 past, and as a result statisticians used the square instead, which also penalizes large residuals more than smaller residuals. The square version also has some convenient throretical properties. It's the standard deviation of the residuals about zero. So we will use the square.

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class: middle, center

# Quiz

What could go wrong?

$$ \frac{1}{n} \sum_{i=1}^n (\hat{y}_i - {y}_i)^2$$ 

???

If you take the square to return things to the same units as the residuals, you have the the root mean square error