The significance test performed in Crosstabs compares Column Proportions using Z tests.
In general, tests for statistical significance are used to estimate the probability that a relationship observed in the data occurred only by chance or the probability that the variables are really unrelated in the data.
The Column Proportion test looks at the rows of a table independently and compares pairs of columns, testing whether the proportions of respondents in one column is significantly different from the proportions in the other column. The proportion is the count in the cell divided by the base for the column.
In Report Example 3, Step 7, an alpha value of .05 was selected and results are shown in the following partial graphic of the Significance Testing Results window. Results shown in the graphic are based on two sided test with the selected significance level 0.05.
In the example above, for each significant pair, the key of the category with the smaller column proportion appears in the subscript of the cell with larger column proportion.
For example, if a cell in column B contains the subscript A, this means that the column proportion of the value in cell B is significantly greater than the column proportion for value in cell A.
See also:
Statistical Testing in Crosstabs