1 Estimate a linear regression model on BurglaryRT using PercentRural as the independent variable Variables Entered Removed a Model Variables Entered Variables Removed Method 1 PercentRural b Enter a Dependent Variable Burglary Rate per 100K b All requested variables entered Model Summary Model R R Square Adjusted R Square Std Error of the Estimate 1 051 a 003 018 257 70359 a Predictors (Constant), PercentRural ANOVA a Model Sum of Squares df Mean Square F Sig 1 Regression 8371 841 1 8371 841 126 724 b Residual 3187734 656 48 66411 139 Total 3196106 497 49 a Dependent Variable Burglary Rate per 100K b Predictors (Constant), PercentRural Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig B Std Error Beta 1 (Constant) 667 967 76 609 8 719

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1.Estimate a linear regression model on BurglaryRT using PercentRural as the independent variable. Variables Entered/Removed a Model Variables Entered Variables Removed Method 1 PercentRural b

1.Estimate a linear regression model on BurglaryRT using PercentRural as the independent variable.

Variables Entered/Removed^a
Model	Variables Entered	Variables Removed	Method
1	PercentRural^b	.	Enter
a. Dependent Variable: Burglary Rate per 100K
b. All requested variables entered.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.051^a	.003	-.018	257.70359
a. Predictors: (Constant), PercentRural

ANOVA^a
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	8371.841	1	8371.841	.126	.724^b
Residual	3187734.656	48	66411.139
Total	3196106.497	49
a. Dependent Variable: Burglary Rate per 100K
b. Predictors: (Constant), PercentRural

Coefficients^a
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	667.967	76.609		8.719	<.001
PercentRural	.918	2.584	.051	.355	.724
a. Dependent Variable: Burglary Rate per 100K

Put together a few sentences to summarize your regression results (hint: interpret your intercept, regression coefficient, R-squared, and hypothesis testing results).

2.Estimate a linear regression model on MVTheftRT using PercentRural as the independent variable.

Variables Entered/Removed^a
Model	Variables Entered	Variables Removed	Method
1	PercentRural^b	.	Enter
a. Dependent Variable: Motor Vehicle Rate per 100K
b. All requested variables entered.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.581^a	.337	.324	76.78737
a. Predictors: (Constant), PercentRural

ANOVA^a
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	144064.671	1	144064.671	24.433	<.001^b
Residual	283022.379	48	5896.300
Total	427087.050	49
a. Dependent Variable: Motor Vehicle Rate per 100K
b. Predictors: (Constant), PercentRural

Coefficients^a
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	328.245	22.827		14.380	<.001
PercentRural	-3.806	.770	-.581	-4.943	<.001
a. Dependent Variable: Motor Vehicle Rate per 100K

Put together a few sentences to summarize your regression results (hint: interpret your intercept, regression coefficient, R-squared, and hypothesis testing results).