What is the purpose of a scatter plot in data analysis?

A scatter plot is a graphical representation that demonstrates the relationship between two quantitative variables. Each point on the scatter plot represents an observation from the data set, with the position of the point determined by the values of the two variables being measured. This visualization allows analysts to identify patterns, trends, or correlations, such as whether an increase in one variable corresponds to an increase or decrease in the other variable.

For example, in a business context, a scatter plot could be used to evaluate the relationship between advertising expenditure and sales revenue, helping to determine if higher spending correlates with increased sales performance. This utility makes scatter plots particularly valuable in fields such as economics, psychology, and health sciences, where understanding the interactions between variables is crucial for drawing conclusions and making predictions.

In contrast, other types of graphs serve different purposes: some focus on single-variable distributions or categorize data, while others summarize central tendency measures without illustrating relationships between two variables. Hence, the primary function of a scatter plot firmly lies in its ability to visualize relationships between pairs of quantitative data, marking it as the correct answer.