This is called an "inverse" relationship.
A positive correlation coefficient means that as the value of one variable increases, the value of the other variable increases; as one decreases the other decreases. A negative correlation coefficient indicates that as one variable increases, the other decreases, and vice-versa.
The dependent variable has an inverse linear relationship with the dependent variable. When the dependent increases, the independent decreases, and conversely.
decreases
A correlation is the relationship between two or more variables. Correlations are described as either weak or strong, and positive or negative. There can be a perfect correlation between variables, or no correlation between variables. It is important to determine the correlation between variables in order to know if and how closely changes in one variable are reflected by changes in another variable. This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction. -1 ≤ r ≤ +1 if r= +1 or -1, there is a perfect correlation if r= 0 there is no correlation between the variables. a value closer to + or - 1 demonstrates a strong correlation, while a value closer to 0 demonstrates a weak correlation. a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases. However, it is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis. Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.
No correlation.
One variable always decreases as the other decreases. One variable always increases as the other increases.
as one variable increases the other variable decreases
I think you're referring to Correlation. This means the relationship between two variables. There can be a positive correlation, where as one variable increases, so does the other. There can be a negative correlation, where as one variable increases, the other decreases. Lastly, there can be no correlation, where there is no relationship between the two variables.
decreases
A positive correlation coefficient means that as the value of one variable increases, the value of the other variable increases; as one decreases the other decreases. A negative correlation coefficient indicates that as one variable increases, the other decreases, and vice-versa.
Depends on the relationship between the independent and dependent variables.
It depends on the relationship, if any, between the independent and dependent variables.
An inverse proportion between two variables is when the value of one variable increases, the other decreases. Mathematically, this is shown as: x = k / yn where x and y are the two variables, and k and n are constants.
The dependent variable has an inverse linear relationship with the dependent variable. When the dependent increases, the independent decreases, and conversely.
A negative correlation occurs when, as one variable increases, the other variable decreases. Some variables that might have a negative correlation would be: indoor heating use and temperature outside. As the temperature outside decreases, the amount of heating used will increase.
dependent variable improves (or increases) as independent variable increases
It means that they are directly proportional to each other. As one variable increases, the other variable increases/decreases at a constant rate. The constant rate is determined by the gradiant of the straight line.