Christina Sweet
1. “Crazy t-test”
ANOVA
V1
Sum of Squares
Between Groups
df
Mean Square
F
1.618
1
1.618
Within Groups
957.941
61
15.704
Total
959.559
62
Sig.
.103
.749
Independent Samples Test
Levene's Test for
Equality of
Variances
t-test for Equality of Means
95% Confidence
Interval of the
Sig. (2-
F
V1
Equal variances
Sig.
.721
t
.399
df
.321
tailed)
Mean
Difference
Std. Error
Difference Difference
Lower
Upper
61
.749
.32059
.99866 -1.67636
2.31754
.321 60.922
.749
.32059
.99757 -1.67422
2.31541
assumed
Equal variances
not assumed
The p-values obtained from the ANOVA and t-test are the same p=.749 >.05 and therefore a significant
difference was not found with either test.
2. Post Hoc
Multiple Comparisons
Dependent Variable:Measures
95% Confidence Interval
Mean
(I) Group
Tukey HSD
1
2
(J) Group
Difference (I-J)
Std. Error
Sig.
Lower Bound
Upper Bound
2
5.0871875*
1.6876535
.016
.692179
9.482196
3
-.8340625
1.6876535
.960
-5.229071
3.560946
4
9.0881250*
1.6876535
.000
4.693116
13.483134
1
-5.0871875*
1.6876535
.016
-9.482196
-.692179
3
-5.9212500*
1.6876535
.003
-10.316259
-1.526241
4
4.0009375
1.6876535
.088
-.394071
8.395946
3
4
Scheffe
1
2
3
4
1
.8340625
1.6876535
.960
-3.560946
5.229071
2
5.9212500*
1.6876535
.003
1.526241
10.316259
4
9.9221875*
1.6876535
.000
5.527179
14.317196
1
-9.0881250*
1.6876535
.000
-13.483134
-4.693116
2
-4.0009375
1.6876535
.088
-8.395946
.394071
3
-9.9221875*
1.6876535
.000
-14.317196
-5.527179
2
5.0871875*
1.6876535
.032
.303919
9.870456
3
-.8340625
1.6876535
.970
-5.617331
3.949206
4
9.0881250*
1.6876535
.000
4.304856
13.871394
1
-5.0871875*
1.6876535
.032
-9.870456
-.303919
3
-5.9212500*
1.6876535
.008
-10.704519
-1.137981
4
4.0009375
1.6876535
.138
-.782331
8.784206
1
.8340625
1.6876535
.970
-3.949206
5.617331
2
5.9212500*
1.6876535
.008
1.137981
10.704519
4
9.9221875*
1.6876535
.000
5.138919
14.705456
1
-9.0881250*
1.6876535
.000
-13.871394
-4.304856
2
-4.0009375
1.6876535
.138
-8.784206
.782331
3
-9.9221875*
1.6876535
.000
-14.705456
-5.138919
*. The mean difference is significant at the 0.05 level.
The difference between Tukey and Scheffe is that Scheffe is more flexible and more rigorous than Tukey,
but Tukey is more powerful.
3. Correlation Bank loan
Correlations
Years at current address
Pearson Correlation
Years at current
Debt to income
address
ratio (x100)
1
Sig. (2-tailed)
N
Debt to income ratio (x100)
Pearson Correlation
-.033
.337
850
850
-.033
1
Sig. (2-tailed)
.337
N
850
850
The correlation is weak and not significant sig. .,337> .05 and a -.033 person correlation is not very
strong relationship.
Model Summary
Model
1
R
.033a
R Square
.001
Adjusted R
Std. Error of the
Square
Estimate
.000
a. Predictors: (Constant), Years at current address
6.71975
R^2 is known as the coefficient of
determination, it is the amount
of variance in one dependent
variable that can be explained by
the independent.
According to the R^2 less than
1% of the Debt to Income Ratio
can be explained by Years at
current Address.
The amount of variance is small so years at current address does not explain a lot of the
variance in Debt to Income Ratio.
5.
Correlations
Spearman's rho
Level of education
Correlation Coefficient
Debt to income
education
ratio (x100)
1.000
.009
.
.801
N
850
850
Correlation Coefficient
.009
1.000
Sig. (2-tailed)
.801
.
N
850
850
Sig. (2-tailed)
Debt to income ratio (x100)
Level of
I do not think there is a strong correlation between level of education and the debt income ratio, as
seen with a correlation coefficient of .09, which is very weak and not even significant sig.=.801>.05.