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The Null Hypothesis - H0: There is no autocorrelation
The Alternative Hypothesis - H1: There is at least first order autocorrelation
Rejection Criteria: Reject H0 if LBQ1 >
Autocorrelation Function: RESI1
Lag ACF T LBQ
1 0.0081553 0.32 0.10
2 0.0065510 0.26 0.17
3 -0.0279832 -1.09 1.36
4 -0.0079441 -0.31 1.46
5 0.0254074 0.99 2.44
There are 83 lags but the first 5 have been used identify whether there is auto correlation present:
Lag
LBQ
Chi-Squared
Interpretation
1
0.10
= 3.84
Since LBQ = 0.10 < 3.84 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
2
0.17
= 5.99
Since LBQ = 0.17 < 5.99 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
3
1.36
= 7.81
Since LBQ = 1.36 < 7.81 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
4
1.46
= 9.48
Since LBQ = 1.46 < 9.48 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
5
2.44
= 11.07
Since LBQ = 2.44 < 11.07 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
The graph for Partial Autocorrelation Function for RES1 shows that there is no autocorrelation even though there are alternating spikes because they fall inside the 5% significance
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