Which method would be most effective in identifying the relationship strength between two continuous variables?

The correlation coefficient quantifies the strength and direction of a linear relationship between two continuous variables. Values close to +1 or -1 indicate a strong positive or negative relationship, respectively, while values near 0 suggest a weak or no linear relationship. Calculating the correlation coefficient is particularly useful in EDA as it helps analysts understand potential dependencies between variables, which can influence modeling and feature selection decisions. This metric is essential for identifying patterns that might not be evident through simple visualization. Option A is incorrect as histograms display frequency distribution, not relationships. Option B is incorrect because box plots are used to display distribution and identify outliers, not relationships. Option D is incorrect as pie charts are used for categorical data proportions, not continuous variable relationships. Option E is incorrect because line plots are for trends over time, not relationship strength between two variables.