User:RosebellaCapio/sandbox

In statistics, there is a negative relationship or inverse relationship between two variables if higher values of one variable tend to be associated with lower values of the other. A negative relationship between two variables usually implies that the correlation between them is negative, or—what is in some contexts equivalent— that the slope in a corresponding graph is negative. A negative correlation between variables is also called anticorrelation or inverse correlation. The correlation coefficient, which is a number between 0 and 1, determines whether two variables have a positive or negative relationship, that is, the correlation coefficient talks of the strength of the relationship between the variables. If the correlation coefficient is close to -1 the two variables are highly negatively related and highly positively related if the coefficient is close to +1.

An example would be a negative cross-sectional relationship between illness and vaccination, if it is observed that where the incidence of one is higher than average, the incidence of the other tends to be lower than average. Similarly, there would be a negative temporal relationship between illness and vaccination if it is observed in one location that times with a higher-than-average incidence of one tend to coincide with a lower-than-average incidence of the other.

In finance, an inverse correlation between the returns on two different assets enhances the risk-reduction effect of diversifying by holding them both in the same portfolio.

A scatter plot can be used to give a visual representation of how the variables are related, whether positively or negatively. For example, if higher values of GPAs collected from a sample of 100 students tend to be associated with lower values of the ages of the students, it can be said that GPA and ages of the students are negatively related.

RosebellaCapio (talk) 06:47, 19 April 2018 (UTC)