You can use the covariance to determine the direction of a linear relationship between two variables as follows:

If both variables tend to increase or decrease together, the coefficient is positive.

If one variable tends to increase as the other decreases, the coefficient is negative.

Covariance is similar to correlation but when the covariance is calculated, the data are not standardized. Therefore, the covariance is expressed in units that vary with the data and is not converted to a standardized scale of −1 to +1. Because the data are not standardized, you cannot use the covariance statistic to assess the strength of a linear relationship. To assess the strength of a relationship between two variables using a standardized scale of −1 to +1, use correlation.

In the covariance matrix in the output, the off-diagonal elements contain the covariances of each pair of variables. The diagonal elements of the covariance matrix contain the variances of each variable. The variance measures how much the data are scattered about the mean. The variance is equal to the square of the standard deviation.

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