A regression analysis done with Excel for the relationship between The placement test scores and the final grades for 20 students who took the regular course were recorded and yielded the following output. SUMMARY OUTPUT Regression Statistics Multiple R 0.45351 R Square 0.20567 Adjusted F 0.16155 Standard E 16.1747 Observatic 20 ANOVA df SS MS gnificance F Regression 1 1219.35 1219.35 4.66073 0.04461 Residual 18 4709.2 261.622 Total 19 5928.55 Chart Area Coefficientsandard Ernt Stat P-value Lower 95% Upper 95%ower 95.0%pper 95.0% 0.0192 5.95316 59.0587 5.95316 59.0587 Intercept 32.5059 12.6386 2.57195 X Variable 0.47106 0.2182 2.15887 0.04461 0.01264 0.92948 0.01264 0.92948 What percent of the total sum of squares (SST) can be explained by using the estimated regression equation to predict the course grade? A. 45.35% B. 20.57% C. 79.43% D. 21.82%

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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A regression analysis done with Excel for the relationship between The
placement test scores and the final grades for 20 students who took the regular
course were recorded and yielded the following output.
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.45351
R Square 0.20567
Adjusted F 0.16155
Standard E 16.1747
Observatic
20
ANOVA
df
SS
MS
F
gnificance F
0.04461
1 1219.35
1219.35 4.66073
Regression
Residual
Total
18 4709.2 261.622
19 5928.55
Chart Area
Coefficientsandard Ernt Stat
Intercept 32.5059 12.6386 2.57195
P-value Lower 95% Upper 95%ower 95.0%pper 95.0%
0.0192 5.95316 59.0587 5.95316 59.0587
X Variable 0.47106 0.2182 2.15887 0.04461 0.01264 0.92948 0.01264 0.92948
What percent of the total sum of squares (SST) can be explained by using the
estimated regression equation to predict the course grade?
A. 45.35%
B. 20.57%
C. 79.43%
D. 21.82%
Transcribed Image Text:A regression analysis done with Excel for the relationship between The placement test scores and the final grades for 20 students who took the regular course were recorded and yielded the following output. SUMMARY OUTPUT Regression Statistics Multiple R 0.45351 R Square 0.20567 Adjusted F 0.16155 Standard E 16.1747 Observatic 20 ANOVA df SS MS F gnificance F 0.04461 1 1219.35 1219.35 4.66073 Regression Residual Total 18 4709.2 261.622 19 5928.55 Chart Area Coefficientsandard Ernt Stat Intercept 32.5059 12.6386 2.57195 P-value Lower 95% Upper 95%ower 95.0%pper 95.0% 0.0192 5.95316 59.0587 5.95316 59.0587 X Variable 0.47106 0.2182 2.15887 0.04461 0.01264 0.92948 0.01264 0.92948 What percent of the total sum of squares (SST) can be explained by using the estimated regression equation to predict the course grade? A. 45.35% B. 20.57% C. 79.43% D. 21.82%
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