SUMMARY OUTPUT Regression Statistics Multiple R 0.69406672 R Square Adjusted R Square Standard Error Observations 0.481728612 0.476440129 3.936905277 100 ANOVA Regression Residual Total df SS MS F 1 1411.826131 1411.82613 91.09012 Significance F 1.18186E-15 98 99 1518.923869 2930.75 15.4992232 Coefficients Standard Error Intercept Father's Age (Death) 29.28584902 0.627659604 4.539696555 t Stat P-value 6.45105872 4.23E-09 0.065764048 9.54411453 1.18E-15 Lower 95% Upper 95% 20.27696896 38.29472909 0.497152992 0.758166217 Lower 95.0% Upper 95.0% 20.27696896 0.497152992 38.29472909 0.758166217 Customer's Age (Death) Excel was used to run a simple linear regression analysis. Excel output and diagnostic plots follow for your reference in answering the remaining questions. 15 Father's Age (Death) Residual Plot Residuals -10 -15 10 10 5 0 40 50 80 90 100 Father's Age (Death) 100 90 80 Normal Probability Plot 70 50 40 30 20 10 0 0 20 40 60 80 100 120 Sample Percentile

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section: Chapter Questions
Problem 43SGR
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Question

what is the regression eruation that describes the relationship bewteen the customer's age at death and their father's age at death

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.69406672
R Square
Adjusted R Square
Standard Error
Observations
0.481728612
0.476440129
3.936905277
100
ANOVA
Regression
Residual
Total
df
SS
MS
F
1
1411.826131
1411.82613 91.09012
Significance F
1.18186E-15
98
99
1518.923869
2930.75
15.4992232
Coefficients
Standard Error
Intercept
Father's Age (Death)
29.28584902
0.627659604
4.539696555
t Stat P-value
6.45105872 4.23E-09
0.065764048 9.54411453 1.18E-15
Lower 95% Upper 95%
20.27696896 38.29472909
0.497152992 0.758166217
Lower 95.0% Upper 95.0%
20.27696896
0.497152992
38.29472909
0.758166217
Transcribed Image Text:SUMMARY OUTPUT Regression Statistics Multiple R 0.69406672 R Square Adjusted R Square Standard Error Observations 0.481728612 0.476440129 3.936905277 100 ANOVA Regression Residual Total df SS MS F 1 1411.826131 1411.82613 91.09012 Significance F 1.18186E-15 98 99 1518.923869 2930.75 15.4992232 Coefficients Standard Error Intercept Father's Age (Death) 29.28584902 0.627659604 4.539696555 t Stat P-value 6.45105872 4.23E-09 0.065764048 9.54411453 1.18E-15 Lower 95% Upper 95% 20.27696896 38.29472909 0.497152992 0.758166217 Lower 95.0% Upper 95.0% 20.27696896 0.497152992 38.29472909 0.758166217
Customer's Age (Death)
Excel was used to run a simple linear regression analysis. Excel output and diagnostic
plots follow for your reference in answering the remaining questions.
15
Father's Age (Death) Residual Plot
Residuals
-10
-15
10
10
5
0
40
50
80
90
100
Father's Age (Death)
100
90
80
Normal Probability Plot
70
50
40
30
20
10
0
0
20
40
60
80
100
120
Sample Percentile
Transcribed Image Text:Customer's Age (Death) Excel was used to run a simple linear regression analysis. Excel output and diagnostic plots follow for your reference in answering the remaining questions. 15 Father's Age (Death) Residual Plot Residuals -10 -15 10 10 5 0 40 50 80 90 100 Father's Age (Death) 100 90 80 Normal Probability Plot 70 50 40 30 20 10 0 0 20 40 60 80 100 120 Sample Percentile
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