Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 19 Dec 2010 19:35:13 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t12927872970nk769pym1vjzz6.htm/, Retrieved Sun, 05 May 2024 08:26:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112702, Retrieved Sun, 05 May 2024 08:26:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Paper: Partial Au...] [2010-12-19 15:09:48] [48146708a479232c43a8f6e52fbf83b4]
- R  D    [(Partial) Autocorrelation Function] [Paper: Partial au...] [2010-12-19 19:35:13] [6f3869f9d1e39c73f93153f1f7803f84] [Current]
-   P       [(Partial) Autocorrelation Function] [Paper: Partial au...] [2010-12-19 19:55:20] [48146708a479232c43a8f6e52fbf83b4]
-   P         [(Partial) Autocorrelation Function] [Paper: Partial au...] [2010-12-21 07:19:38] [48146708a479232c43a8f6e52fbf83b4]
-   P         [(Partial) Autocorrelation Function] [Paper: Partial au...] [2010-12-21 07:40:29] [48146708a479232c43a8f6e52fbf83b4]
-   P         [(Partial) Autocorrelation Function] [Paper: Partial au...] [2010-12-21 07:58:08] [48146708a479232c43a8f6e52fbf83b4]
-   P       [(Partial) Autocorrelation Function] [Paper: Partial au...] [2010-12-19 20:01:00] [48146708a479232c43a8f6e52fbf83b4]
Feedback Forum

Post a new message
Dataseries X:
608
651
691
627
634
731
475
337
803
722
590
724
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
706
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858
775
785
1006
789
734
906
532
387
991
841
892
782




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112702&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112702&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112702&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1316271.20640.115529
2-0.275348-2.52360.006749
30.187541.71880.044664
4-0.0034-0.03120.487609
5-0.03282-0.30080.382154
60.2055531.88390.031517
7-0.03617-0.33150.370545
80.0618260.56660.286235
90.1664151.52520.06548
10-0.298143-2.73250.00383
110.0769380.70520.241334
120.6926036.34780
130.0202490.18560.426609
14-0.298069-2.73180.003838
150.0475430.43570.332072
16-0.038677-0.35450.361935
17-0.056456-0.51740.30311
180.059910.54910.292202
19-0.090459-0.82910.204707
20-0.021404-0.19620.422476
210.0229380.21020.417
22-0.296758-2.71980.003968
23-0.001621-0.01490.49409
240.5025684.60617e-06
250.0385470.35330.362378
26-0.296315-2.71580.004013
27-0.029725-0.27240.392978
28-0.059779-0.54790.292612
29-0.115395-1.05760.146631
300.0062070.05690.477385
31-0.0727-0.66630.25352
32-0.061713-0.56560.286584
330.0282030.25850.398334
34-0.190874-1.74940.041938
35-0.024605-0.22550.411065
360.4076933.73660.00017
370.0441510.40460.343383
38-0.26143-2.39610.009397
39-0.028095-0.25750.398715
40-0.042708-0.39140.348236
41-0.082145-0.75290.226816
420.0658690.60370.273836
43-0.039298-0.36020.359813
44-0.043554-0.39920.345386
450.0829410.76020.224641
46-0.128578-1.17840.120976
47-0.043043-0.39450.347106
480.331213.03560.001598

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.131627 & 1.2064 & 0.115529 \tabularnewline
2 & -0.275348 & -2.5236 & 0.006749 \tabularnewline
3 & 0.18754 & 1.7188 & 0.044664 \tabularnewline
4 & -0.0034 & -0.0312 & 0.487609 \tabularnewline
5 & -0.03282 & -0.3008 & 0.382154 \tabularnewline
6 & 0.205553 & 1.8839 & 0.031517 \tabularnewline
7 & -0.03617 & -0.3315 & 0.370545 \tabularnewline
8 & 0.061826 & 0.5666 & 0.286235 \tabularnewline
9 & 0.166415 & 1.5252 & 0.06548 \tabularnewline
10 & -0.298143 & -2.7325 & 0.00383 \tabularnewline
11 & 0.076938 & 0.7052 & 0.241334 \tabularnewline
12 & 0.692603 & 6.3478 & 0 \tabularnewline
13 & 0.020249 & 0.1856 & 0.426609 \tabularnewline
14 & -0.298069 & -2.7318 & 0.003838 \tabularnewline
15 & 0.047543 & 0.4357 & 0.332072 \tabularnewline
16 & -0.038677 & -0.3545 & 0.361935 \tabularnewline
17 & -0.056456 & -0.5174 & 0.30311 \tabularnewline
18 & 0.05991 & 0.5491 & 0.292202 \tabularnewline
19 & -0.090459 & -0.8291 & 0.204707 \tabularnewline
20 & -0.021404 & -0.1962 & 0.422476 \tabularnewline
21 & 0.022938 & 0.2102 & 0.417 \tabularnewline
22 & -0.296758 & -2.7198 & 0.003968 \tabularnewline
23 & -0.001621 & -0.0149 & 0.49409 \tabularnewline
24 & 0.502568 & 4.6061 & 7e-06 \tabularnewline
25 & 0.038547 & 0.3533 & 0.362378 \tabularnewline
26 & -0.296315 & -2.7158 & 0.004013 \tabularnewline
27 & -0.029725 & -0.2724 & 0.392978 \tabularnewline
28 & -0.059779 & -0.5479 & 0.292612 \tabularnewline
29 & -0.115395 & -1.0576 & 0.146631 \tabularnewline
30 & 0.006207 & 0.0569 & 0.477385 \tabularnewline
31 & -0.0727 & -0.6663 & 0.25352 \tabularnewline
32 & -0.061713 & -0.5656 & 0.286584 \tabularnewline
33 & 0.028203 & 0.2585 & 0.398334 \tabularnewline
34 & -0.190874 & -1.7494 & 0.041938 \tabularnewline
35 & -0.024605 & -0.2255 & 0.411065 \tabularnewline
36 & 0.407693 & 3.7366 & 0.00017 \tabularnewline
37 & 0.044151 & 0.4046 & 0.343383 \tabularnewline
38 & -0.26143 & -2.3961 & 0.009397 \tabularnewline
39 & -0.028095 & -0.2575 & 0.398715 \tabularnewline
40 & -0.042708 & -0.3914 & 0.348236 \tabularnewline
41 & -0.082145 & -0.7529 & 0.226816 \tabularnewline
42 & 0.065869 & 0.6037 & 0.273836 \tabularnewline
43 & -0.039298 & -0.3602 & 0.359813 \tabularnewline
44 & -0.043554 & -0.3992 & 0.345386 \tabularnewline
45 & 0.082941 & 0.7602 & 0.224641 \tabularnewline
46 & -0.128578 & -1.1784 & 0.120976 \tabularnewline
47 & -0.043043 & -0.3945 & 0.347106 \tabularnewline
48 & 0.33121 & 3.0356 & 0.001598 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112702&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.131627[/C][C]1.2064[/C][C]0.115529[/C][/ROW]
[ROW][C]2[/C][C]-0.275348[/C][C]-2.5236[/C][C]0.006749[/C][/ROW]
[ROW][C]3[/C][C]0.18754[/C][C]1.7188[/C][C]0.044664[/C][/ROW]
[ROW][C]4[/C][C]-0.0034[/C][C]-0.0312[/C][C]0.487609[/C][/ROW]
[ROW][C]5[/C][C]-0.03282[/C][C]-0.3008[/C][C]0.382154[/C][/ROW]
[ROW][C]6[/C][C]0.205553[/C][C]1.8839[/C][C]0.031517[/C][/ROW]
[ROW][C]7[/C][C]-0.03617[/C][C]-0.3315[/C][C]0.370545[/C][/ROW]
[ROW][C]8[/C][C]0.061826[/C][C]0.5666[/C][C]0.286235[/C][/ROW]
[ROW][C]9[/C][C]0.166415[/C][C]1.5252[/C][C]0.06548[/C][/ROW]
[ROW][C]10[/C][C]-0.298143[/C][C]-2.7325[/C][C]0.00383[/C][/ROW]
[ROW][C]11[/C][C]0.076938[/C][C]0.7052[/C][C]0.241334[/C][/ROW]
[ROW][C]12[/C][C]0.692603[/C][C]6.3478[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.020249[/C][C]0.1856[/C][C]0.426609[/C][/ROW]
[ROW][C]14[/C][C]-0.298069[/C][C]-2.7318[/C][C]0.003838[/C][/ROW]
[ROW][C]15[/C][C]0.047543[/C][C]0.4357[/C][C]0.332072[/C][/ROW]
[ROW][C]16[/C][C]-0.038677[/C][C]-0.3545[/C][C]0.361935[/C][/ROW]
[ROW][C]17[/C][C]-0.056456[/C][C]-0.5174[/C][C]0.30311[/C][/ROW]
[ROW][C]18[/C][C]0.05991[/C][C]0.5491[/C][C]0.292202[/C][/ROW]
[ROW][C]19[/C][C]-0.090459[/C][C]-0.8291[/C][C]0.204707[/C][/ROW]
[ROW][C]20[/C][C]-0.021404[/C][C]-0.1962[/C][C]0.422476[/C][/ROW]
[ROW][C]21[/C][C]0.022938[/C][C]0.2102[/C][C]0.417[/C][/ROW]
[ROW][C]22[/C][C]-0.296758[/C][C]-2.7198[/C][C]0.003968[/C][/ROW]
[ROW][C]23[/C][C]-0.001621[/C][C]-0.0149[/C][C]0.49409[/C][/ROW]
[ROW][C]24[/C][C]0.502568[/C][C]4.6061[/C][C]7e-06[/C][/ROW]
[ROW][C]25[/C][C]0.038547[/C][C]0.3533[/C][C]0.362378[/C][/ROW]
[ROW][C]26[/C][C]-0.296315[/C][C]-2.7158[/C][C]0.004013[/C][/ROW]
[ROW][C]27[/C][C]-0.029725[/C][C]-0.2724[/C][C]0.392978[/C][/ROW]
[ROW][C]28[/C][C]-0.059779[/C][C]-0.5479[/C][C]0.292612[/C][/ROW]
[ROW][C]29[/C][C]-0.115395[/C][C]-1.0576[/C][C]0.146631[/C][/ROW]
[ROW][C]30[/C][C]0.006207[/C][C]0.0569[/C][C]0.477385[/C][/ROW]
[ROW][C]31[/C][C]-0.0727[/C][C]-0.6663[/C][C]0.25352[/C][/ROW]
[ROW][C]32[/C][C]-0.061713[/C][C]-0.5656[/C][C]0.286584[/C][/ROW]
[ROW][C]33[/C][C]0.028203[/C][C]0.2585[/C][C]0.398334[/C][/ROW]
[ROW][C]34[/C][C]-0.190874[/C][C]-1.7494[/C][C]0.041938[/C][/ROW]
[ROW][C]35[/C][C]-0.024605[/C][C]-0.2255[/C][C]0.411065[/C][/ROW]
[ROW][C]36[/C][C]0.407693[/C][C]3.7366[/C][C]0.00017[/C][/ROW]
[ROW][C]37[/C][C]0.044151[/C][C]0.4046[/C][C]0.343383[/C][/ROW]
[ROW][C]38[/C][C]-0.26143[/C][C]-2.3961[/C][C]0.009397[/C][/ROW]
[ROW][C]39[/C][C]-0.028095[/C][C]-0.2575[/C][C]0.398715[/C][/ROW]
[ROW][C]40[/C][C]-0.042708[/C][C]-0.3914[/C][C]0.348236[/C][/ROW]
[ROW][C]41[/C][C]-0.082145[/C][C]-0.7529[/C][C]0.226816[/C][/ROW]
[ROW][C]42[/C][C]0.065869[/C][C]0.6037[/C][C]0.273836[/C][/ROW]
[ROW][C]43[/C][C]-0.039298[/C][C]-0.3602[/C][C]0.359813[/C][/ROW]
[ROW][C]44[/C][C]-0.043554[/C][C]-0.3992[/C][C]0.345386[/C][/ROW]
[ROW][C]45[/C][C]0.082941[/C][C]0.7602[/C][C]0.224641[/C][/ROW]
[ROW][C]46[/C][C]-0.128578[/C][C]-1.1784[/C][C]0.120976[/C][/ROW]
[ROW][C]47[/C][C]-0.043043[/C][C]-0.3945[/C][C]0.347106[/C][/ROW]
[ROW][C]48[/C][C]0.33121[/C][C]3.0356[/C][C]0.001598[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112702&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112702&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1316271.20640.115529
2-0.275348-2.52360.006749
30.187541.71880.044664
4-0.0034-0.03120.487609
5-0.03282-0.30080.382154
60.2055531.88390.031517
7-0.03617-0.33150.370545
80.0618260.56660.286235
90.1664151.52520.06548
10-0.298143-2.73250.00383
110.0769380.70520.241334
120.6926036.34780
130.0202490.18560.426609
14-0.298069-2.73180.003838
150.0475430.43570.332072
16-0.038677-0.35450.361935
17-0.056456-0.51740.30311
180.059910.54910.292202
19-0.090459-0.82910.204707
20-0.021404-0.19620.422476
210.0229380.21020.417
22-0.296758-2.71980.003968
23-0.001621-0.01490.49409
240.5025684.60617e-06
250.0385470.35330.362378
26-0.296315-2.71580.004013
27-0.029725-0.27240.392978
28-0.059779-0.54790.292612
29-0.115395-1.05760.146631
300.0062070.05690.477385
31-0.0727-0.66630.25352
32-0.061713-0.56560.286584
330.0282030.25850.398334
34-0.190874-1.74940.041938
35-0.024605-0.22550.411065
360.4076933.73660.00017
370.0441510.40460.343383
38-0.26143-2.39610.009397
39-0.028095-0.25750.398715
40-0.042708-0.39140.348236
41-0.082145-0.75290.226816
420.0658690.60370.273836
43-0.039298-0.36020.359813
44-0.043554-0.39920.345386
450.0829410.76020.224641
46-0.128578-1.17840.120976
47-0.043043-0.39450.347106
480.331213.03560.001598







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1316271.20640.115529
2-0.297834-2.72970.003861
30.3057282.8020.003151
4-0.232993-2.13540.01782
50.2356412.15970.016824
60.0163960.15030.440456
7-0.017389-0.15940.436878
80.2230062.04390.022049
9-0.072892-0.66810.252962
10-0.239062-2.1910.015609
110.3574233.27580.000766
120.4857654.45211.3e-05
13-0.145541-1.33390.092921
14-0.163761-1.50090.068566
15-0.184075-1.68710.04765
160.1054460.96640.168303
17-0.117934-1.08090.141421
18-0.136195-1.24820.107704
19-0.062656-0.57430.283665
20-0.201028-1.84250.034468
21-0.028769-0.26370.396338
22-0.004439-0.04070.483824
23-0.011088-0.10160.459649
240.1292171.18430.119819
250.0795590.72920.233962
260.0385720.35350.362291
270.0170430.15620.438125
28-0.088527-0.81140.209726
29-0.024397-0.22360.411806
30-0.007262-0.06660.473545
31-0.021967-0.20130.420462
32-0.089528-0.82050.207116
330.0348470.31940.375116
340.0677950.62140.268026
350.0013670.01250.495017
360.0006430.00590.497657
37-0.053368-0.48910.313014
380.0765040.70120.242567
39-0.032302-0.2960.383962
400.0037520.03440.486325
410.0014040.01290.494881
420.0421820.38660.350012
43-0.030476-0.27930.390344
440.0368450.33770.368219
450.0417040.38220.351631
46-0.016697-0.1530.439369
47-0.077913-0.71410.238577
48-0.031859-0.2920.385505

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.131627 & 1.2064 & 0.115529 \tabularnewline
2 & -0.297834 & -2.7297 & 0.003861 \tabularnewline
3 & 0.305728 & 2.802 & 0.003151 \tabularnewline
4 & -0.232993 & -2.1354 & 0.01782 \tabularnewline
5 & 0.235641 & 2.1597 & 0.016824 \tabularnewline
6 & 0.016396 & 0.1503 & 0.440456 \tabularnewline
7 & -0.017389 & -0.1594 & 0.436878 \tabularnewline
8 & 0.223006 & 2.0439 & 0.022049 \tabularnewline
9 & -0.072892 & -0.6681 & 0.252962 \tabularnewline
10 & -0.239062 & -2.191 & 0.015609 \tabularnewline
11 & 0.357423 & 3.2758 & 0.000766 \tabularnewline
12 & 0.485765 & 4.4521 & 1.3e-05 \tabularnewline
13 & -0.145541 & -1.3339 & 0.092921 \tabularnewline
14 & -0.163761 & -1.5009 & 0.068566 \tabularnewline
15 & -0.184075 & -1.6871 & 0.04765 \tabularnewline
16 & 0.105446 & 0.9664 & 0.168303 \tabularnewline
17 & -0.117934 & -1.0809 & 0.141421 \tabularnewline
18 & -0.136195 & -1.2482 & 0.107704 \tabularnewline
19 & -0.062656 & -0.5743 & 0.283665 \tabularnewline
20 & -0.201028 & -1.8425 & 0.034468 \tabularnewline
21 & -0.028769 & -0.2637 & 0.396338 \tabularnewline
22 & -0.004439 & -0.0407 & 0.483824 \tabularnewline
23 & -0.011088 & -0.1016 & 0.459649 \tabularnewline
24 & 0.129217 & 1.1843 & 0.119819 \tabularnewline
25 & 0.079559 & 0.7292 & 0.233962 \tabularnewline
26 & 0.038572 & 0.3535 & 0.362291 \tabularnewline
27 & 0.017043 & 0.1562 & 0.438125 \tabularnewline
28 & -0.088527 & -0.8114 & 0.209726 \tabularnewline
29 & -0.024397 & -0.2236 & 0.411806 \tabularnewline
30 & -0.007262 & -0.0666 & 0.473545 \tabularnewline
31 & -0.021967 & -0.2013 & 0.420462 \tabularnewline
32 & -0.089528 & -0.8205 & 0.207116 \tabularnewline
33 & 0.034847 & 0.3194 & 0.375116 \tabularnewline
34 & 0.067795 & 0.6214 & 0.268026 \tabularnewline
35 & 0.001367 & 0.0125 & 0.495017 \tabularnewline
36 & 0.000643 & 0.0059 & 0.497657 \tabularnewline
37 & -0.053368 & -0.4891 & 0.313014 \tabularnewline
38 & 0.076504 & 0.7012 & 0.242567 \tabularnewline
39 & -0.032302 & -0.296 & 0.383962 \tabularnewline
40 & 0.003752 & 0.0344 & 0.486325 \tabularnewline
41 & 0.001404 & 0.0129 & 0.494881 \tabularnewline
42 & 0.042182 & 0.3866 & 0.350012 \tabularnewline
43 & -0.030476 & -0.2793 & 0.390344 \tabularnewline
44 & 0.036845 & 0.3377 & 0.368219 \tabularnewline
45 & 0.041704 & 0.3822 & 0.351631 \tabularnewline
46 & -0.016697 & -0.153 & 0.439369 \tabularnewline
47 & -0.077913 & -0.7141 & 0.238577 \tabularnewline
48 & -0.031859 & -0.292 & 0.385505 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112702&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.131627[/C][C]1.2064[/C][C]0.115529[/C][/ROW]
[ROW][C]2[/C][C]-0.297834[/C][C]-2.7297[/C][C]0.003861[/C][/ROW]
[ROW][C]3[/C][C]0.305728[/C][C]2.802[/C][C]0.003151[/C][/ROW]
[ROW][C]4[/C][C]-0.232993[/C][C]-2.1354[/C][C]0.01782[/C][/ROW]
[ROW][C]5[/C][C]0.235641[/C][C]2.1597[/C][C]0.016824[/C][/ROW]
[ROW][C]6[/C][C]0.016396[/C][C]0.1503[/C][C]0.440456[/C][/ROW]
[ROW][C]7[/C][C]-0.017389[/C][C]-0.1594[/C][C]0.436878[/C][/ROW]
[ROW][C]8[/C][C]0.223006[/C][C]2.0439[/C][C]0.022049[/C][/ROW]
[ROW][C]9[/C][C]-0.072892[/C][C]-0.6681[/C][C]0.252962[/C][/ROW]
[ROW][C]10[/C][C]-0.239062[/C][C]-2.191[/C][C]0.015609[/C][/ROW]
[ROW][C]11[/C][C]0.357423[/C][C]3.2758[/C][C]0.000766[/C][/ROW]
[ROW][C]12[/C][C]0.485765[/C][C]4.4521[/C][C]1.3e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.145541[/C][C]-1.3339[/C][C]0.092921[/C][/ROW]
[ROW][C]14[/C][C]-0.163761[/C][C]-1.5009[/C][C]0.068566[/C][/ROW]
[ROW][C]15[/C][C]-0.184075[/C][C]-1.6871[/C][C]0.04765[/C][/ROW]
[ROW][C]16[/C][C]0.105446[/C][C]0.9664[/C][C]0.168303[/C][/ROW]
[ROW][C]17[/C][C]-0.117934[/C][C]-1.0809[/C][C]0.141421[/C][/ROW]
[ROW][C]18[/C][C]-0.136195[/C][C]-1.2482[/C][C]0.107704[/C][/ROW]
[ROW][C]19[/C][C]-0.062656[/C][C]-0.5743[/C][C]0.283665[/C][/ROW]
[ROW][C]20[/C][C]-0.201028[/C][C]-1.8425[/C][C]0.034468[/C][/ROW]
[ROW][C]21[/C][C]-0.028769[/C][C]-0.2637[/C][C]0.396338[/C][/ROW]
[ROW][C]22[/C][C]-0.004439[/C][C]-0.0407[/C][C]0.483824[/C][/ROW]
[ROW][C]23[/C][C]-0.011088[/C][C]-0.1016[/C][C]0.459649[/C][/ROW]
[ROW][C]24[/C][C]0.129217[/C][C]1.1843[/C][C]0.119819[/C][/ROW]
[ROW][C]25[/C][C]0.079559[/C][C]0.7292[/C][C]0.233962[/C][/ROW]
[ROW][C]26[/C][C]0.038572[/C][C]0.3535[/C][C]0.362291[/C][/ROW]
[ROW][C]27[/C][C]0.017043[/C][C]0.1562[/C][C]0.438125[/C][/ROW]
[ROW][C]28[/C][C]-0.088527[/C][C]-0.8114[/C][C]0.209726[/C][/ROW]
[ROW][C]29[/C][C]-0.024397[/C][C]-0.2236[/C][C]0.411806[/C][/ROW]
[ROW][C]30[/C][C]-0.007262[/C][C]-0.0666[/C][C]0.473545[/C][/ROW]
[ROW][C]31[/C][C]-0.021967[/C][C]-0.2013[/C][C]0.420462[/C][/ROW]
[ROW][C]32[/C][C]-0.089528[/C][C]-0.8205[/C][C]0.207116[/C][/ROW]
[ROW][C]33[/C][C]0.034847[/C][C]0.3194[/C][C]0.375116[/C][/ROW]
[ROW][C]34[/C][C]0.067795[/C][C]0.6214[/C][C]0.268026[/C][/ROW]
[ROW][C]35[/C][C]0.001367[/C][C]0.0125[/C][C]0.495017[/C][/ROW]
[ROW][C]36[/C][C]0.000643[/C][C]0.0059[/C][C]0.497657[/C][/ROW]
[ROW][C]37[/C][C]-0.053368[/C][C]-0.4891[/C][C]0.313014[/C][/ROW]
[ROW][C]38[/C][C]0.076504[/C][C]0.7012[/C][C]0.242567[/C][/ROW]
[ROW][C]39[/C][C]-0.032302[/C][C]-0.296[/C][C]0.383962[/C][/ROW]
[ROW][C]40[/C][C]0.003752[/C][C]0.0344[/C][C]0.486325[/C][/ROW]
[ROW][C]41[/C][C]0.001404[/C][C]0.0129[/C][C]0.494881[/C][/ROW]
[ROW][C]42[/C][C]0.042182[/C][C]0.3866[/C][C]0.350012[/C][/ROW]
[ROW][C]43[/C][C]-0.030476[/C][C]-0.2793[/C][C]0.390344[/C][/ROW]
[ROW][C]44[/C][C]0.036845[/C][C]0.3377[/C][C]0.368219[/C][/ROW]
[ROW][C]45[/C][C]0.041704[/C][C]0.3822[/C][C]0.351631[/C][/ROW]
[ROW][C]46[/C][C]-0.016697[/C][C]-0.153[/C][C]0.439369[/C][/ROW]
[ROW][C]47[/C][C]-0.077913[/C][C]-0.7141[/C][C]0.238577[/C][/ROW]
[ROW][C]48[/C][C]-0.031859[/C][C]-0.292[/C][C]0.385505[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112702&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112702&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1316271.20640.115529
2-0.297834-2.72970.003861
30.3057282.8020.003151
4-0.232993-2.13540.01782
50.2356412.15970.016824
60.0163960.15030.440456
7-0.017389-0.15940.436878
80.2230062.04390.022049
9-0.072892-0.66810.252962
10-0.239062-2.1910.015609
110.3574233.27580.000766
120.4857654.45211.3e-05
13-0.145541-1.33390.092921
14-0.163761-1.50090.068566
15-0.184075-1.68710.04765
160.1054460.96640.168303
17-0.117934-1.08090.141421
18-0.136195-1.24820.107704
19-0.062656-0.57430.283665
20-0.201028-1.84250.034468
21-0.028769-0.26370.396338
22-0.004439-0.04070.483824
23-0.011088-0.10160.459649
240.1292171.18430.119819
250.0795590.72920.233962
260.0385720.35350.362291
270.0170430.15620.438125
28-0.088527-0.81140.209726
29-0.024397-0.22360.411806
30-0.007262-0.06660.473545
31-0.021967-0.20130.420462
32-0.089528-0.82050.207116
330.0348470.31940.375116
340.0677950.62140.268026
350.0013670.01250.495017
360.0006430.00590.497657
37-0.053368-0.48910.313014
380.0765040.70120.242567
39-0.032302-0.2960.383962
400.0037520.03440.486325
410.0014040.01290.494881
420.0421820.38660.350012
43-0.030476-0.27930.390344
440.0368450.33770.368219
450.0417040.38220.351631
46-0.016697-0.1530.439369
47-0.077913-0.71410.238577
48-0.031859-0.2920.385505



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')