What do crosstabulations show for two binary or discrete variables?

Crosstabulations are an effective way to analyze the relationship between two binary or discrete variables by showing the frequency distribution of these variables in a tabular format. This means they provide a clear visual representation of how different categories or values of one variable correlate with those of another. By laying out the data in a grid, it becomes easy to see patterns, such as how many instances fall into each category combination, allowing for an understanding of how the two variables interact.

For instance, if one variable is whether individuals own a car (yes/no), and the second variable is whether they have a driver's license (yes/no), a crosstabulation would show the distribution of individuals across those categories, revealing the relationships between car ownership and having a driver’s license. This helps in making informed inferences based on the distribution of values observed.

While trends, comparative analysis, and average rates may also provide insights, they do not specifically encapsulate the primary capability of crosstabulations, which is to display the distribution of values for the associated categories of the variables in question.