The discussion clarifies the distinction between auto-correlation and cross-correlation, emphasizing that the primary difference lies in normalization. Auto-correlation relates to the correlation of a variable with itself over time, while cross-correlation involves the correlation between two different variables. Both types of correlation are derived from their respective co-variances, normalized by the square root of the product of the variances of the individual variables, ensuring that correlation values remain between 0 and 1.
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