From Method, select the Pearson correlation or the Spearman correlation.
For example, an engineer can use the Pearson correlation coefficient to determine whether increases in a facility's temperature are associated with decreases in the thickness of chocolate coating.
Use the Spearman correlation coefficient (also known as Spearman's rho) when the relationship between variables is not linear. The Spearman correlation measures the monotonic relationship between two continuous or ordinal variables. In a monotonic relationship, the variables tend to move in the same relative direction, but not necessarily at a constant rate. In a linear relationship, the variables move in the same direction at a constant rate. For more information, go to Linear, nonlinear, and monotonic relationships.
The Spearman correlation coefficient is often used to evaluate relationships with ordinal variables. If your data are continuous, Minitab ranks the raw data before performing the correlation.
For example, a manager ranks employees in the order they complete a test exercise. The manager can use the Spearman correlation coefficient to evaluate whether the employee's rank is related to the number of months they have been employed.
For more information, go to A comparison of the Pearson and Spearman correlation methods.