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A scatter diagram effectively displays the relationship between two quantitative variables, with one variable plotted on the horizontal axis and the other on the vertical axis. In this format, the dependent variable is represented on the vertical axis, allowing viewers to observe how changes in the independent variable affect the dependent one.

This visualization is crucial in identifying patterns, correlations, or trends between the two variables, providing insights into their relationship. For instance, if the points cluster together in a certain pattern, this may indicate a strong correlation, while a more scattered arrangement could suggest a weak or no correlation.

Other options such as histograms, box plots, and line charts serve different purposes. A histogram is used for displaying the distribution of a single variable, box plots summarize the distribution of data based on a five-number summary and identify potential outliers, while line charts can show trends over time but are not typically used to analyze the relationship between two distinct quantitative variables in the same way scatter diagrams do. Thus, the scatter diagram is the most suitable choice for illustrating the relationship between the two variables in question.