Solve the Problem $\sum ( y - \hat { y } ) ^ { 2 }$

Essay

Solve the problem.
-The sum of squares of residuals $\sum ( y - \hat { y } ) ^ { 2 }$ can be used to assess the quality of a regression model. A residual is the difference between an observed y value and the value of y predicted from the model, $\hat { \mathrm { y } }$ . The better the model, the smaller the sum of squares of residuals. For the data below find the sum of squares of residuals which results from fitting a linear model, and the sum of squares of residuals which results from fitting a logarithmic model. Which model fits better? How can you tell? $\begin{array} { c | c c c c c } x & 1 & 2 & 3 & 4 & 5 \\\hline y & 7 & 17 & 20 & 25 & 28\end{array}$