In looking at models E and G, consistent with theory and logic, the burglary rat
ID: 1164605 • Letter: I
Question
In looking at models E and G, consistent with theory and logic, the burglary rate is negatively related to average rainfall and positively related to the number of sunny days.
Select one:
True
False
MODULE E
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.68701
R Square
0.471982
Adjusted R Square
0.435981
Standard Error
150.7216
Observations
48
ANOVA
df
SS
MS
F
Significance F
Regression
3
893472.2
297824.1
13.11018
3E-06
Residual
44
999548.1
22717
Total
47
1893020
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
1976.292
385.0644
5.132367
6.22E-06
1200.245
2752.338
1200.245
2752.338
PerCapIncome
-0.01969
0.004006
-4.91553
1.27E-05
-0.02777
-0.01162
-0.02777
-0.01162
Rain
5.189802
1.736089
2.989364
0.004563
1.690945
8.688659
1.690945
8.688659
MedianAge
-21.2417
10.65279
-1.99401
0.052371
-42.711
0.227536
-42.711
0.227536
MODULE F
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.781322
R Square
0.610464
Adjusted R Square
0.583905
Standard Error
129.4568
Observations
48
ANOVA
df
SS
MS
F
Significance F
Regression
3
1155621
385207.1
22.985
4.19E-09
Residual
44
737398.9
16759.07
Total
47
1893020
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
369.7955
402.3406
0.919111
0.363049
-441.069
1180.66
-441.069
1180.66
PerCapIncome
-0.01358
0.003704
-3.6655
0.000661
-0.02104
-0.00611
-0.02104
-0.00611
Temp
14.40017
2.733339
5.268342
3.96E-06
8.891483
19.90885
8.891483
19.90885
MedianAge
0.089994
8.224318
0.010942
0.991319
-16.485
16.66502
-16.485
16.66502
MODULE G
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.659317
R Square
0.434698
Adjusted R Square
0.382112
Standard Error
157.7551
Observations
48
ANOVA
df
SS
MS
F
Significance F
Regression
4
822892.9
205723.2
8.266398
4.88E-05
Residual
43
1070127
24886.68
Total
47
1893020
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
905.8806
528.7346
1.713299
0.09386
-160.414
1972.176
-160.414
1972.176
PerCapIncome
-0.02046
0.004332
-4.72343
2.49E-05
-0.0292
-0.01173
-0.0292
-0.01173
Sun
1.753156
1.000744
1.751854
0.086929
-0.26504
3.771349
-0.26504
3.771349
MedianAge
4.701205
11.43281
0.411203
0.682966
-18.3552
27.75765
-18.3552
27.75765
%Metro
159.6372
127.5231
1.25183
0.217399
-97.5375
416.812
-97.5375
416.812
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.68701
R Square
0.471982
Adjusted R Square
0.435981
Standard Error
150.7216
Observations
48
ANOVA
df
SS
MS
F
Significance F
Regression
3
893472.2
297824.1
13.11018
3E-06
Residual
44
999548.1
22717
Total
47
1893020
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
1976.292
385.0644
5.132367
6.22E-06
1200.245
2752.338
1200.245
2752.338
PerCapIncome
-0.01969
0.004006
-4.91553
1.27E-05
-0.02777
-0.01162
-0.02777
-0.01162
Rain
5.189802
1.736089
2.989364
0.004563
1.690945
8.688659
1.690945
8.688659
MedianAge
-21.2417
10.65279
-1.99401
0.052371
-42.711
0.227536
-42.711
0.227536
Explanation / Answer
The burglary rate is negatively related to average rainfall is false because the coefficient of rainfall in module E is positive thereby showing a positive relation. So if average rainfall increases by 1 unit the burgrlary rate will increase by 5.189 units.
and
The burglary rate is positively related to the number of sunny days is true because the coefficient of sunny days in module G is positive thereby showing a positive relation. So if number of sunny days increases by 1 unit the burglary rate will increase by 1.753 units.
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