Which chart would you use to display the correlation of measures?

A scatter plot is the ideal choice for displaying the correlation of measures because it represents two quantitative variables on a two-dimensional graph. Each point on the scatter plot corresponds to a specific pairing of values from the two measures, allowing viewers to visually assess the relationship between them.

In a scatter plot, a clustering of points can indicate a positive, negative, or no correlation. For example, if the points form a upward trend, it suggests a positive correlation; if they trend downward, it indicates a negative correlation. This visual representation aids in identifying patterns, strengths of relationships, and potential outliers between the measures, which is crucial for data analysis.

Other chart types like a line chart, tree map, and bar chart do not effectively convey this type of correlation. A line chart is generally used to show trends over time, making it unsuitable for assessing relationships between two independent measures. Tree maps focus on hierarchical data representation and do not facilitate the comparison of two measures in correlation. Bar charts, while useful for comparing quantities across categories, lack the ability to depict relationships in two-variable scenarios. Thus, the scatter plot stands out as the most effective option for illustrating the correlation of measures.