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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.