A linear regression analysis is used to analyze the relationship of the sleep time the night before the exam (minutes) and the midterm score (points). The results are shown below. SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Regression Statistics Intercept Sleep Time 0.981712 0.963758 0.959228 2.204662 df 10 SS MS ignificance F 1 1034.016 1034.016 212.7371 4.79E-07 8 38.88427 4.860534 9 1072.9 Coefficientsandard Err t Stat P-value Lower 95% Upper 95%ower 95.0%pper 95. 12.10246 4.971651 2.434294 0.040927 0.637811 23.56711 0.637811 23.5671 0.204902 0.014048 14.58551 4.79E-07 0.172506 0.237297 0.172506 0.23729 Which statement aligns with the result? A. Linear regression is not suitable for this analysis because R Square is 0.963758 B. The relationship is not linear since Multiple R is too high at 0.981412 C. The student shall sleep at least 204.902 minutes before the exam D. The student shall sleep at least 12.10246 minutes before the exam E. If the student sleeps 1 more hour, the score shall increase 21 points. F. If the student sleeps 1 more hour, the score shall increase 12.2941 points. G. If the student sleeps 1 more hour, the score shall increase 12.6824 points. (Enter either A, B, C, D, E, F, or G.)

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answer in 4 decimal places and please do it on excel. thank you

A linear regression analysis is used to analyze the relationship of the sleep
time the night before the exam (minutes) and the midterm score (points).
The results are shown below.
SUMMARY OUTPUT
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression Statistics
Regression
Residual
Total
0.981712
0.963758
0.959228
2.204662
df
10
SS
MS
F ignificance F
1034.016 1034.016 212.7371 4.79E-07
8 38.88427 4.860534
9 1072.9
Coefficientsandard Err t Stat P-value Lower 95% Upper 95%ower 95.0%pper 95.0%
12.10246 4.971651 2.434294 0.040927 0.637811 23.56711 0.637811 23.56711
0.204902 0.014048 14.58551 4.79E-07 0.172506 0.237297 0.172506 0.237297
Intercept
Sleep Time
Which statement aligns with the result?
A. Linear regression is not suitable for this analysis because R Square is
0.963758
B. The relationship is not linear since Multiple R is too high at 0.981412
C. The student shall sleep at least 204.902 minutes before the exam
D. The student shall sleep at least 12.10246 minutes before the exam
E. If the student sleeps 1 more hour, the score shall increase 21 points.
F. If the student sleeps 1 more hour, the score shall increase 12.2941
points.
G. If the student sleeps 1 more hour, the score shall increase 12.6824
points.
(Enter either A, B, C, D, E, F, or G.)
Transcribed Image Text:A linear regression analysis is used to analyze the relationship of the sleep time the night before the exam (minutes) and the midterm score (points). The results are shown below. SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Statistics Regression Residual Total 0.981712 0.963758 0.959228 2.204662 df 10 SS MS F ignificance F 1034.016 1034.016 212.7371 4.79E-07 8 38.88427 4.860534 9 1072.9 Coefficientsandard Err t Stat P-value Lower 95% Upper 95%ower 95.0%pper 95.0% 12.10246 4.971651 2.434294 0.040927 0.637811 23.56711 0.637811 23.56711 0.204902 0.014048 14.58551 4.79E-07 0.172506 0.237297 0.172506 0.237297 Intercept Sleep Time Which statement aligns with the result? A. Linear regression is not suitable for this analysis because R Square is 0.963758 B. The relationship is not linear since Multiple R is too high at 0.981412 C. The student shall sleep at least 204.902 minutes before the exam D. The student shall sleep at least 12.10246 minutes before the exam E. If the student sleeps 1 more hour, the score shall increase 21 points. F. If the student sleeps 1 more hour, the score shall increase 12.2941 points. G. If the student sleeps 1 more hour, the score shall increase 12.6824 points. (Enter either A, B, C, D, E, F, or G.)
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