The usage note, Tests of Independence Using Two-Way Contingency Tables in SPSS describes how to use SPSS to conduct this test. If you are using a dataset that contains more than two variables, you can conduct a multiway analysis for independence among your variables. For instance, you might want to know if a person's gender, their choice of department, and acceptance status in the graduate school are independent of each other. Or you might want to test the hypothesis that gender is independent of department and acceptance decision, while acknowledging that there is a relationship between department and acceptance decision. If your data do not meet these conditions, see a consultant to determine if you should be using a more appropriate analysis.
Observations are probabilistically independent of each other .
Each categorical entry of an observation is independent of other observations in the dataset. This results in a single categorical entry for every unit of observation, whether it be an individual participant, a dyad such as a married couple, or a group such as a student organization. Each observation must represent one and only one joint event . An example of such observations is given in the above table in which applicants are categorized on the basis of their sex and whether they were accepted or rejected. Each applicant must be classified as representing exactly one of the four possible joint events in the above contingency table.