Measure the relationship between two numeric data variables by calculating the correlation coefficient.
Details
The statistical model used to test for the correlation between two variables of a given dataset. The Correlation Coefficient (r) ranges from -1.0 to +1.0. The closer r is to either of these values, the more closely the two variables are related. If r is closer to 0, it means there is little or no relationship between the two variables.
[1] denoted in the output below refers to the test statistic. In this example, r is closer to 1 than it is to 0 signalling a strong correlation.
Output
Parameters
| Variable name | Required | Constraints | Description |
|---|---|---|---|
| column1 | Yes | Column Input.
Integer, Decimal |
Numerical variable upon which the test will be computed. |
| column2 | Yes | Column Input.
Integer, Decimal |
Numerical variable upon which the test will be computed. |
| use | Yes | Select from five options | How you would like to handle missing data, all.obs assumes no missing data. Select from everything, all.obs, complete.obs, na.or.complete, pairwise.complete.obs. |
| method | Yes | Select from two options | Specify the type of correlation to calculate. Choose between Pearson and Spearman. |