In models B through D, what seems to be the relationship between the burglary rate and the percent of the 1864 population who are young adults (1824)?
Select one:
a. It is difficult to describe the relationship; the young adult variables were all significant at 5% in models B, C, and D, but the signs and sizes of the coefficients were very different between models.
b. Conclusions about the relationship between young adults and the burglary rate are difficult to draw since the unemployment rate variable is consistently positive and significant, which reduces the reliability of the estimates for the young adult variables.
c. The burglary rate seems to increase as the proportion of young adults increases (models B, C, and D), though the effect is only significant (at the 10% level) for young adult males (model C).
d. We can be confident that the relationship between the burglary rate and proportion of young adults is negative, given the signs of the young adult coefficients in all models and the high adjusted Rsquare values.
MODULE B
SUMMARY OUTPUT 

Regression Statistics 

Multiple R 
0.428911 

R Square 
0.183965 

Adjusted R Square 
0.147696 

Standard Error 
185.2789 

Observations 
48 

ANOVA 

df 
SS 
MS 
F 
Significance F 

Regression 
2 
348248.8263 
174124.4 
5.072335 
0.010315 

Residual 
45 
1544771.532 
34328.26 

Total 
47 
1893020.358 

Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 

Intercept 
480.503 
498.0290621 
0.96481 
0.339797 
1483.58 
522.5791 
1483.58 
522.5791 

%Unemploy 
60.64388 
19.15148576 
3.166537 
0.002769 
22.07081 
99.21696 
22.07081 
99.21696 

%young 
4186.85 
2696.892719 
1.552472 
0.127555 
1244.97 
9618.671 
1244.97 
9618.671 
MODULE C
SUMMARY OUTPUT 

Regression Statistics 

Multiple R 
0.444877 

R Square 
0.197916 

Adjusted R Square 
0.162267 

Standard Error 
183.6883 

Observations 
48 

ANOVA 

df 
SS 
MS 
F 
Significance F 

Regression 
2 
374658.3 
187329.2 
5.551912 
0.006998 

Residual 
45 
1518362 
33741.38 

Total 
47 
1893020 

Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 

Intercept 
603.329 
499.929 
1.20683 
0.233803 
1610.24 
403.5793 
1610.24 
403.5793 

%Unemploy 
61.16653 
18.73611 
3.264634 
0.002098 
23.43007 
98.90299 
23.43007 
98.90299 

%youngmale 
4794.899 
2665.975 
1.798553 
0.078799 
574.651 
10164.45 
574.651 
10164.45 
MODULE D
SUMMARY OUTPUT 

Regression Statistics 

Multiple R 
0.413764 

R Square 
0.1712 

Adjusted R Square 
0.134365 

Standard Error 
186.7223 

Observations 
48 

ANOVA 

df 
SS 
MS 
F 
Significance F 

Regression 
2 
324085.9 
162042.9 
4.647697 
0.014626 

Residual 
45 
1568934 
34865.21 

Total 
47 
1893020 

Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 

Intercept 
338.182 
484.4083 
0.69813 
0.488686 
1313.83 
637.4666 
1313.83 
637.4666 
%Unemploy 
59.26618 
19.44323 
3.048165 
0.003847 
20.1055 
98.42685 
20.1055 
98.42685 
%youngfemale 
3454.179 
2664.948 
1.296153 
0.201531 
1913.3 
8821.659 
1913.3 
8821.659 
Option C is correct
The burglary rate seems to increase as the proportion of young adults increases (models B, C, and D), though the effect is only significant (at the 10% level) for young adult males (model C).
Explanation: The coefficient for % yound adult and Pvalues for each model are,
Coefficient for %young adult  Pvalue  Significance level = 0.10  Significance  
Model B  4186.85  0.127555  >  0.1  Not Significant 
Model C  4794.899  0.078799  <  0.1  Significant 
Model D  3454.179  0.201531  >  0.1  Not Significant 
The only coefficient for % young male adult is significant at 10 % significant level
All the coefficients are positive hence burglary will increase for increase in % young adult.
Get Answers For Free
Most questions answered within 1 hours.