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# Mean Squared Error Calculator

The mean squared error (MSE) or mean squared deviation (MSD) is a metric that tells you how close your predicted values are to your observed values in a regression analysis. It is the sum of the squares of the distance between the predicted and observed values. The distances are the errors. The equation for the MSE is as follows:

$$\text{MSE}= \frac{\Sigma (P_{i} – O_{i})^{2}}{n}$$

where:

• Σ = Sum over all considered values
• Pi = ith Predicted value
• Oi = ith Observed value
• n = sample size

You can use the MSE calculator below by entering a list of observed and predicted values in the boxes below, then click Calculate MSE.