# LinRegR2 (MDX)

Calculates the linear regression of a set and returns the coefficient of determination, R2.

## Syntax

``````
LinRegR2(Set_Expression, Numeric_Expression_y [ ,Numeric_Expression_x ] )
``````

## Arguments

Set_Expression
A valid Multidimensional Expressions (MDX) expression that returns a set.

Numeric_Expression_y
A valid numeric expression that is typically a Multidimensional Expressions (MDX) expression of cell coordinates that return a number that represents values for the y-axis.

Numeric_Expression_x
A valid numeric expression that is typically a Multidimensional Expressions (MDX) expression of cell coordinates that return a number that represents values for the x-axis.

## Remarks

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 LinRegR2 function evaluates the specified setagainst the first numeric expressionto obtain the values for the y-axis. The function then evaluates the specified set against 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-axisargument is frequently used with the Time dimension.

After obtaining the set of points, the LinRegR2 function returns the statistical R2 that describes the fit of the linear equation to the points.

Note

The LinRegR2 function ignores empty cells or cells that contain text or logical values. However, the function includes cells with values of zero.

## Example

The following example returns the statistical R2 that describes the goodness of fit of the linear regression equation to the points for the unit sales and the store sales measures.

``````LinRegR2(LastPeriods(10), [Measures].[Unit Sales],[Measures].[Store Sales])
``````