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

Mean Squared Error (MSE)4.2553

Standard Error of Regression vs Residual Sum of Squares (SSE)

सूत्र देखें →

सूत्र

## 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.

हल किया गया उदाहरण

SSE = 200, n = 50, p = 2 predictors.

  1. 01df = 50 - 2 - 1 = 47
  2. 02MSE = 200 / 47 = 4.2553
  3. 03Se = sqrt(4.2553) = 2.0629