Calculates the linear regression of a set and returns the variance associated with the regression line y = ax + b.
LinRegVariance(«Set», «Numeric Expression»[, «Numeric Expression»])
Linear regression that uses the least-squares method calculates the equation of the best-fit line for a series of points. Let the regression line be given by the following equation, where a is called the slope and b is called the intercept:
y = ax+b
This function evaluates «Set» against the first «Numeric Expression» to get the set of values for the y-axis. It then evaluates «Set» against the second «Numeric Expression», if present, to get the set of values for the x-axis. If the second «Numeric Expression» is not present, the function uses the members of «Set» as values for the x-axis.
The latter case is not often useful for standard dimensions (for example, SalesPerson). However, it is often used with the Time dimension.
After obtaining the set of points, LinRegVariance returns the statistical variance that describes the fit of the linear equation to the points.
Note Empty cells or cells containing text or logical values are ignored; however, cells with values of zero are included.