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Feature Description
Pearson Correlation Coefficient (r) measures the linear relationship between two continuous variables. It ranges from -1 to 1, where -1 indicates a perfect negative linear relationship, 1 indicates a perfect positive linear relationship, and 0 indicates no linear relationship. Pearson's correlation assumes that the data are normally distributed and have a linear relationship with homoscedasticity (constant variance of the error terms).
Spearman's Rank Correlation Coefficient (ρ or rs) measures the strength and direction of the monotonic relationship between two variables, which can be ordinal, interval, or continuous. It is based on the ranks of the data rather than the raw data itself and ranges from -1 to 1, with the same interpretation as Pearson's correlation. Spearman's correlation does not assume normal distribution or linearity and is used when data are not normally distributed or when the relationship is not linear.
Use Case
Pearson Correlation Coefficient and Spearman's Rank Correlation Coefficient are both measures of the strength and direction of the relationship between two variables, but they differ in their assumptions and applicability.
Benefits
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Priority
High
Record