WEInsurU is attempting to predict how long customers will live based on how long their parents and grandparents have lived. Here is the results of the excel analysis.
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A |
B |
C |
D |
E |
F |
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1 |
SUMMARY OUTPUT |
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2 |
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3 |
Regression Statistics |
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4 |
Multiple R |
0.8608 |
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5 |
R Square |
0.7411 |
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6 |
Adjusted R Square |
0.7301 |
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7 |
Standard Error |
2.66 |
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8 |
Observations |
100 |
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9 |
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10 |
ANOVA |
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11 |
df |
SS |
MS |
F |
Significance F |
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12 |
Regression |
4 |
1930 |
482.38 |
67.97 |
0.00000 |
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13 |
Residual |
95 |
674 |
7.10 |
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14 |
Total |
99 |
2604 |
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15 |
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16 |
Coefficients |
Standard Error |
t Stat |
P-Value |
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17 |
Intercept |
3.24 |
5.42 |
0.60 |
0.5512 |
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18 |
Mother |
0.451 |
0.0545 |
8.27 |
0.0000 |
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19 |
Father |
0.411 |
0.0498 |
8.26 |
0.0000 |
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20 |
Gmother(s) |
0.0166 |
0.0661 |
0.25 |
0.8028 |
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21 |
Gfather(s) |
0.0869 |
0.0657 |
1.32 |
0.1890 |
a. What is the regression equation?
b. What does the significance level of 0.00000 for F mean?
c. Why is the adjusted R-square lower than the R-square?
d. Which, if any, of the coefficients are statistically significant? How do you know?
d. If an individual’s mother lived to be 86, their father lived to be 73, and grandmothers averaged 77 and the grandfathers lived to be 68 when they died. How long would you expect this individual to live?
