Exercise

# Computing the MSE & RMSE of a model

Just as you did earlier with \(R^2\), which is a measure of model fit, let's now compute the root mean square error (RMSE) of our models, which is a commonly used measure of preditive error. Let's use the model of price as a function of size and number of bedrooms.

The model is available in your workspace as `model_price_2`

.

Instructions 1/2

**undefined XP**

Let's start by computing the mean squared error (`mse`

), which is the `mean`

of the squared `residual`

.