Free Standard Error of Regression Calculator
Calculate the standard error of the regression (root mean square error) measuring prediction accuracy.
Standard Error of Regression
2.0628
Standard Error of Regression vs Residual Sum of Squares (SSE)
Standard Error of Regression (RMSE)
The standard error of regression (also called residual standard error or RMSE) estimates the standard deviation of the residuals.
Formula
Se = sqrt(SSE / (n - p - 1))
where SSE is the sum of squared residuals, n is sample size, and p is the number of predictors. Smaller Se means better prediction accuracy. The denominator (n - p - 1) accounts for the degrees of freedom lost estimating the model parameters.
Example Calculation
SSE = 200, n = 50, p = 2 predictors.
- 01df = 50 - 2 - 1 = 47
- 02MSE = 200 / 47 = 4.2553
- 03Se = sqrt(4.2553) = 2.0629
Frequently Asked Questions
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