MSE is short for mean squared error.
It measures the average squared difference between the estimated values and the actual value.
The mean squared error tells you how close a regression line is to a set of points.
Formula to calculate MSE.
![How to Calculate MSE.](https://www.learntocalculate.com/wp-content/uploads/2021/02/MSEE.png)
![How to Calculate MSE.](https://www.learntocalculate.com/wp-content/uploads/2021/02/MSEE-2-1.png)
Example:
Suppose you were measuring the length of 5 strings, calculate the MSE if the sum of the observed value is 60 cm and the sum of the predicted value is 61.5 cm.
![How to Calculate MSE.](https://www.learntocalculate.com/wp-content/uploads/2021/02/MSEE-3.png)
Therefore, the MSE is 0.45.