8- 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: Im (formula = B - A) Residuals: Min 10 Median 30 Маx -16.340 -10.793 -9.653 -8.502 58.325 Coefficients: Estimate Std. Error t value Pr (>|t|) (Intercept) 19.6315 20.6457 0.951 0.373 A 9.9609 0.3717 26.800 2.58e-08 *** --- Signif. codes: O *** 0.001 *** 0.01 0.05 '.' 0.1 1 Residual standard error: 26.46 on 7 degrees of freedom Multiple R-squared: 0.9903, F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08 Adjusted R-squared: 0.989 a) 49.5142 decrease b) 29.8827 increase 58.8945 decrease 29.8827 decrease 58.8945 increase
8- 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: Im (formula = B - A) Residuals: Min 10 Median 30 Маx -16.340 -10.793 -9.653 -8.502 58.325 Coefficients: Estimate Std. Error t value Pr (>|t|) (Intercept) 19.6315 20.6457 0.951 0.373 A 9.9609 0.3717 26.800 2.58e-08 *** --- Signif. codes: O *** 0.001 *** 0.01 0.05 '.' 0.1 1 Residual standard error: 26.46 on 7 degrees of freedom Multiple R-squared: 0.9903, F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08 Adjusted R-squared: 0.989 a) 49.5142 decrease b) 29.8827 increase 58.8945 decrease 29.8827 decrease 58.8945 increase
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
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![8- 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:
Im (formula = B -
A)
Residuals:
Min
10
Median
30
Маx
-16.340 -10.793
-9.653
-8.502
58.325
Coefficients:
Estimate Std. Error t value Pr (>[t])
(Intercept)
19.6315
20.6457
0.951
0.373
A
9.9609
0.3717
26.800 2.58e-08 ***
---
Signif. codes:
O *** 0.001
1** 0.01
1** 0.05 '.' 0.1 '' 1
Residual standard error: 26.46 on 7 degrees of freedom
Multiple R-squared: 0.9903,
Adjusted R-squared:
0.989
F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08
a)
49.5142 decrease
b)
29.8827 increase
c)
58.8945 decrease
29.8827 decrease
58.8945 increase](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa8403ab6-244d-4f22-9010-1efe7f4fc972%2Fe28be5ef-ae42-4d95-99a5-c14bd58eb210%2Fqt9rqtol_processed.png&w=3840&q=75)
Transcribed Image Text:8- 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:
Im (formula = B -
A)
Residuals:
Min
10
Median
30
Маx
-16.340 -10.793
-9.653
-8.502
58.325
Coefficients:
Estimate Std. Error t value Pr (>[t])
(Intercept)
19.6315
20.6457
0.951
0.373
A
9.9609
0.3717
26.800 2.58e-08 ***
---
Signif. codes:
O *** 0.001
1** 0.01
1** 0.05 '.' 0.1 '' 1
Residual standard error: 26.46 on 7 degrees of freedom
Multiple R-squared: 0.9903,
Adjusted R-squared:
0.989
F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08
a)
49.5142 decrease
b)
29.8827 increase
c)
58.8945 decrease
29.8827 decrease
58.8945 increase
Expert Solution

Step 1
Let, the simple linear regression model where X is related to response variable Y in a linear form is given by,
From given summary result,
Step by step
Solved in 2 steps
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