Cross-tabulation
T tests can be used to determine whether there are significant differences
between undergraduate and graduate students or between face-to-face and
online instruction.
However, these procedures would be conducted separately by education
level and then by instructional preference. This would not reveal an
association between the two variables.
Correlation analysis is typically used to measure the association between
variables, but correlation can only be used with quantitative variables.
In order to compare categorical variables, the data can be summarized into a
table, which lists the options for one variable as the rows and the options for
the other variable as the columns. This is called a crosstab because two
variables are being tabulated at the same time, and the frequency, or the
percentage of individuals in each subcategory, are being counted.
Cross-tabulation of the two qualitative (nominal) variables:
In this example, instructional preferences are listed as the rows and
education levels are listed as the columns.
The next step is to obtain the frequencies for each category, which can be
done using statistical software, especially for a very large sample.
Although a crosstab is a helpful descriptive statistic, it is also important to be
able to determine if there is an association between the two variables and
whether or not it is statistically significant.