In model A, it was seen that per capita income was negative and significantly (a
ID: 1164603 • Letter: I
Question
In model A, it was seen that per capita income was negative and significantly (at the 10% level) related to the burglary rate. In models E through G, the per capita income variable is
Select one:
a. still negatively related to the burglary rate, but is no longer significant at the 10% level.
b. more difficult to interpret since the adjusted R-squares in models E through G are higher with the different independent variables than in model A.
c. still significant, even at the 1% level, but the sign of the relationship has switched to being positively related to the burglary rate.
d. still negatively related to the burglary rate, and still significant even at the 1% level.
MODULE A
Regression Statistics
Multiple R
0.695384875
R Square
0.483560125
Adjusted R Square
0.448348315
44.8348315
Standard Error
149.0600243
Observations
48
ANOVA
df
SS
MS
F
Significance F
Regression
3
915389.1604
305129.7
13.7329
1.86E-06
Residual
44
977631.1977
22218.89
Total
47
1893020.358
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
724.6155159
271.9492418
2.664525
0.010736
176.5378
1272.693
176.5378
1272.693
Population
1.40401E-06
3.11351E-06
0.45094
0.654247
-4.9E-06
7.68E-06
-4.9E-06
7.68E-06
PerCapIncome
-0.012348004
0.004977038
-2.48099
0.016996
-0.02238
-0.00232
-0.02238
-0.00232
%Poverty
27.51728303
8.88092885
3.098469
0.003384
9.618947
45.41562
9.618947
45.41562
Regression Statistics
Multiple R
0.695384875
R Square
0.483560125
Adjusted R Square
0.448348315
44.8348315
Standard Error
149.0600243
Observations
48
ANOVA
df
SS
MS
F
Significance F
Regression
3
915389.1604
305129.7
13.7329
1.86E-06
Residual
44
977631.1977
22218.89
Total
47
1893020.358
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
724.6155159
271.9492418
2.664525
0.010736
176.5378
1272.693
176.5378
1272.693
Population
1.40401E-06
3.11351E-06
0.45094
0.654247
-4.9E-06
7.68E-06
-4.9E-06
7.68E-06
PerCapIncome
-0.012348004
0.004977038
-2.48099
0.016996
-0.02238
-0.00232
-0.02238
-0.00232
%Poverty
27.51728303
8.88092885
3.098469
0.003384
9.618947
45.41562
9.618947
45.41562
Explanation / Answer
D. still negatively related to the burglary rate, and still significant even at the 10% level.
This is so because in the modules E through G the coefficient of the per capita income is negative suggesting a negative relation between it and burglary rate. Also, when we see the p-values for per capita income we observe that the p values are less than 0.05 so we reject the null hypothesis that the coefficient of percapita income is zero concluding that there relationship is significant.
Please like my answer.
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.