What distinguishes a scatter plot from a dot plot?

The distinction between a scatter plot and a dot plot primarily revolves around their representation of data points and the structure of their axes. A scatter plot is designed to show the relationship between two variables, which is why it has two axes. Each point on the scatter plot represents a pair of values corresponding to the two variables being measured, allowing analysts to observe correlations or patterns.

In contrast, a dot plot primarily shows the frequency of single data points over a single axis, representing one variable. While it can illustrate data distribution and is effective in visualizing smaller datasets, it does not delve into the relationships between two different variables.

The claim that a scatter plot "has a single dot for each set of data" specifies the uniqueness of points representing paired observations in a scatter plot, while emphasizing the nature of representation rather than the differences between the two plot types. This is key because it highlights how scatter plots focus on relationships between multiple dimensions, whereas dot plots typically focus on the distribution or count of data points along a single axis.