Standard Error of Regression Calculator — Formula
## 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.
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.
Esempio Risolto
SSE = 200, n = 50, p = 2 predictors.
- df = 50 - 2 - 1 = 47
- MSE = 200 / 47 = 4.2553
- Se = sqrt(4.2553) = 2.0629