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Covariance vs Correlation: Difference, Formula, Examples and Comparison Introduction Covariance and correlation are two important statistical concepts used to measure the relationship between two variables. They help answer questions such as: Does advertising increase sales? Does study time affect exam marks? Are height and weight related? Although both measure relationships between variables, covariance and correlation have important differences in interpretation and usage. What is Covariance? Covariance measures the direction in which two variables change together. $$ Cov(X,Y)= \frac{\sum(X_i-\bar X)(Y_i-\bar Y)} {n} $$ Interpretation of Covariance Positive Covariance When: $$ Cov(X,Y)>0 $$ Both variables increase or decrease together. Negative Covariance $$ Cov(X,Y) One variable increases while the other decreases. Zero Covariance $$ Cov(X,Y)=0 $$ There is no linear relationship between v...