Similarly, we might expect there to be a relationship between a person's annual salary and the amount of time they spend each day worrying about paying their bills. A negative, or inverse, relationship. On the other hand, we might not expect a relationship between a person's shoe size and the number of ties they own, or between the number of potato chips they eat per week and the number of digits on their car license plates. Correlations and scatterplots let us investigate the relationship between two quantitative variables. Correlation A correlation measures the direction and strength of the linear relationship between two quantitative variables.
Life is just too complicated and our measures are far from perfect.
Alternatively, you could say that lower scores on X are associated with higher scores on Y. 2. This is best indicated by squaring a correlation. The correlation squared indicates the proportion of variance that two variables share. A correlation measures the degree to which the relationship between two quantitative variables can be approximated by a straight line . Make sure that you always check a scatterplot to avoid reporting a zero correlation when there actually is a curvilinear relationship.