What is the main purpose of a scatter plot?

A scatter plot is specifically designed to illustrate the relationship between two quantitative variables. Each point on the scatter plot represents an observation in the dataset, with one variable plotted along the x-axis and the other along the y-axis. This visual representation allows for the immediate identification of patterns, correlations, or trends that may exist between the variables. For example, if there's a positive correlation, points will trend upward from left to right, indicating that as one variable increases, the other does as well.

This clarity of relationships makes scatter plots valuable in various fields, particularly in business and social sciences, where understanding how different factors interact is crucial for analysis and decision-making. Other types of visualizations serve different purposes; for example, frequency distributions focus on how often data points occur, while highlighting outliers is typically done in box plots or other specialized graphs. Lastly, while scatter plots can indicate trends, they do not specifically aim to display changes over time, which is typically the domain of line graphs.