Exercise

# RMSE Step-by-step

In this exercise, you will quantify the over-all model "goodness-of-fit" of a pre-built model, by computing one of the most common quantitative measures of model quality, the RMSE, step-by-step.

Start with the pre-loaded data `x_data`

and `y_data`

, and use it with a predefined modeling function `model_fit_and_predict()`

.

Instructions

**100 XP**

- Compute
`y_model`

values from`model_fit_and_predict(x_data, y_data)`

. - Compute the
`residuals`

as the difference between`y_model`

and`y_data`

. - Use
`np.sum()`

and`np.square()`

to compute`RSS`

, and divide by`len(residuals)`

to get`MSE`

. - Take the
`np.sqrt()`

of`MSE`

to get`RMSE`

, and print all results.