A statistical program is recommended. You may need to use the appropriate appendix table or technology to answer this question. Data for two variables, x and y, follow. 12345 1539 12 (a) Develop the estimated regression equation for these data. (Round your numerical values to two decimal places.) (b) Plot the standardized residuals versus ý. -1 21 0 2 4 6 8 10 12 14 16 18 20 0 2 4 6 8 10 12 14 16 18 20 468 10 12 14 16 18 20 0 2 4 6 8 10 12 14 16 18 20 0 2 Do there appear to be any outliers in these data? Explain. The value of the standardized residual for Select |is either greater than +2 or less than -2. Therefore, there -Select- (c) Compute the studentized deleted residuals for these data. (Round your answers to two decimal places.) Studentized X Y Deleted Residual 11 25 33 4 9 5 12 At the 0.05 level of significance, can any of these observations be classified as an outlier? Explain. (Select all that apply.) O Observation x, - 1 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). O Observation x, = 2 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). O Observation x, - 3 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). O Observation x,- 4 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025) O Observation x, = 5 can be classifled as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). O None of the observations can be classified as outliers since they do not have large studentized deleted residuals (greater than to.025 or less than -to.025)- Standardized Residual

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