Question

In models B through D, what seems to be the relationship between the burglary rate and...

In models B through D, what seems to be the relationship between the burglary rate and the percent of the 18-64 population who are young adults (18-24)?

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 R-square 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

P-value

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

P-value

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

P-value

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

Homework Answers

Answer #1

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 P-values for each model are,

Coefficient for %young adult P-value 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.

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