LINESTX

Applies to: Calculated column Calculated table Measure Visual calculation

Uses the Least Squares method to calculate a straight line that best fits the given data, then returns a table describing the line. The data result from expressions evaluated for each row in a table. The equation for the line is of the form: y = Slope1*x1 + Slope2*x2 + ... + Intercept.

Syntax

LINESTX ( <table>, <expressionY>, <expressionX>[, …][, <const>] )

Parameters

Return value

A single-row table describing the line, plus additional statistics. These are the available columns:

• Slope1, Slope2, ..., SlopeN: the coefficients corresponding to each x-value;
• Intercept: intercept value;
• StandardErrorSlope1, StandardErrorSlope2, ..., StandardErrorSlopeN: the standard error values for the coefficients Slope1, Slope2, ..., SlopeN;
• StandardErrorIntercept: the standard error value for the constant Intercept;
• CoefficientOfDetermination: the coefficient of determination (r²). Compares estimated and actual y-values, and ranges in value from 0 to 1: the higher the value, the higher the correlation in the sample;
• StandardError: the standard error for the y estimate;
• FStatistic: the F statistic, or the F-observed value. Use the F statistic to determine whether the observed relationship between the dependent and independent variables occurs by chance;
• DegreesOfFreedom: the degrees of freedom. Use this value to help you find F-critical values in a statistical table, and determine a confidence level for the model;
• RegressionSumOfSquares: the regression sum of squares;
• ResidualSumOfSquares: the residual sum of squares.

Example 1

The following DAX query:

DEFINE VAR TotalSalesByRegion = SUMMARIZECOLUMNS(
    'Sales Territory'[Sales Territory Key],
    'Sales Territory'[Population],
    "Total Sales", SUM(Sales[Sales Amount])
)
EVALUATE LINESTX(
    'TotalSalesByRegion',
    [Total Sales],
    [Population]
)

Returns a single-row table with ten columns:

• Slope1 and Intercept: the coefficients of the calculated linear model;
• StandardErrorSlope1 and StandardErrorIntercept: the standard error values for the coefficients above;
• CoefficientOfDetermination, StandardError, FStatistic, DegreesOfFreedom, RegressionSumOfSquares and ResidualSumOfSquares: regression statistics about the model.

For a given sales territory, this model predicts total sales by the following formula:

Total Sales = Slope1 * Population + Intercept

Example 2

The following DAX query:

DEFINE VAR TotalSalesByCustomer = SUMMARIZECOLUMNS(
    'Customer'[Customer ID],
    'Customer'[Age],
    'Customer'[NumOfChildren],
    "Total Sales", SUM(Sales[Sales Amount])
)
EVALUATE LINESTX(
    'TotalSalesByCustomer',
    [Total Sales],
    [Age],
    [NumOfChildren]
)

Returns a single-row table with twelve columns:

For a given customer, this model predicts total sales by the following formula:

Total Sales = Slope1 * Age + Slope2 * NumOfChildren + Intercept

Related content

LINEST
Statistical functions