Which of the following is a common use of line graphs in statistical analysis?

Line graphs are particularly useful in illustrating trends over time or relationships between variables, making them ideal for representing interaction effects. When analyzing data that involves changes across different conditions or over time, line graphs can show how one variable influences another or how multiple variables interact. The slopes and intersections of lines can effectively convey these dynamic relationships, allowing the viewer to easily identify patterns and trends.

In contrast, other choices do not accurately reflect the primary purpose of line graphs. For instance, pie charts are best represented using circular graphs rather than line graphs, as line graphs do not convey proportions well. Similarly, while line graphs can show relationships involving multiple independent variables, they primarily focus on the dependent variable's trends rather than representing those independent variables directly. Lastly, tracking individual participant scores is typically better suited to other types of graphs or tables, as line graphs aggregate data trends rather than highlighting individual measures. Therefore, the choice highlighting interaction effects based on trends aligns perfectly with the strength of line graphs in statistical analysis.