1.What is the critical F at the .05 level (4 decimal places)?   2.Is the addition of SOUTH and URBAN statistically valuable (at the .05 significance level)?  How do you justify this conclusion?

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1.What is the critical F at the .05 level (4 decimal places)? 

 2.Is the addition of SOUTH and URBAN statistically valuable (at the .05 significance level)?  How do you justify this conclusion?  

 

BIG MODEL: R² = .520_n=126 Dependent Variable: %_BOOSTER
Coefficientsa
Unstandardized Coefficients
Std. Error
Model
B
1
(Constant)
25.0
2.0
Repub
-15.0
3.0
BIG
REGRESSION
-- Model
Summary
Educ
3.0
1.0
Repub*Educ
-1.0
0.2
South
-3.0
2.0
Model R Square
Urban
5.0
4.0
1
.520
a. Dependent Variable: %_Booster
Sig.
.000
.000
.002
.003
.214
.325
95.0% Confidence Interval for
B
Lower Bound
Upper Bound
21.0
29.0
-21.0
-9.0
1.0
5.0
-1.4
-0.6
-7.0
1.0
-3.0
13.0
Transcribed Image Text:BIG MODEL: R² = .520_n=126 Dependent Variable: %_BOOSTER Coefficientsa Unstandardized Coefficients Std. Error Model B 1 (Constant) 25.0 2.0 Repub -15.0 3.0 BIG REGRESSION -- Model Summary Educ 3.0 1.0 Repub*Educ -1.0 0.2 South -3.0 2.0 Model R Square Urban 5.0 4.0 1 .520 a. Dependent Variable: %_Booster Sig. .000 .000 .002 .003 .214 .325 95.0% Confidence Interval for B Lower Bound Upper Bound 21.0 29.0 -21.0 -9.0 1.0 5.0 -1.4 -0.6 -7.0 1.0 -3.0 13.0
small MODEL:
n=126 Dependent Variable: %_BOOSTER
Coefficientsa
95.0% Confidence Interval for
B
Unstandardized Coefficients
small
regression
Model
B
Std. Error
Sig.
Lower Bound Upper Bound
1
(Constant)
30.0
3.0
-- Model
.000
24.0
36.0
Repub
-20.0
2.0
Summary
.000
-24.0
-16.0
Educ
3.0
0.3
.000
2.4
3.6
Model R Square
Repub*Educ
-1.0
0.1
.000
-1.2
-0.8
1
.510
a. Dependent Variable: %_Booster
DEPENDENT VARIABLE -- %_BOOSTER: = Percent of adults in county who received a COVID-19 booster
shot;
REPUB: = 1 if a majority of registered voters in county are Republicans, o otherwise;
EDUC: = mean number of years of education of adults age 25 and above;
REPUB*EDUC: = interaction (product) of REPUB and EDUC;
SOUTH: = 1 if county is in the southern part of the U.S., o otherwise;
URBAN: = 1 if county is primarily urban, o otherwise
R² = .510
Transcribed Image Text:small MODEL: n=126 Dependent Variable: %_BOOSTER Coefficientsa 95.0% Confidence Interval for B Unstandardized Coefficients small regression Model B Std. Error Sig. Lower Bound Upper Bound 1 (Constant) 30.0 3.0 -- Model .000 24.0 36.0 Repub -20.0 2.0 Summary .000 -24.0 -16.0 Educ 3.0 0.3 .000 2.4 3.6 Model R Square Repub*Educ -1.0 0.1 .000 -1.2 -0.8 1 .510 a. Dependent Variable: %_Booster DEPENDENT VARIABLE -- %_BOOSTER: = Percent of adults in county who received a COVID-19 booster shot; REPUB: = 1 if a majority of registered voters in county are Republicans, o otherwise; EDUC: = mean number of years of education of adults age 25 and above; REPUB*EDUC: = interaction (product) of REPUB and EDUC; SOUTH: = 1 if county is in the southern part of the U.S., o otherwise; URBAN: = 1 if county is primarily urban, o otherwise R² = .510
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Is the addition of SOUTH and URBAN statistically valuable (at the .05 significance level)?  How do you justify this conclusion?

 

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