Calculates the linear regression of a set, and returns the variance associated with the regression line, y = ax + b.
Linear regression, that uses the least-squares method, calculates the equation of a regression line (that is, the best-fit line for a series of points). The regression line has the following equation, where a is the slope and b is the intercept:
y = ax+b
The LinRegVariance function evaluates the specified setagainst the first numeric expression to obtain the values for the y-axis. The function then evaluates the specified setagainst the second numeric expression, if specified, to obtain the values for the x-axis. If the second numeric expressionis not specified, the function uses the current context of the cells in the specified set as the values for the x-axis. Not specifying the x-axis argument is frequently used with the Time dimension.
After obtaining the set of points, the LinRegVariance function returns the statistical variance that describes the fit of the linear equation to the points.
The LinRegVariance function ignores empty cells or cells that contain text or logical values. However, the function includes cells with values of zero.
The following example returns the statistical variance that describes the fit of the linear equation to the points for the unit sales and the store sales measures.
LinRegVariance(LastPeriods(10),[Measures].[Unit Sales],[Measures].[Store Sales])