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

Question 125

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Solve the problem.
-The sum of squares of residuals (yy^)2\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, y^\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? x12345y717202528\begin{array} { c | c c c c c } x & 1 & 2 & 3 & 4 & 5 \\\hline y & 7 & 17 & 20 & 25 & 28\end{array}

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Sum of squares of residuals for linear m...

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