Least Square Error Calculator

Calculate Least Square Error



Formula

To calculate the Least Square Error (LSE):

\[ LSE = \frac{1}{n} \sum (observed - predicted)^2 \]

Where:

What is Least Square Error?

Least square error is a measure used in statistical models to quantify the difference between the values predicted by a model and the values actually observed from the environment that is being modeled. It is a common measure of the overall 'fit' of a model, with lower values indicating a better fit.

Example Calculation

Let's assume the following values:

Using the formula:

\[ LSE = \frac{1}{5} \left( (3-2.8)^2 + (4-4.1)^2 + (5-4.9)^2 + (6-6.2)^2 + (7-7.1)^2 \right) \]

\[ LSE = \frac{1}{5} \left( 0.04 + 0.01 + 0.01 + 0.04 + 0.01 \right) = \frac{1}{5} \times 0.11 = 0.022 \]

The Least Square Error is 0.022.