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 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 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
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
State the value of the coefficient of father's age (death) and the interpret this value in the context of the problem at hand?
Would it be sensible to use the relationship found here to estimate the age at death of females customers of the insurance company using their mother's age at death?
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
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
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