Please provide a narrative discussion of both tables. Include Eta, the Levene te
ID: 3253433 • Letter: P
Question
Please provide a narrative discussion of both tables. Include Eta, the Levene test, and the observed change in the F-value of current family income when moving from a one-way to a two-way analysis:
Table 1:
Dependent Variable: life satisfaction
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Partial Eta Squared
Corrected Model
18.618a
6
3.103
4.193
.001
.102
Intercept
1934.535
1
1934.535
2613.859
.000
.922
income
18.618
6
3.103
4.193
.001
.102
Error
164.304
222
.740
Total
5492.225
229
Corrected Total
182.922
228
a. R Squared = .102 (Adjusted R Squared = .078)
Table 2:
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Partial Eta Squared
Corrected Model
25.957a
13
1.997
2.735
.001
.142
Intercept
1765.270
1
1765.270
2417.945
.000
.918
income
18.663
6
3.110
4.260
.000
.106
sex
1.998
1
1.998
2.737
.100
.013
income * sex
4.395
6
.733
1.003
.424
.027
Error
156.965
215
.730
Total
5492.225
229
Corrected Total
182.922
228
a. R Squared = .142 (Adjusted R Squared = .090)
Dependent Variable: life satisfaction
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Partial Eta Squared
Corrected Model
18.618a
6
3.103
4.193
.001
.102
Intercept
1934.535
1
1934.535
2613.859
.000
.922
income
18.618
6
3.103
4.193
.001
.102
Error
164.304
222
.740
Total
5492.225
229
Corrected Total
182.922
228
a. R Squared = .102 (Adjusted R Squared = .078)
Explanation / Answer
Any regression analysis must to include a significance criteria, according with these criteria, only is included the variables who brings significance manners to the model.
F test shows the critical level associated to correlation coefficient, to contrast the independence hypothesis less than 0.05(input probability), if the critical level Is bigger than 0.10(output probability) is going out the model. For F value, a variable can be part of the regression model if the value of statistical F used to contrast the impendence hypothesis is bigger than 3.84(input value) and stays out of the model if the value of statistical F is less than 2.71(output value).
The regression results shows that R squared and adjusted R squared explaining 10.2 and 14.2 of the variance for both models. The squared sum determinates the minimum of the squared distance sum between the sample data and the prognosticated equation data.
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