What type of data is appropriate for a line graph?

A line graph is particularly well-suited for displaying continuous data, which represents measurable quantities that can take on an infinite number of values within a range. Continuous data includes variables such as time, temperature, or height, where any value is possible, and can be represented with great accuracy on a graph. The primary purpose of a line graph is to illustrate trends over time or relationships between variables, making it a valuable tool for visualizing continuous data.

In contrast, categorical data refers to non-numeric groups or categories that do not have inherent numerical meaning. Qualitative data describes characteristics or attributes that cannot be quantified in numbers, further differentiating it from the continuous data suitable for a line graph. Interval data, while numeric, is used to represent values with known distances between them, but it lacks a true zero point, making it less ideal for a line graph compared to the broader set of continuous data types. Thus, the use of continuous data in a line graph facilitates an accurate representation of trends, making it the correct choice for this question.