If Linear Correlation test is selected, the correlation test is calculated. For this calculation there must be at least 3 or more observations. This calculation calculates if there is a significant correlation between the two compared columns. When there is a relationship (correlation) between the two variables this relationship can be calculated. See Regression.
The correlation does not work in DOE mode because there are no pairs in this mode.

Interpretation

The smaller the p value is the more likely there is a significant correlation between the variables.

Always check the correlation graph.

Develve uses the commonly accepted value of p < 0.05 for significance.

For a good power (0.8 in Develve) the amount of observations must be bigger than the minimum calculated.

n = Amount of pairs
= correlation
= significance 0.05 in the sample size calculation (2 sided)
= Power 0.80 in the sample size calculation

Example

Between data-sets A and D is a correlation (Row Correl p <0.05), and the sample size is big enough.
Between data-sets A and C is no significant correlation and the sample size is to small.

To see what the relation between the data sets check the Regression result.

Colors of the cells

Green

No significant difference

Yellow

Significant difference

Example

To use the Multiple Correlation test "Menu: Tools=> Multiple Correlation". Then select the data-sets to test. Only between data-sets A and D is a correlation (Row Correl p <0.05). When clicking on Graph the a matrix of correlation graphs will be displayed. In graph it is visible that there is a correlation between A and D.