5- According to the summary result of linear regression model between A and B obtained from R given below, we can fita regression line. Assume that A has any value. If we decrease the value of A by 3, how would Y be affected?Call:1m (formula = B A)Residuals:Min10 Median30Max-16.340 -10.793-9.653-8.50258.325Coefficients:Estimate Std. Error t value Pr(>1t|)20.6457(Intercept)19.63150.9510.373A9.96090.371726.800 2.58e-08 ***Signif. codes:0 *** 0.001 ** 0.01 * 0.05, 0.1 1Residual standard error: 26.46 on 7 degrees of freedomAdjusted R-squared:p-value: 2.58le-080.989Multiple R-squared:F-statistic: 718.2 on 1 and 7 DF,0.9903,a)29.8827 increaseb)29.8827 decreaseC)58.8945 increased)49.5142 decreasee)58.8945 decreaseLeave blank

Given Data : The slope of the regression is 9.9609 and positive sign tells that if A goes high , y…

5- According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume that A has any value. If we decrease the value of A by 3, how would Y be affected? Call: 1m (formula - B- A) Residuals: Min 10 Median 30 Max -16.340 -10.793 -9.653 -8.502 58.325 Coefficients: Estimate Std. Error t value Pr (>It|) (Intercept) 19.6315 20.6457 0.951 0.373 A 9.9609 0.3717 26.800 2.58e-08 *** Signif. codes: 0 **** 0.001 *** 0.01 * 0.05 , 0.1 1 Residual standard error: 26.46 on 7 degrees of freedom 0.9903, Adjusted R-squared: 0.989 Multiple R-squared: F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08 a) 29.8827 increase b) 29.8827 decrease c) 58.8945 increase d) 49.5142 decrease e) 58.8945 decrease Leave blank

5- According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume that A has any value. If we decrease the value of A by 3, how would Y be affected? Call: 1m (formula - B- A) Residuals: Min 10 Median 30 Max -16.340 -10.793 -9.653 -8.502 58.325 Coefficients: Estimate Std. Error t value Pr (>It|) (Intercept) 19.6315 20.6457 0.951 0.373 A 9.9609 0.3717 26.800 2.58e-08 * Signif. codes: 0 0.001 * 0.01 * 0.05 , 0.1 1 Residual standard error: 26.46 on 7 degrees of freedom 0.9903, Adjusted R-squared: 0.989 Multiple R-squared: F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08 a) 29.8827 increase b) 29.8827 decrease c) 58.8945 increase d) 49.5142 decrease e) 58.8945 decrease Leave blank

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter4: Eigenvalues And Eigenvectors

Section4.6: Applications And The Perron-frobenius Theorem

Problem 25EQ

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