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Exercise 15.40 Algo (Residual Analysis) Data for two variables, and y, follow. 24 25 3/12 23 31 a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. ŷ = -42.33 + 2.73 b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. 2₂ No 22 24 25 28 41 Yi 12 23 31 36 68 Standardized Residual -1.42 Standardized Residual -0.04 X 1.26 0.47 -0.39 X Can any of these observations be classified as an outlier? Explain. Because none c. Develop a standardized residual plot for ŷ. A X M 2₂ 22 of the standardized residuals are less than -2 or greater than 2, none 28 41 36 68 ✔ of the observations can be classified as an outlier. Hint(s) Check My Work

Exercise 15.40 Algo (Residual Analysis) Data for two variables, and y, follow. 24 25 3/12 23 31 a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. ŷ = -42.33 + 2.73 b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. 2₂ No 22 24 25 28 41 Yi 12 23 31 36 68 Standardized Residual -1.42 Standardized Residual -0.04 X 1.26 0.47 -0.39 X Can any of these observations be classified as an outlier? Explain. Because none c. Develop a standardized residual plot for ŷ. A X M 2₂ 22 of the standardized residuals are less than -2 or greater than 2, none 28 41 36 68 ✔ of the observations can be classified as an outlier. Hint(s) Check My Work

MATLAB: An Introduction with Applications
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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Exercise 15.40 Algo (Residual Analysis) Data for two variables, and y, follow. No X 22 24 -2 25 a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. y = -42.33 b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. 28 41 + 2.73 Yi 12 23 31 36 68 x Standardized Residual Standardized Residual -1.42 -0.04 1.26 X 0.47 Can any of these observations be classified as an outlier? Explain. -0.39 X Because none c. Develop a standardized residual plot for ŷ. A Xi Yi Cittad Val 22 12 of the standardized residuals are less than -2 or greater than 2, none 24 25 28 41 23 31 36 68 of the observations can be classified as an outlier. Question 1 of 1 Hint(s) Check My Work
Transcribed Image Text:Exercise 15.40 Algo (Residual Analysis) Data for two variables, and y, follow. No X 22 24 -2 25 a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. y = -42.33 b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. 28 41 + 2.73 Yi 12 23 31 36 68 x Standardized Residual Standardized Residual -1.42 -0.04 1.26 X 0.47 Can any of these observations be classified as an outlier? Explain. -0.39 X Because none c. Develop a standardized residual plot for ŷ. A Xi Yi Cittad Val 22 12 of the standardized residuals are less than -2 or greater than 2, none 24 25 28 41 23 31 36 68 of the observations can be classified as an outlier. Question 1 of 1 Hint(s) Check My Work
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