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:: Auto Correlation Function ::

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Server date: May 26, 2017, 4:44 am

Auto Correlation Function (ACF) of timeseries Airline.ds by timelag (k)
Degree of non-seasonal differencingd0
Degree of seasonal differencingD0
Box-Cox transformation parameterL1
Standard Error of ACF 0.171499

Time lagAcf(k)T-StatSig.
1-0.27189-1.585377
20.5506523.210828***
3-0.173099-1.009329
40.3868692.255813**
5-0.12912-0.752893
60.1727841.007493
7-0.048829-0.284718
8-0.046486-0.271056
9-0.044164-0.257521
10-0.139263-0.812037
110.0083630.048764
12-0.280654-1.63648
130.0651150.37968
14-0.367117-2.140639**
15-0.002334-0.01361
16-0.200542-1.16935
17-0.065956-0.384588
18-0.050665-0.295427
19-0.11378-0.663445
200.0438530.255706
21-0.096434-0.562301
220.0892480.520399
23-0.053152-0.309928
240.1577510.91984
25-0.043005-0.250761
260.0878450.512219
27-0.062432-0.364038
280.1171260.682955
29-0.01848-0.107759
300.0229440.133784
31-0.021847-0.127386
320.0204340.119149
330.0062660.036536
3400
3500
3600
3700
computations based on Sample Auto Correlation Formula


Warnings and Comments based on Artificial Intelligence
Warning: more than 5% of all ACF coefficients are significantly different from zero at the 5% level.
Warning: more than 1% of all ACF coefficients are significantly different from zero at the 1% level.




Auto Correlation Function of time series.

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From this analysis it can be concluded that the time series under investigation should be differenced to induce stationarity.
Last computationDelete history
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Fri, 26 May 2017 04:44:19 +0100Auto Correlation FunctionPrint | Word | Excel | Blog this | Delete
Fri, 26 May 2017 04:44:19 +0100Start of session-
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Wessa, P. (2017), Free Statistics Software, Office for Research Development and Education,
version 1.1.23-r7, URL http://www.wessa.net/

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