These functions have to do with association between two attributes. They are all aggregate functions so you can use them in formulas for attributes or for measures.
Note: All of these functions take an optional last argument, a Boolean expression. That modifies the function so that it applies only to those cases where the condition is true. For example, correlation( engineSize, fuelUsage, carSize = "compact") finds the correlation between engineSize and fuelUsage for the subset of cars in the collection that are compact.
correlation( x, y ) |
The correlation coefficient of y and x. |
rSquared( x, y) |
The square of the correlation coefficient of y and x. It represents the proportion of the variation of y that is accounted for by a least-squares regression line. It takes on values between 0 and 1. |
linRegrIntercept( x, y) |
Returns the intercept of the least-squares regression line with x as the independent attribute and y as the dependent attribute. |
linRegrSlope( x, y ) |
Returns the slope of the least-squares regression line with x as the independent attribute and y as the dependent attribute. |