First input array containing numerical values.
Second input array containing numerical values.
result: A double representing the computed correlation coefficient.
Notes: - The function enforces that both input arrays must have the same length. - Pearson correlation is computed using the formula: (Σ (x_i - mean_x) * (y_i - mean_y)) / sqrt(Σ (x_i - mean_x)^2 * Σ (y_i - mean_y)^2) - If both input arrays have constant values, the denominator may be zero, resulting in a division-by-zero scenario. - Assumes that input arrays are non-empty; otherwise, an invalid result may occur. - Correlation does not imply causation. Consider additional statistical tests to determine dependencies. - If working with time series data, ensure that the relationship is stable over time before making predictive assumptions.
Summary: Computes the Pearson correlation coefficient between two input arrays. The correlation coefficient measures the linear relationship between two datasets, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation).