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The Sequential Sums of Squares Represent the Conditional Contribution of Each

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The sequential sums of squares represent the conditional contribution of each of the predictor variables given the variables already in the model. Use the following partial output generated using MINITAB to determine which predictor variable accounts for the largest proportion of the total variation explained by the regression model. What is the proportion accounted by the selected variable? The sequential sums of squares represent the conditional contribution of each of the predictor variables given the variables already in the model. Use the following partial output generated using MINITAB to determine which predictor variable accounts for the largest proportion of the total variation explained by the regression model. What is the proportion accounted by the selected variable?

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blured image accounts for 16,560.1/18,969....

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