An **inverse** relationship is one in which the value of one parameter tends to decrease as the value of the other parameter of the relationship increases. However, an **inverse** relationship can also exist between x and y variables instead of functions. An inverse relationship is one in which the value of one parameter tends to decrease as the value of the other parameter of the relationship increases. However, an inverse relationship can also exist between the variables x and y instead of functions.

A typical example of this type of relationship is between interest rates and consumer spending. Even if two variables have a very strong inverse correlation, this result by itself does not prove a cause and effect relationship between the two. If one increases, the other decreases. This is why inverse relationships are downward curves that become shallower the further you go along them.

## What is the opposite of an inverse relationship?

It means that variables can show an inverse correlation during some periods and a positive correlation during others. To form the inverse of the conditional statement, you have to take the negation of both the hypothesis and the conclusion. Positive correlation describes the relationship between two variables that change together, while inverse correlation describes the relationship between two variables that change in opposite directions. The following graph illustrates a strong inverse correlation between two sets of data points plotted on the graph.

In an inverse relationship, an increase in one quantity leads to a corresponding decrease in the other. An inverse correlation, also known as a negative correlation, is an opposite relationship between two variables, so that when the value of one variable is high, the value of the other variable is likely to be low.