In probability theory and statistics, covariance is a measure of how much two random variables change together.
Negative Covariance - In the opposite case, when the greater values of one variable mainly correspond to the lesser values of the other, i.e., the variables tend to show opposite behavior, the covariance is negative. If a sealed balloon is squashed in one dimension then it will expand in the other two. [See Conjugate Variables]
Positive Covariance - If the greater values of one variable mainly correspond with the greater values of the other variable, and the same holds for the lesser values, i.e., the variables tend to show similar behavior, the covariance is positive. For example, as a balloon is blown up it gets larger in all dimensions.
The sign of the covariance therefore shows the tendency in the linear relationship between the variables. The magnitude of the covariance is not easy to interpret. The normalized version of the covariance, the correlation coefficient, however, shows by its magnitude the strength of the linear relation. Wikipedia, Covariance
See comment on this principle: Negative Covariance in Russell and Keely.
See Also
Conjugate Variables 3.13 - Reciprocals and Proportions of Motions and Substance 6.1 - Reciprocal Radiations 7.3 - Law of Love - Reciprocal Interchange of State on Multiple Subdivisions 7.6 - Reciprocal Disintegration and Creation 7.7 - Reciprocal States of Matter and Energy Figure 12.13 - Some Multi-Dimensional as Inverse and Direct Reciprocal Relationships Figure 13.14 - Equilibrium as Reciprocal Forces Figure 3.10 - Temperature Accumulates in the North and Cools in the South Reciprocally reciprocal Rotation and Revolution are Reciprocals