15.8 Practice Assignment: 15.8 Practice Questions Exercise 15.40 Algo (Residual Analysis) 1.0 Data for two variables,...

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15.8 Practice Assignment: 15.8 Practice Questions Exercise 15.40 Algo (Residual Analysis) 1.0 Data for two variables, and y, follow. + * a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value = negative number. b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. Standardized Yi Residual 12 24 21 26 31 28 40 35 70 Can any of these observations be classified as an outlier? Explain. -Select your answer- Because -Select your answer- of the standardized residuals are less than -2 or greater than 2, -Select your answer - of the observations can be classified as an outlier. c. Develop a standardized residual plot for . Standardized Residual F-1 10 30 50 60 70 Fitted Value Standardized Residual 10 Standardized Residual Fitted Value 10 30 Fitted Value - Select your answer- Does the residual plot support the assumptions about ? Explain. With only 5 observations, it -Select your answer- difficult to determine if the model assumptions are violated. A 22 24 26 28 40 12 21 31 35 70 15.8 Practice Assignment: 15.8 Practice Questions Exercise 15.40 Algo (Residual Analysis) 1.0 Data for two variables, and y, follow. + * a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value = negative number. b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. Standardized Yi Residual 12 24 21 26 31 28 40 35 70 Can any of these observations be classified as an outlier? Explain. -Select your answer- Because -Select your answer- of the standardized residuals are less than -2 or greater than 2, -Select your answer - of the observations can be classified as an outlier. c. Develop a standardized residual plot for . Standardized Residual F-1 10 30 50 60 70 Fitted Value Standardized Residual 10 Standardized Residual Fitted Value 10 30 Fitted Value - Select your answer- Does the residual plot support the assumptions about ? Explain. With only 5 observations, it -Select your answer- difficult to determine if the model assumptions are violated. A 22 24 26 28 40 12 21 31 35 70