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10- [-124 Points] DETAILS LAROSESTAT3 4.3.060. MY NOTES ' ASK YOUR TEACHER Refer to the following table of fuel economy data for a sample of

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10- [-124 Points] DETAILS LAROSESTAT3 4.3.060. MY NOTES ' ASK YOUR TEACHER Refer to the following table of fuel economy data for a sample of 10 vehicles. The predictor variable is x = engine size, expressed in liters; the response variable is y = combined (city/highway) gas mileage, expressed in miles per gallon (mpg). ., "2.1?\" Mini Cooper 1.6 31 Ford Focus 2.0 28 Toyota Camry 2.5 26 Honda Accord 2.4 26 Subaru Forester 2.5 23 Toyota Highlander 2.7 22 Ford Taurus 3.5 20 Chevrolet Equinox 3.0 19 Dodge Nitro 4.0 17 Cadillac limousine 4.6 14 (a) Compute the residual for each data value. Form a table of the residuals and squared residuals. (Round your answers to three decimal places.) x = engine size (liters) (Y ' 9) (y - 9)2 1.6 2.0 2.5 2.4 2.5 2.7 3.5 3.0 4.0 4.6 Sum the squared residuals to get SSE. (Round your answer to three decimal places.) (b) What does SSE measure? At this point, do we know whether SSE is large or small? Why or why not? Q SSE measures the sum of the residuals. We know that SSE is small, since we know the regression line, according to the least squares criterion no other possible straight line would result in a smaller SSE. O SSE measures the sum of the squared residuals. We know that SSE is large, since we know the regression line, according to the least squares criterion there are other possible straight lines that would result in a smaller SSE. O SSE measures the sum of squares. We know that SSE is small, since we know the regression line, according to the least squares criterion no other possible straight line would result in a smaller SSE. O SSE measures the sum of the squared residuals. We know that SSE is small, since we know the regression line, according to the least squares criterion no other possible straight line would result in a smaller SSE. O SSE measures the sum of the residuals. We know that SSE is large, since we know the regression line, according to the least squares criterion there are other possible straight lines that would result in a smaller SSE. (c) Which vehicle has the largest absolute residual? Clearly explain why this vehicle is unusual

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