Mean Squared Error

Media & Interactive Simulations

Data Scientist Greg Hogg clearly explains the difference between Absolute Error and Squared Error, and why MSE is vital for calculus-based optimization.

Line of Best Fit

Drag the white points or adjust the sliders to see how the penalty squares visually expand.

MSE: 0.000
y = -0.30x + -2.00
Access the code of this MSE Simulation