The root mean squared error (RMSE) is a metric that’s used to measure how far apart the predicted values and the observed values in a regression analysis.
The RMSE metric is usually easier to interpret than MSE because it returns the error in terms of the unit you’re predicting.
RMSE = 3.08221
The formula for calculating the RMSE is as follows:
RMSE = √(Σ(yi – ŷi)² / n)
Here, Σ is the sum of values yi is the observed value, ŷi is the predicted value, n is the number of observations.
To calculate the RMSE, you need to subtract xᵗʰ predicted value from each xᵗʰ observed value, then square the difference.
Once you do that for all observations, sum the squared values and divide by the number of observations. As the last step, square root the MSE value.
If you want to calculate the MSE value instead, use the MSE calculator.
I hope this calculator helps. Happy analyzing!