What type of graph is commonly used to represent the relationship between two quantitative variables?

A scatter diagram is the ideal choice for representing the relationship between two quantitative variables. This type of graph plots individual data points on a Cartesian plane, with one variable along the x-axis and the other along the y-axis. This visualization allows for an immediate assessment of correlation, trends, or patterns that exist between the two variables being studied.

In this context, the scatter diagram excels because it can effectively demonstrate how one variable may change in relation to another, showcasing potential relationships such as positive correlation, negative correlation, or no correlation. The spatial distribution of the points helps identify clusters, outliers, and the overall pathway of the relationship, which is essential in many analytical scenarios, particularly in mass appraisal where understanding relationships between property characteristics is crucial.

Other graph types, while useful for different purposes, do not serve the same specific function for two quantitative variables. For example, pie charts represent parts of a whole, making them unsuitable for showcasing two-variable relationships. Bar graphs depict categorical data rather than continuous measurements, and histograms are specific to frequency distributions of a single quantitative variable. Thus, the scatter diagram stands out as the precise tool for examining correlations between two quantitative factors in data analysis.