Net Income to Net Worth Net Worth to Total Liabilities
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Regression analysis is used to test the hypothesized relationship among variables; the result of each hypothesis is summarized here. All
result above measure with α = 0.05. a. Autocorrelation test
Examining autocorrelation in a research is aimed to recognize whether there is any correlation between intruder
variables e
t
or not, in certain period with the previous intruder variable e
t – 1
. To see the correlation between residuals, we examines Durbin Watson test. The simpler way to examines
autocorrelation between one variable and others is by seeing Durbin Watson’s number. A good model is model which the data has no
correlation between one residual and the other residuals. Since this research has the number of samples n 40, the
significance level α 0.05, and predictor variables k 9, we can find the upper and lower level of Durbin Watson for this research.
From the table of Durbin Watson, this research has Durbin Watson upper level d
u
for 1.67 and Durbin Watson lower level d
l
for 1.42.
This research has done the autocorrelation test through SPSS v.16. The table 4.12 shows that the number of Durbin Watson in
this research is 1.857.
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Since the Durbin Watson formula is 4-d dL , where 4 – 2.025 2.072, thus, it can be concluded that there is not occur
a correlation between residuals in this research. Or, in other way, the model in this research has passed the autocorrelation test.
Table 4.11 Model Sumary