What is a unique characteristic of a frequency polygon compared to a histogram?

A frequency polygon is distinguished from a histogram primarily by its method of data representation. In a frequency polygon, the midpoints of the bins are plotted as points on a graph and these points are then connected with straight lines. This connection creates a continuous line that represents the distribution of the data, which allows for easy comparison between different data sets or different distributions.

Unlike a histogram, which uses bars to represent the frequency of data in different intervals, the frequency polygon provides a clearer view of trends and patterns across the distribution. This is particularly useful in identifying the shape of the data distribution, such as whether it is normal, skewed, or has multiple modes.

While other options mention colors, representation methods, and discrete data, these attributes are not defining characteristics of frequency polygons compared to histograms. The unique aspect of connecting points instead emphasizes the continuous nature of the data visualization in a frequency polygon, making it easy to analyze and interpret the overall shape of the data distribution.