A data analyst has created a line chart to display the quarterly sales performance of four different product lines over the last three years. Each product line is represented by a uniquely colored line. During a review, a manager notes that it is impossible to determine which product line corresponds to which colored line. To resolve this ambiguity and make the chart interpretable, which design element must the analyst add?
The correct answer is a legend. A legend serves as a key for a chart, identifying what the different colors, patterns, or symbols used in the visualization represent. In this scenario, with four different product lines each shown as a uniquely colored line, a legend is essential to connect each color to its corresponding product line, making the chart understandable.
Data labels are incorrect because they display the specific value of individual data points on a chart. While they add precision, they do not solve the core problem of identifying which product line each colored line represents.
A title is incorrect because it describes the overall purpose and content of the chart (e.g., 'Quarterly Sales by Product Line') but does not explain the individual elements within it.
Gridlines are incorrect as they are background lines that help the viewer's eye align data points with the values on an axis. They provide a frame of reference for values but do not help in distinguishing between data categories.
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