All of the statistical tests are based on the assumption that the samples being compared are independent of each other. However, in hierarchical data, there is normally a relationship between the lower levels and the higher levels, which means that cases at the lower level are not independent of each other. For example, you would not expect the voting patterns of the members of a household to be totally independent of each other, nor would you expect the various journeys or shopping trips made by an individual to be unrelated to each other. These relationships mean that the underlying assumptions required for the statistical tests are almost never satisfied when you run the tests on lower level data.

Therefore, when you are working with hierarchical data using the hierarchical view, UNICOM Intelligence Professional changes the specified table level (a warning message is not provided) if any of the variables included in the table are from a lower level.

If there is no relationship between the lower levels and higher levels, use the TestAtLowerLevels statistics property to support statistical testing at lower levels.

For example: