# LinRegIntercept (MDX)

Calculates the linear regression of a set and returns the value of the x-intercept in the regression line, y = ax + b.

## Syntax

```
LinRegIntercept(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 **LinRegIntercept** function evaluates the specified set against the first numeric expression to 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 expression is not specified, the function uses the current context of the cells in the specified set as 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 **LinRegIntercept** function returns the intercept of the regression line (b in the previous equation).

Note

The **LinRegIntercept** 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 intercept of a regression line for the unit sales and the store sales measures.

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