additional breakdowns of data creating very little confusion or complication by sitting in an additional column, alongside the rest of the data, for easy comparison.

Within a cross tabulation the data is often represented as percentage along with the number of responses to that particular question choice. For questions that involve a scale, for instance; strongly agree, agree, neutral, disagree and strongly disagree, it can often be the case that the cross-tab will include a summary of the response such as Net agree and Net disagree, providing a total sum of the positive or negative responses. Additionally a cross-tab may include a mean score and a standard deviation for each question in the survey.

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Cross tabulation data (cross-tabs)