The root mean square error (RMSE) is a metric that tells us how far apart our predicted values are from our observed values in a regression analysis, on average. It is calculated as:

RMSE = √[ Σ(P_i – O_i)² / n ]

where:

• Σ is a fancy symbol that means “sum”
• P_i is the predicted value for the i^th observation
• O_i is the observed value for the i^th observation
• n is the sample size

To find the RMSE for a regression, simply enter a list of observed values and predicted values in the two boxes below, then click the “Calculate” button:

34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24

37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23

RMSE = 2.43242