Department of Agriculture is concerned about the number of acres of farmland being withdrawn from farming. The department would like to propose new legislation to prevent this but wants to show the legislature what would happen if it does not act. Drew Johnson, the department’s statistician, regresses the number of acres used for farming in the state on time. Johnson finds the following: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .943a .890 .795 3.2875 a. Predictors: (Constant), Number of Years ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1378.458 1 1378.458 141.149 .000a Residual 478.567 49 9.766 Total 1857.025 50 a. Predictors: (Constant), Number of Years b. Dependent Variable: Acres (in Millions)
Department of Agriculture is concerned about the number of acres of farmland being withdrawn from farming. The department would like to propose new legislation to prevent this but wants to show the legislature what would happen if it does not act. Drew Johnson, the department’s statistician, regresses the number of acres used for farming in the state on time. Johnson finds the following:
|
Model Summary |
||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.943a |
.890 |
.795 |
3.2875 |
|
a. Predictors: (Constant), Number of Years |
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
1378.458 |
1 |
1378.458 |
141.149 |
.000a |
|
Residual |
478.567 |
49 |
9.766 |
|
|
|
|
Total |
1857.025 |
50 |
|
|
|
|
|
a. Predictors: (Constant), Number of Years |
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|
b. Dependent Variable: Acres (in Millions) |
|
Coefficientsa |
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|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
2.743 |
.357 |
|
7.683 |
.000 |
|
Year |
-.027 |
.0007 |
-.025 |
-38.571 |
.000 |
|
|
a. Dependent Variable: Acres (in Millions) |
- What is the IV and DV? How strong is the relationship?
- From the results shown above, write the regression equation.
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