For example, in Table 1, the joint event representing rejected males contains 166 observations. Marginal events refer to the total number of observations for a category of a particular variable. Here, the marginal event for the category female is 245. We could create a multiway contingency table by further crosstabulating the above example with four academic departments, producing a three-way contingency table with a 2 x 2 x 4 structure. One way to display such a three-way table would be as five separate gender x decision tables, one for each of four departments.
Categorical data are often part of larger datasets that contain continuous variables.
For example, categorical variables such as a person's sex or race might be found in a dataset that also has continuous variables for IQ and height. There are also datasets that consist entirely of categorical variables. How you enter data depends on which kind of dataset you have. In a dataset with continuous variables, there is typically a row for each of the participants in your study. Each participant will have a data value for each column representing a variable.