Linear Regression Standard Error

Routine Summary

Calculates the standard error associated with linear regression coefficients.


L₁ - values of the independent variable
L₂ - values of the dependent variable


Ans - a 2-element list containing the standard errors

Variables Used

L₁, L₂,

Calculator Compatibility


:2-Var Stats

This routine computes the standard error (uncertainty) associated with the linear regression coefficients a and ba and σb, respectively) for the regression equation y=ax+b. Precisely stated, the true value of the coefficient a is expected to be within the interval a±σa, and similarly for b.

The routine returns a two-element list; σa is the first element, and σb is the second element.

If one prefers to use the function LinReg(a+bx) instead of LinReg(ax+b), the appropriate routine is:

:2-Var Stats

(note that the meanings of σa and σb have now interchanged).

In both routines, r², a, b, n, and Σx² are statistical variables.


For the fitting equation y=ax+b,

\begin{align} \definecolor{darkgreen}{rgb}{0.90,0.91,0.859}\pagecolor{darkgreen} \begin{align*} \sigma_a&=a\sqrt{\frac{\frac1{r^2}-1}{n-2}} \\ \sigma_b&=\sigma_a\sqrt{\frac{\Sigma x^2}{n}} \end{align*} \end{align}

where n is the number of data points, r² is the coefficient of determination, and Σx² is the sum of squares of the independent variable values.

Error Conditions


Lichten, William. Data and Error Analysis., 2nd. ed., Prentice Hall: Upper Saddle River, NJ, 1999.


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