Which chart type is appropriate for displaying changes in data over time?

A line graph is the most suitable chart type for displaying changes in data over time because it effectively visualizes trends and patterns by connecting individual data points with a continuous line. This format allows viewers to easily observe fluctuations, such as increases or decreases in values, over a specified period.

The structure of a line graph typically involves time placed on one axis—usually the horizontal axis—while the variable being measured is represented on the other axis, allowing for a clear chronological understanding of the data's progress. It helps in identifying trends at a glance, which is essential for time-series analysis.

In contrast, other chart types like histograms, heatmaps, and box plots serve different purposes. Histograms are better suited for displaying the distribution of a dataset, showing how data values are distributed across different intervals. Heatmaps are useful for visualizing data density and patterns across two dimensions, but not for showing explicit changes over time. Box plots summarize a dataset's distribution and its quartiles, focusing on statistical summaries rather than on the progression of data points across time periods. Thus, while these alternatives have their own unique strengths, they do not effectively represent temporal changes as well as a line graph does.