City Code |
% Under 21 |
# of Fatals |
1 |
16 |
3.822 |
2 |
7 |
0 |
3 |
5 |
0.46 |
4 |
10 |
2.033 |
5 |
14 |
2.282 |
6 |
10 |
0.621 |
7 |
12 |
1.511 |
8 |
12 |
1.824 |
9 |
13 |
1.209 |
10 |
11 |
2.034 |
11 |
8 |
1.321 |
12 |
14 |
2.468 |
13 |
14 |
2.455 |
14 |
18 |
3.787 |
15 |
16 |
3.508 |
16 |
10 |
1.113 |
17 |
7 |
1.144 |
18 |
15 |
3.084 |
19 |
18 |
4.16 |
20 |
16 |
3.688 |
21 |
8 |
0.782 |
22 |
9 |
1.307 |
23 |
14 |
2.016 |
24 |
13 |
3.542 |
25 |
13 |
3.137 |
26 |
16 |
3.832 |
27 |
11 |
1.187 |
28 |
10 |
2.168 |
29 |
7 |
2.241 |
30 |
11 |
1.02 |
31 |
9 |
0.548 |
32 |
9 |
0.396 |
10. What is the estimated increase in number of fatal accidents per 1000 licenses due to a 1% increase in the percentage of drivers under 21 (ie. the slope)?
11. What is the standard deviation of the estimated slope?
12. What is the estimated number of fatal accidents per 1000 licenses if there were no drivers under the age of 21 (ie. the intercept)?
13. What percentage of the variation in accident fatalities can be explained by the linear relationship with drivers under 21 (ie. 100 times the unadjusted coefficient of determination = 100 R2)?
10. 0.2951
11. 0.0342
12. -1.4456
13. 71.2%
r² | 0.712 | |||||
r | 0.844 | |||||
Std. Error | 0.653 | |||||
n | 32 | |||||
k | 1 | |||||
Dep. Var. | # of Fatals | |||||
ANOVA table | ||||||
Source | SS | df | MS | F | p-value | |
Regression | 31.6995 | 1 | 31.6995 | 74.30 | 1.29E-09 | |
Residual | 12.7992 | 30 | 0.4266 | |||
Total | 44.4988 | 31 | ||||
Regression output | confidence interval | |||||
variables | coefficients | std. error | t (df=30) | p-value | 95% lower | 95% upper |
Intercept | -1.4456 | |||||
% Under 21 | 0.2951 | 0.0342 | 8.620 | 1.29E-09 | 0.2252 | 0.3650 |
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