Figure 1 shows the results of the statistical test without interaction term between Region and Design (aov1), and the statistical test with interaction term between Region and Design (aov2) as R output for this problem. Figure 1. R output of model results for two statistical models, one without an interaction term between Design and Region (aov1) and one with interaction term between Design and Region (aov2). > aovi <- aoV(RESPONSE~Design+Region, data=ads) > summary(aov1) pesign Region Residuals --- signif. codes: of Sum sq Mean sq F value 2 236337 118169 3 94638 30 42495 Pr (>F) 83.42 5. 56e-13 *** 22.27 8. 80e-08 *** 31546 1416 O **** 0.001 *** 0.01 * 0.05 0.1 1 aov2 <- aov(Response-Design*Region, data-ads) > summary(aov2) of Sum sq Mean sq F value 2 236337 118169 82. 812 1.69e-11 *** Pr (>F) pesign Region besign:Region 6 Residuals --- signif. codes: 0 **** 0.001 *** 0.01 ** 0.05 .' 0.1 '1 3 94638 8248 24 34247 31546 22.107 4.34 e-07 *** 0. 963 1375 1427 0.47
Figure 1 shows the results of the statistical test without interaction term between Region and Design (aov1), and the statistical test with interaction term between Region and Design (aov2) as R output for this problem. Figure 1. R output of model results for two statistical models, one without an interaction term between Design and Region (aov1) and one with interaction term between Design and Region (aov2). > aovi <- aoV(RESPONSE~Design+Region, data=ads) > summary(aov1) pesign Region Residuals --- signif. codes: of Sum sq Mean sq F value 2 236337 118169 3 94638 30 42495 Pr (>F) 83.42 5. 56e-13 *** 22.27 8. 80e-08 *** 31546 1416 O **** 0.001 *** 0.01 * 0.05 0.1 1 aov2 <- aov(Response-Design*Region, data-ads) > summary(aov2) of Sum sq Mean sq F value 2 236337 118169 82. 812 1.69e-11 *** Pr (>F) pesign Region besign:Region 6 Residuals --- signif. codes: 0 **** 0.001 *** 0.01 ** 0.05 .' 0.1 '1 3 94638 8248 24 34247 31546 22.107 4.34 e-07 *** 0. 963 1375 1427 0.47
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
![Figure 1 shows the results of the statistical test without interaction term between Region and Design (aov1), and the statistical test with interaction term between
Region and Design (aov2) as R output for this problem.
Figure 1.
R output of model results for two statistical models, one without an interaction term between Design and Region (aov1) and one with interaction term between Design
and Region (aov2).
aovi <- aov(Response-Design+Region, data=ads)
summary(aov1)
þesign
Region
Residuals
Df Sum Sq Mean sq F value
2 236337
3 94638
30
118169
31546
1416
Pr (>F)
83.42 5.56e-13 ***
22.27 8. 80e-08 ***
42495
signif. codes: 0 ****' 0.001 ***' 0.01 **' 0.05 '.' 0.1 ''1
aov2 <- aov(Response-Design*Region, data=ads)
summary(aov2)
of Sum sq Mean sq F value
2 236337 118169 82. 812 1.69e-11 ***
Pr (>F)
þesign
Region
þesign:Region 6
Residuals
3 94638
8248
34247
31546 22.107 4. 34e-07 ***
0. 963
1375
1427
0.47
24
---
signif. codes:
O ***
0.001
0. 01 *
0.05 .' 0.1'1
Using a significant at the significance level alpha = 0.05, based on Figure 1 which statement is correct?
%D
The model without interaction (aov1) shows that the factors Design and Region are not significant with regards to their impact on survey responses at the selected
significance level.
The model with interaction (aov2) shows that interaction term between Design and Region is significant with regards to the impact on survey responses at the
selected significance level.
Using the model with interaction (aov2) results, we fail to reject the null hypothesis related to interaction between Design and Region at the selected significance
level, i.e., we can't reject that the levels of Design are the same with regards to the impact of Region on Response, and we can't reject that levels of Region are
the same with regards to the impact of Design on Response.
Using the model with interaction (aov2) results, we reject the null hypothesis related to interaction between Design and Region at the selected significance level,
i.e., we reject that the levels of Design are the same with regards to the impact of Region on Response, and we reject that levels of Region are the same with
regards to the impact of Design on Response.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F52d603da-3ef0-4691-a51e-f5486473db25%2F96570990-29c2-47f7-aa63-f2f9221d5bfe%2F7h62ve_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Figure 1 shows the results of the statistical test without interaction term between Region and Design (aov1), and the statistical test with interaction term between
Region and Design (aov2) as R output for this problem.
Figure 1.
R output of model results for two statistical models, one without an interaction term between Design and Region (aov1) and one with interaction term between Design
and Region (aov2).
aovi <- aov(Response-Design+Region, data=ads)
summary(aov1)
þesign
Region
Residuals
Df Sum Sq Mean sq F value
2 236337
3 94638
30
118169
31546
1416
Pr (>F)
83.42 5.56e-13 ***
22.27 8. 80e-08 ***
42495
signif. codes: 0 ****' 0.001 ***' 0.01 **' 0.05 '.' 0.1 ''1
aov2 <- aov(Response-Design*Region, data=ads)
summary(aov2)
of Sum sq Mean sq F value
2 236337 118169 82. 812 1.69e-11 ***
Pr (>F)
þesign
Region
þesign:Region 6
Residuals
3 94638
8248
34247
31546 22.107 4. 34e-07 ***
0. 963
1375
1427
0.47
24
---
signif. codes:
O ***
0.001
0. 01 *
0.05 .' 0.1'1
Using a significant at the significance level alpha = 0.05, based on Figure 1 which statement is correct?
%D
The model without interaction (aov1) shows that the factors Design and Region are not significant with regards to their impact on survey responses at the selected
significance level.
The model with interaction (aov2) shows that interaction term between Design and Region is significant with regards to the impact on survey responses at the
selected significance level.
Using the model with interaction (aov2) results, we fail to reject the null hypothesis related to interaction between Design and Region at the selected significance
level, i.e., we can't reject that the levels of Design are the same with regards to the impact of Region on Response, and we can't reject that levels of Region are
the same with regards to the impact of Design on Response.
Using the model with interaction (aov2) results, we reject the null hypothesis related to interaction between Design and Region at the selected significance level,
i.e., we reject that the levels of Design are the same with regards to the impact of Region on Response, and we reject that levels of Region are the same with
regards to the impact of Design on Response.
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