Which criteria could a pivot table be applied to?

A pivot table is a powerful tool used in data analysis to summarize, organize, and analyze large datasets. The key to effectively using a pivot table lies in choosing the right criteria that allows meaningful aggregation and comparison of information.

Using assignment scores as a criterion for a pivot table is particularly effective because it allows for quantitative analysis. With scores, you can compute various statistical measures such as averages, totals, counts, or even percentages. You can group the data based on different categories like student names or assignment dates and easily visualize how scores differ across these categories, making it ideal for performance tracking.

In contrast, while student names, assignment dates, and shared collaborators provide categorical data that can also be analyzed in a pivot table, they do not lend themselves to numerical calculations in the same way that assignment scores do. Using categorical data typically results in either counts or grouping, but it does not facilitate more complex operations like averaging or finding maximums directly without additional numerical values to analyze. Thus, the nature of assignment scores as numerical data makes it a suitable choice for application within a pivot table.