Questions we will answer ar as follows:
1.What are the primary determinants of property crimes in the United States?
2.What would you wish to know about property crime rates that tail endnot be answered
by this data set?
3.How does population density affect property crime rates? Is this expected?
Multiple regression analysis can be used to impersonate property crime in United States. The
regression model suggested is of the form.
Crimes = b0+b1Pincome + b2Dropout +b3Pubaid+b4density+ b5Kids+ b6Prescip+ b7unemploy+ b8 Urban
present bi (i =0,1,..8) are known as the regression coefficients . They are estimated by the method of least squares. bi measure the bear on of unit change in the independent variable on crime. The estimated values of regression coefficients are given as follows:
Variablescoefficientsstd. wrongdoingt (df=41)p-value
Intercept-642.50301024.03-0.627.5339
PINCOME-0.01830.0773-0.237.8136
DROPOUT81.292621.98583.698.0006
PUBAID-113.714478.7000-1.445.1561
DENSITY-1.98410.7299-2.718.0096
KIDS1.10381.44850.762.4504
PRECIP1.582111.16360.142.8880
UNEMPLOY-46.383079.6479-0.582.5635
URBAN64.
391510.93035.8916.18E-07
Therefor the model can be written as follows:
Crimes = -642.5030 -0.0183 Pincome + 81.2926 Dropout -113.7144 Pubaid -1.9841 Density +1.1038 Kids+ 1.5821 Prescip - 46.3830 Unemploy+ 64.3915Urban
The adequacy of the model is determined by the R2 value (Coefficient of determination) . R2 measure the section of variability in crime that can be explained by the regression model.
Model Summary
R²0.690
Adjusted R²0.630
R0.831
Std. Error749.394
Thus 69.0 % variability in the model can be explained using the regression model.
The significance of regression coefficients are tested using a Student t...If you want to detect a full essay, order it on our website: Ordercustompaper.com
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