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Model Summary Change Statistics Adjusted R Std. Error of the Model R Square Change F Change R R Square Square Estimate df1 df2 Sig. F Change 268 .072 .067 5.49167 .072 13.333 1 172 .000 443b .196 .187 5.12637 .124 26.387 1 171 .000 a. Predictors: (Constant), noncounshr b. Predictors: (Constant), noncounshr, LF_M Answer the following: 1) Why is the df2 for model 2 171? (Show the df formula and how you end up with df2 equals 171) 2) How much variance is accounted for by LF_M? 3)Of model 1 and model 2, which is the full model and which is the reduced model? 4) Is there a significant difference between the full and the reduced models? How do you know?

Model Summary Change Statistics Adjusted R Std. Error of the Model R Square Change F Change R R Square Square Estimate df1 df2 Sig. F Change 268 .072 .067 5.49167 .072 13.333 1 172 .000 443b .196 .187 5.12637 .124 26.387 1 171 .000 a. Predictors: (Constant), noncounshr b. Predictors: (Constant), noncounshr, LF_M Answer the following: 1) Why is the df2 for model 2 171? (Show the df formula and how you end up with df2 equals 171) 2) How much variance is accounted for by LF_M? 3)Of model 1 and model 2, which is the full model and which is the reduced model? 4) Is there a significant difference between the full and the reduced models? How do you know?

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter3: Functions And Graphs
Section3.3: Lines
Problem 76E
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Model Summary Change Statistics Adjusted R Std. Error of the Model R R Square Square Estimate R Square Change F Change df1 df2 Sig. F Change 1 .268 .072 .067 5.49167 .072 13.333 172 .000 .443 196 .187 5.12637 .124 26.387 171 .000 a. Predictors: (Constant), nonceunshr b. Predictors: (Constant), noncounshr. LF_M Answer the following: 1) Why is the df2 for model 2 171? (Show the df formula and how you end up with df2 equals 171) 2) How much variance is accounted for by LF_M? 3)Of model 1 and model 2, which is the full model and which is the reduced model? 4) Is there a significant difference between the full and the reduced models? How do you know?
Transcribed Image Text:Model Summary Change Statistics Adjusted R Std. Error of the Model R R Square Square Estimate R Square Change F Change df1 df2 Sig. F Change 1 .268 .072 .067 5.49167 .072 13.333 172 .000 .443 196 .187 5.12637 .124 26.387 171 .000 a. Predictors: (Constant), nonceunshr b. Predictors: (Constant), noncounshr. LF_M Answer the following: 1) Why is the df2 for model 2 171? (Show the df formula and how you end up with df2 equals 171) 2) How much variance is accounted for by LF_M? 3)Of model 1 and model 2, which is the full model and which is the reduced model? 4) Is there a significant difference between the full and the reduced models? How do you know?
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