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Data for two variables, and y, follow. 3₁ 12 21 a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. ŷ y = * 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 26 28 40 Yi 12 21 31 35 70 x Standardized Residual Can any of these observations be classified as an outlier? Explain. S * Xi 22 24 26 28 40 35 70 31 35

Data for two variables, and y, follow. 3₁ 12 21 a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. ŷ y = * 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 26 28 40 Yi 12 21 31 35 70 x Standardized Residual Can any of these observations be classified as an outlier? Explain. S * Xi 22 24 26 28 40 35 70 31 35

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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Data for two variables, and y, follow. xi No a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. ŷ b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. 22 24 26 28 40 Yi 12 21 31 35 70 x Standardized Residual Can any of these observations be classified as an outlier? Explain. Xi 22 24 26 28 40 Because none c. Develop a standardized residual plot for . Yi 12 21 31 35 70 of the standardized residuals are less than -2 or greater than 2, none of the observations can be classified as an outlier.
Transcribed Image Text:Data for two variables, and y, follow. xi No a. Develop the estimated regression equation for these data (to 2 decimals). Enter negative value as negative number. ŷ b. Compute the standardized residuals for these data (to 2 decimals). Do not round your intermediate calculations. Enter negative value as negative number. 22 24 26 28 40 Yi 12 21 31 35 70 x Standardized Residual Can any of these observations be classified as an outlier? Explain. Xi 22 24 26 28 40 Because none c. Develop a standardized residual plot for . Yi 12 21 31 35 70 of the standardized residuals are less than -2 or greater than 2, none of the observations can be classified as an outlier.
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