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
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
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text: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.
x, 12 345
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
0 2 4 6 8 10 12 14 16 18 20
0 2 4 6 8 10 12 14 16 18 20
0 2 4 6 8 10 12 14 16 18 20
0 2 4 6 8 10 12 14 16 18 20
Do there appear to be any outliers in these data? Explain.
The value of the standardized residual for Select-
--
v is either greater than +2 or less than -2. Therefore, there -Select--
v.
(c) Compute the studentized deleted residuals for these data. (Round your answers to two decimal places.)
Studentized
Deleted Residual
1
1
2 5
33
49
5 12
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 classified 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 dassified as outliers since they do not have large studentized deleted residuals (greater than to.025 or less than -to.025).
Standardized Residual
Standardized Residual
Standardized Residual
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