We would now like to test our model using the testing data that we produced from Question $2.$ To chieve this, we'll use the mean square error, which for your convenience is written as:

MSE$=\frac{1}{N}{\displaystyle \underset{i=1}{\overset{N}{}}}(p_i-y_i{)}^2$

where $p_i$ refers to the $i^{th}$ prediction made from $x_{-}$test,$y_i$ refers to the $i^{th}$ value in $y_{-}$test $,$ and $N$ is the length of $y_{-}$test $.$

Function Specifications:

Should return the mean square error over the input from the predicted values of X$\_$test as compared to values of $y_{-}t$ test

The output should be a float rounded to $2$ decimal places.

$[93]$:

## START FUNCTION

def test$\_$model$($model$,$ X$\_$test, y$\_$test$)$:

# your code here

return

## END FUNCTION

$[95]$: data $=$ get$\_$year$\_$pop$(\text{'}$Aruba$\text{'})$