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Solve the problem.
-The sum of squares of residuals 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, . 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?
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