Which type of visualization is used to chart variations in a dataset over a specific time period?

A line graph is a powerful visualization tool specifically designed to demonstrate trends and variations in a dataset over time. The x-axis typically represents the time intervals—such as days, months, or years—while the y-axis shows the values of the data points. This format allows viewers to easily see fluctuations, peaks, and troughs in the data, making it ideal for identifying trends over a specific duration.

In contexts such as tracking sales figures, stock prices, or any other time-dependent variable, the line graph's continuous flow can effectively convey how a dataset evolves, providing valuable insights into patterns and potential future performance. This makes it an essential choice for any analysis that requires an understanding of changes over time.

Other options, while useful for different types of data representation, do not serve the same purpose. For example, a heatmap is effective for showing the intensity of data across two variables but does not indicate changes over time. A scatter plot helps illustrate the relationship between two numerical variables and does not focus explicitly on temporal trends. A funnel chart visualizes stages in a process, such as sales conversions, rather than displaying data changes over a time period. Hence, the line graph stands out as the most appropriate option for illustrating time-based variations.