Exercise

# Residual Sum of the Squares

In a previous exercise, we saw that the altitude along a hiking trail was roughly fit by a linear model, and we introduced the concept of ** differences** between the model and the data as a

**.**

*measure of model goodness*In this exercise, you'll work with the same measured data, and quantifying how well a model fits it by computing the sum of the square of the "differences", also called "residuals".

Instructions

**100 XP**

- Load the
`x_data`

,`y_data`

with the pre-defined`load_data()`

function. - Call the pre-defined
`model()`

, passing in`x_data`

and specific values`a0`

,`a1`

. - Compute the residuals as
`y_data - y_model`

and then find`rss`

by using`np.square()`

and`np.sum()`

. - Print the resulting value of
`rss`

.