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Strongest predictor
The coefficient
in the regression analysis for Household income in 2014-2015 is 5144.5.
a.
The value of significance factor in the
regression analysis of % single parent 2012-2016 is above 0.005 that is 0.009.
b.
The regression analysis calculated for Population
density in 2010 showed value of significance factor is 
.
c.
In case of regression analysis of Income in 1990
the value of significance factor is below than 0.005 that is measured as 0.
d.
Like the income analysis the significance factor
for Median rent 2012-2016 is 0.
e.
The regression analysis of Census response rate
in 2010 shows significance factor as zero. On the basis of these analysis the
maximum predictive parameter is observed for percentage single parent
2012-2016.
Consistency
In the
regression analysis 5 parameters were considered to predict the household
income. The value of significance factor in the regression analysis of % single
parent 2012-2016 is above 0.005 that is 0.009 therefore only this result is
valuable. The result is consistent with the regression outcomes of the
analysis.
|
SUMMARY OUTPUT |
||||||||
|
Regression Statistics |
||||||||
|
Multiple R |
0.082403245 |
|||||||
|
R Square |
0.006790295 |
|||||||
|
Adjusted R Square |
0.005794096 |
|||||||
|
Standard Error |
14461.97686 |
|||||||
|
Observations |
999 |
|||||||
|
ANOVA |
||||||||
|
|
df |
SS |
MS |
F |
Significance F |
|||
|
Regression |
1 |
1425601545 |
1425601545 |
6.816207973 |
0.009168997 |
|||
|
Residual |
997 |
2.08521E+11 |
209148774.6 |
|||||
|
Total |
998 |
2.09947E+11 |
|
|
|
|||
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
Intercept |
41772.21188 |
1102.545418 |
37.88706677 |
2.6616E-195 |
39608.63602 |
43935.78773 |
39608.63602 |
43935.78773 |
|
Fraction_Single_Parents_in_2012-16 |
-5095.747473 |
1951.805248 |
-2.610786849 |
0.009168997 |
-8925.865155 |
-1265.629792 |
-8925.865155 |
-1265.629792 |
strength and weakness
The analysis
predicts the strength and weakness of the results a dhow it can be used to
reduce the poverty. Different policy implications can be used to image the
research from different perspectives. The report can be used to overcome the
issues faced by the average families in the selected area. There are different
possibilities to reduce poverty along with variety of disciplines. The best
solution is to maintain the competence even under the adverse conditions. The
maximize optimal response is used to overcome the challenges of low-income
families.
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