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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 09 Dec 2008 04:18:29 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/09/t1228821539gmy6vut7v449rqr.htm/, Retrieved Sun, 19 May 2024 10:47:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31300, Retrieved Sun, 19 May 2024 10:47:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact176
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Spectral Analysis] [Diff Spectral] [2008-12-06 12:07:42] [74be16979710d4c4e7c6647856088456]
F RMP   [ARIMA Backward Selection] [Arima backward] [2008-12-06 14:19:09] [74be16979710d4c4e7c6647856088456]
- RMPD    [(Partial) Autocorrelation Function] [] [2008-12-09 10:52:15] [74be16979710d4c4e7c6647856088456]
F   PD        [(Partial) Autocorrelation Function] [] [2008-12-09 11:18:29] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-14 14:59:38 [Steven Vanhooreweghe] [reply
Het is eigelijnlijk de bedoeling dat je antwoord op de vraag seizoenaal(D) of niet-seizoenaal(d) differentieren? Daarvoor moet je kijken naar eventuele uitschieters die wijzen op seizoenaliteit. Die zijn hier niet aanwezig. Je kan dus vermoeden dat je een keer niet-seizoenaal zult moeten differentieren. (d=1)Als je dna kijkt naar het VRM klopt dit inderdaad
2008-12-15 13:48:05 [Katja van Hek] [reply
De ACF grafiek laat duidelijk een lange termijn trend zien die je kunt verwijderen door d=1 te stellen.

Post a new message
Dataseries X:
5.1
4.9
5.2
5.1
4.6
3.7
3.9
3.1
2.8
2.6
2.2
1.8
1.3
1.2
1.4
1.3
1.3
1.9
1.9
2.1
2.0
1.9
1.9
1.9
1.8
1.7
1.6
1.7
1.9
1.7
1.3
2.0
2.0
2.3
2.0
1.7
2.3
2.4
2.4
2.3
2.1
2.1
2.5
2.0
1.8
1.7
1.9
2.1
1.4
1.6
1.7
1.6
1.9
1.6
1.1
1.3
1.6
1.6
1.7
1.6
1.7
1.6
1.5
1.6
1.1
1.5
1.4
1.3
0.9
1.2
0.9
1.1
1.3
1.3
1.4
1.2
1.7
2.0
3.0
3.1
3.2
2.7
2.8
3.0
2.8
3.1
3.1
3.2
3.1
2.7
2.2
2.2
2.1
2.3
2.5
2.3
2.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31300&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31300&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31300&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8451698.3240
20.7474517.36150
30.635776.26160
40.5348435.26760
50.4317954.25272.4e-05
60.32043.15560.001067
70.1952611.92310.0287
80.0918210.90430.184029
90.0282740.27850.390622
10-0.050345-0.49580.310564
11-0.103938-1.02370.154268
12-0.17397-1.71340.044916
13-0.121806-1.19970.116598
14-0.083764-0.8250.205704
15-0.099465-0.97960.164856
16-0.084211-0.82940.204462
17-0.098185-0.9670.167971
18-0.106677-1.05060.148015
19-0.104677-1.03090.152564
20-0.125062-1.23170.110515
21-0.166431-1.63920.05221
22-0.171321-1.68730.047378
23-0.20142-1.98380.025055
24-0.208724-2.05570.021249
25-0.213955-2.10720.01884
26-0.226077-2.22660.014144
27-0.180638-1.77910.039179
28-0.179002-1.7630.040528
29-0.154808-1.52470.065296
30-0.144084-1.41910.079543
31-0.111303-1.09620.13785
32-0.086768-0.85460.197448
33-0.052581-0.51790.302867
34-0.04025-0.39640.346335
35-0.012756-0.12560.450142
360.03060.30140.381886
370.0298130.29360.384835
380.0707370.69670.243834
390.0619970.61060.271447
400.0776560.76480.223118
410.0899080.88550.18904
420.0774280.76260.223783
430.0570140.56150.287868
440.0357640.35220.362713
450.0221950.21860.413713
460.0142980.14080.444154
47-0.010045-0.09890.4607
48-0.039404-0.38810.3494
49-0.026894-0.26490.395832
50-0.040223-0.39620.346431
51-0.046591-0.45890.323678
52-0.033606-0.3310.370687
53-0.054742-0.53910.295511
54-0.040117-0.39510.346815
55-0.006539-0.06440.474391
56-0.005406-0.05320.478824
57-0.02121-0.20890.417484
58-0.0507-0.49930.309337
59-0.082365-0.81120.209618
60-0.119294-1.17490.121454

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.845169 & 8.324 & 0 \tabularnewline
2 & 0.747451 & 7.3615 & 0 \tabularnewline
3 & 0.63577 & 6.2616 & 0 \tabularnewline
4 & 0.534843 & 5.2676 & 0 \tabularnewline
5 & 0.431795 & 4.2527 & 2.4e-05 \tabularnewline
6 & 0.3204 & 3.1556 & 0.001067 \tabularnewline
7 & 0.195261 & 1.9231 & 0.0287 \tabularnewline
8 & 0.091821 & 0.9043 & 0.184029 \tabularnewline
9 & 0.028274 & 0.2785 & 0.390622 \tabularnewline
10 & -0.050345 & -0.4958 & 0.310564 \tabularnewline
11 & -0.103938 & -1.0237 & 0.154268 \tabularnewline
12 & -0.17397 & -1.7134 & 0.044916 \tabularnewline
13 & -0.121806 & -1.1997 & 0.116598 \tabularnewline
14 & -0.083764 & -0.825 & 0.205704 \tabularnewline
15 & -0.099465 & -0.9796 & 0.164856 \tabularnewline
16 & -0.084211 & -0.8294 & 0.204462 \tabularnewline
17 & -0.098185 & -0.967 & 0.167971 \tabularnewline
18 & -0.106677 & -1.0506 & 0.148015 \tabularnewline
19 & -0.104677 & -1.0309 & 0.152564 \tabularnewline
20 & -0.125062 & -1.2317 & 0.110515 \tabularnewline
21 & -0.166431 & -1.6392 & 0.05221 \tabularnewline
22 & -0.171321 & -1.6873 & 0.047378 \tabularnewline
23 & -0.20142 & -1.9838 & 0.025055 \tabularnewline
24 & -0.208724 & -2.0557 & 0.021249 \tabularnewline
25 & -0.213955 & -2.1072 & 0.01884 \tabularnewline
26 & -0.226077 & -2.2266 & 0.014144 \tabularnewline
27 & -0.180638 & -1.7791 & 0.039179 \tabularnewline
28 & -0.179002 & -1.763 & 0.040528 \tabularnewline
29 & -0.154808 & -1.5247 & 0.065296 \tabularnewline
30 & -0.144084 & -1.4191 & 0.079543 \tabularnewline
31 & -0.111303 & -1.0962 & 0.13785 \tabularnewline
32 & -0.086768 & -0.8546 & 0.197448 \tabularnewline
33 & -0.052581 & -0.5179 & 0.302867 \tabularnewline
34 & -0.04025 & -0.3964 & 0.346335 \tabularnewline
35 & -0.012756 & -0.1256 & 0.450142 \tabularnewline
36 & 0.0306 & 0.3014 & 0.381886 \tabularnewline
37 & 0.029813 & 0.2936 & 0.384835 \tabularnewline
38 & 0.070737 & 0.6967 & 0.243834 \tabularnewline
39 & 0.061997 & 0.6106 & 0.271447 \tabularnewline
40 & 0.077656 & 0.7648 & 0.223118 \tabularnewline
41 & 0.089908 & 0.8855 & 0.18904 \tabularnewline
42 & 0.077428 & 0.7626 & 0.223783 \tabularnewline
43 & 0.057014 & 0.5615 & 0.287868 \tabularnewline
44 & 0.035764 & 0.3522 & 0.362713 \tabularnewline
45 & 0.022195 & 0.2186 & 0.413713 \tabularnewline
46 & 0.014298 & 0.1408 & 0.444154 \tabularnewline
47 & -0.010045 & -0.0989 & 0.4607 \tabularnewline
48 & -0.039404 & -0.3881 & 0.3494 \tabularnewline
49 & -0.026894 & -0.2649 & 0.395832 \tabularnewline
50 & -0.040223 & -0.3962 & 0.346431 \tabularnewline
51 & -0.046591 & -0.4589 & 0.323678 \tabularnewline
52 & -0.033606 & -0.331 & 0.370687 \tabularnewline
53 & -0.054742 & -0.5391 & 0.295511 \tabularnewline
54 & -0.040117 & -0.3951 & 0.346815 \tabularnewline
55 & -0.006539 & -0.0644 & 0.474391 \tabularnewline
56 & -0.005406 & -0.0532 & 0.478824 \tabularnewline
57 & -0.02121 & -0.2089 & 0.417484 \tabularnewline
58 & -0.0507 & -0.4993 & 0.309337 \tabularnewline
59 & -0.082365 & -0.8112 & 0.209618 \tabularnewline
60 & -0.119294 & -1.1749 & 0.121454 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31300&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]0.845169[/C][C]8.324[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.747451[/C][C]7.3615[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.63577[/C][C]6.2616[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.534843[/C][C]5.2676[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.431795[/C][C]4.2527[/C][C]2.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.3204[/C][C]3.1556[/C][C]0.001067[/C][/ROW]
[ROW][C]7[/C][C]0.195261[/C][C]1.9231[/C][C]0.0287[/C][/ROW]
[ROW][C]8[/C][C]0.091821[/C][C]0.9043[/C][C]0.184029[/C][/ROW]
[ROW][C]9[/C][C]0.028274[/C][C]0.2785[/C][C]0.390622[/C][/ROW]
[ROW][C]10[/C][C]-0.050345[/C][C]-0.4958[/C][C]0.310564[/C][/ROW]
[ROW][C]11[/C][C]-0.103938[/C][C]-1.0237[/C][C]0.154268[/C][/ROW]
[ROW][C]12[/C][C]-0.17397[/C][C]-1.7134[/C][C]0.044916[/C][/ROW]
[ROW][C]13[/C][C]-0.121806[/C][C]-1.1997[/C][C]0.116598[/C][/ROW]
[ROW][C]14[/C][C]-0.083764[/C][C]-0.825[/C][C]0.205704[/C][/ROW]
[ROW][C]15[/C][C]-0.099465[/C][C]-0.9796[/C][C]0.164856[/C][/ROW]
[ROW][C]16[/C][C]-0.084211[/C][C]-0.8294[/C][C]0.204462[/C][/ROW]
[ROW][C]17[/C][C]-0.098185[/C][C]-0.967[/C][C]0.167971[/C][/ROW]
[ROW][C]18[/C][C]-0.106677[/C][C]-1.0506[/C][C]0.148015[/C][/ROW]
[ROW][C]19[/C][C]-0.104677[/C][C]-1.0309[/C][C]0.152564[/C][/ROW]
[ROW][C]20[/C][C]-0.125062[/C][C]-1.2317[/C][C]0.110515[/C][/ROW]
[ROW][C]21[/C][C]-0.166431[/C][C]-1.6392[/C][C]0.05221[/C][/ROW]
[ROW][C]22[/C][C]-0.171321[/C][C]-1.6873[/C][C]0.047378[/C][/ROW]
[ROW][C]23[/C][C]-0.20142[/C][C]-1.9838[/C][C]0.025055[/C][/ROW]
[ROW][C]24[/C][C]-0.208724[/C][C]-2.0557[/C][C]0.021249[/C][/ROW]
[ROW][C]25[/C][C]-0.213955[/C][C]-2.1072[/C][C]0.01884[/C][/ROW]
[ROW][C]26[/C][C]-0.226077[/C][C]-2.2266[/C][C]0.014144[/C][/ROW]
[ROW][C]27[/C][C]-0.180638[/C][C]-1.7791[/C][C]0.039179[/C][/ROW]
[ROW][C]28[/C][C]-0.179002[/C][C]-1.763[/C][C]0.040528[/C][/ROW]
[ROW][C]29[/C][C]-0.154808[/C][C]-1.5247[/C][C]0.065296[/C][/ROW]
[ROW][C]30[/C][C]-0.144084[/C][C]-1.4191[/C][C]0.079543[/C][/ROW]
[ROW][C]31[/C][C]-0.111303[/C][C]-1.0962[/C][C]0.13785[/C][/ROW]
[ROW][C]32[/C][C]-0.086768[/C][C]-0.8546[/C][C]0.197448[/C][/ROW]
[ROW][C]33[/C][C]-0.052581[/C][C]-0.5179[/C][C]0.302867[/C][/ROW]
[ROW][C]34[/C][C]-0.04025[/C][C]-0.3964[/C][C]0.346335[/C][/ROW]
[ROW][C]35[/C][C]-0.012756[/C][C]-0.1256[/C][C]0.450142[/C][/ROW]
[ROW][C]36[/C][C]0.0306[/C][C]0.3014[/C][C]0.381886[/C][/ROW]
[ROW][C]37[/C][C]0.029813[/C][C]0.2936[/C][C]0.384835[/C][/ROW]
[ROW][C]38[/C][C]0.070737[/C][C]0.6967[/C][C]0.243834[/C][/ROW]
[ROW][C]39[/C][C]0.061997[/C][C]0.6106[/C][C]0.271447[/C][/ROW]
[ROW][C]40[/C][C]0.077656[/C][C]0.7648[/C][C]0.223118[/C][/ROW]
[ROW][C]41[/C][C]0.089908[/C][C]0.8855[/C][C]0.18904[/C][/ROW]
[ROW][C]42[/C][C]0.077428[/C][C]0.7626[/C][C]0.223783[/C][/ROW]
[ROW][C]43[/C][C]0.057014[/C][C]0.5615[/C][C]0.287868[/C][/ROW]
[ROW][C]44[/C][C]0.035764[/C][C]0.3522[/C][C]0.362713[/C][/ROW]
[ROW][C]45[/C][C]0.022195[/C][C]0.2186[/C][C]0.413713[/C][/ROW]
[ROW][C]46[/C][C]0.014298[/C][C]0.1408[/C][C]0.444154[/C][/ROW]
[ROW][C]47[/C][C]-0.010045[/C][C]-0.0989[/C][C]0.4607[/C][/ROW]
[ROW][C]48[/C][C]-0.039404[/C][C]-0.3881[/C][C]0.3494[/C][/ROW]
[ROW][C]49[/C][C]-0.026894[/C][C]-0.2649[/C][C]0.395832[/C][/ROW]
[ROW][C]50[/C][C]-0.040223[/C][C]-0.3962[/C][C]0.346431[/C][/ROW]
[ROW][C]51[/C][C]-0.046591[/C][C]-0.4589[/C][C]0.323678[/C][/ROW]
[ROW][C]52[/C][C]-0.033606[/C][C]-0.331[/C][C]0.370687[/C][/ROW]
[ROW][C]53[/C][C]-0.054742[/C][C]-0.5391[/C][C]0.295511[/C][/ROW]
[ROW][C]54[/C][C]-0.040117[/C][C]-0.3951[/C][C]0.346815[/C][/ROW]
[ROW][C]55[/C][C]-0.006539[/C][C]-0.0644[/C][C]0.474391[/C][/ROW]
[ROW][C]56[/C][C]-0.005406[/C][C]-0.0532[/C][C]0.478824[/C][/ROW]
[ROW][C]57[/C][C]-0.02121[/C][C]-0.2089[/C][C]0.417484[/C][/ROW]
[ROW][C]58[/C][C]-0.0507[/C][C]-0.4993[/C][C]0.309337[/C][/ROW]
[ROW][C]59[/C][C]-0.082365[/C][C]-0.8112[/C][C]0.209618[/C][/ROW]
[ROW][C]60[/C][C]-0.119294[/C][C]-1.1749[/C][C]0.121454[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31300&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31300&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
10.8451698.3240
20.7474517.36150
30.635776.26160
40.5348435.26760
50.4317954.25272.4e-05
60.32043.15560.001067
70.1952611.92310.0287
80.0918210.90430.184029
90.0282740.27850.390622
10-0.050345-0.49580.310564
11-0.103938-1.02370.154268
12-0.17397-1.71340.044916
13-0.121806-1.19970.116598
14-0.083764-0.8250.205704
15-0.099465-0.97960.164856
16-0.084211-0.82940.204462
17-0.098185-0.9670.167971
18-0.106677-1.05060.148015
19-0.104677-1.03090.152564
20-0.125062-1.23170.110515
21-0.166431-1.63920.05221
22-0.171321-1.68730.047378
23-0.20142-1.98380.025055
24-0.208724-2.05570.021249
25-0.213955-2.10720.01884
26-0.226077-2.22660.014144
27-0.180638-1.77910.039179
28-0.179002-1.7630.040528
29-0.154808-1.52470.065296
30-0.144084-1.41910.079543
31-0.111303-1.09620.13785
32-0.086768-0.85460.197448
33-0.052581-0.51790.302867
34-0.04025-0.39640.346335
35-0.012756-0.12560.450142
360.03060.30140.381886
370.0298130.29360.384835
380.0707370.69670.243834
390.0619970.61060.271447
400.0776560.76480.223118
410.0899080.88550.18904
420.0774280.76260.223783
430.0570140.56150.287868
440.0357640.35220.362713
450.0221950.21860.413713
460.0142980.14080.444154
47-0.010045-0.09890.4607
48-0.039404-0.38810.3494
49-0.026894-0.26490.395832
50-0.040223-0.39620.346431
51-0.046591-0.45890.323678
52-0.033606-0.3310.370687
53-0.054742-0.53910.295511
54-0.040117-0.39510.346815
55-0.006539-0.06440.474391
56-0.005406-0.05320.478824
57-0.02121-0.20890.417484
58-0.0507-0.49930.309337
59-0.082365-0.81120.209618
60-0.119294-1.17490.121454







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8451698.3240
20.1160011.14250.128033
3-0.07349-0.72380.235467
4-0.039998-0.39390.347247
5-0.06306-0.62110.268005
6-0.104175-1.0260.153721
7-0.143417-1.41250.080502
8-0.041019-0.4040.343555
90.073990.72870.233965
10-0.081495-0.80260.212075
11-0.007901-0.07780.469069
12-0.096694-0.95230.171649
130.3474063.42160.000456
140.0737610.72650.234654
15-0.271929-2.67820.004347
160.0350270.3450.365431
17-0.071827-0.70740.240502
18-0.103994-1.02420.154139
19-0.057211-0.56350.28721
20-0.080379-0.79160.21525
210.0083480.08220.467321
220.037050.36490.357992
23-0.113389-1.11670.13343
240.0349050.34380.36588
250.1737691.71140.045099
26-0.016389-0.16140.436053
27-0.013306-0.1310.448004
28-0.109518-1.07860.141714
290.0146410.14420.442824
30-0.09962-0.98110.164481
310.0376180.37050.355912
32-0.029554-0.29110.38581
33-0.015645-0.15410.43893
340.074840.73710.231424
350.0095730.09430.46254
360.1050191.03430.151779
37-0.009895-0.09750.461282
380.0653270.64340.260744
39-0.03462-0.3410.366934
40-0.06833-0.6730.251284
41-0.047976-0.47250.318814
42-0.123496-1.21630.113412
43-0.01967-0.19370.423396
44-0.033291-0.32790.371854
45-0.006504-0.06410.474528
460.0929760.91570.181046
47-0.050022-0.49270.311684
480.089710.88350.189563
490.1055171.03920.150642
50-0.031251-0.30780.379451
51-0.083005-0.81750.207822
520.006130.06040.475993
53-0.115123-1.13380.12983
54-0.073809-0.72690.23451
550.0810350.79810.21338
56-0.075651-0.74510.229015
57-0.047957-0.47230.31888
58-0.079336-0.78140.218245
59-0.025918-0.25530.399531
60-0.063019-0.62070.268137

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.845169 & 8.324 & 0 \tabularnewline
2 & 0.116001 & 1.1425 & 0.128033 \tabularnewline
3 & -0.07349 & -0.7238 & 0.235467 \tabularnewline
4 & -0.039998 & -0.3939 & 0.347247 \tabularnewline
5 & -0.06306 & -0.6211 & 0.268005 \tabularnewline
6 & -0.104175 & -1.026 & 0.153721 \tabularnewline
7 & -0.143417 & -1.4125 & 0.080502 \tabularnewline
8 & -0.041019 & -0.404 & 0.343555 \tabularnewline
9 & 0.07399 & 0.7287 & 0.233965 \tabularnewline
10 & -0.081495 & -0.8026 & 0.212075 \tabularnewline
11 & -0.007901 & -0.0778 & 0.469069 \tabularnewline
12 & -0.096694 & -0.9523 & 0.171649 \tabularnewline
13 & 0.347406 & 3.4216 & 0.000456 \tabularnewline
14 & 0.073761 & 0.7265 & 0.234654 \tabularnewline
15 & -0.271929 & -2.6782 & 0.004347 \tabularnewline
16 & 0.035027 & 0.345 & 0.365431 \tabularnewline
17 & -0.071827 & -0.7074 & 0.240502 \tabularnewline
18 & -0.103994 & -1.0242 & 0.154139 \tabularnewline
19 & -0.057211 & -0.5635 & 0.28721 \tabularnewline
20 & -0.080379 & -0.7916 & 0.21525 \tabularnewline
21 & 0.008348 & 0.0822 & 0.467321 \tabularnewline
22 & 0.03705 & 0.3649 & 0.357992 \tabularnewline
23 & -0.113389 & -1.1167 & 0.13343 \tabularnewline
24 & 0.034905 & 0.3438 & 0.36588 \tabularnewline
25 & 0.173769 & 1.7114 & 0.045099 \tabularnewline
26 & -0.016389 & -0.1614 & 0.436053 \tabularnewline
27 & -0.013306 & -0.131 & 0.448004 \tabularnewline
28 & -0.109518 & -1.0786 & 0.141714 \tabularnewline
29 & 0.014641 & 0.1442 & 0.442824 \tabularnewline
30 & -0.09962 & -0.9811 & 0.164481 \tabularnewline
31 & 0.037618 & 0.3705 & 0.355912 \tabularnewline
32 & -0.029554 & -0.2911 & 0.38581 \tabularnewline
33 & -0.015645 & -0.1541 & 0.43893 \tabularnewline
34 & 0.07484 & 0.7371 & 0.231424 \tabularnewline
35 & 0.009573 & 0.0943 & 0.46254 \tabularnewline
36 & 0.105019 & 1.0343 & 0.151779 \tabularnewline
37 & -0.009895 & -0.0975 & 0.461282 \tabularnewline
38 & 0.065327 & 0.6434 & 0.260744 \tabularnewline
39 & -0.03462 & -0.341 & 0.366934 \tabularnewline
40 & -0.06833 & -0.673 & 0.251284 \tabularnewline
41 & -0.047976 & -0.4725 & 0.318814 \tabularnewline
42 & -0.123496 & -1.2163 & 0.113412 \tabularnewline
43 & -0.01967 & -0.1937 & 0.423396 \tabularnewline
44 & -0.033291 & -0.3279 & 0.371854 \tabularnewline
45 & -0.006504 & -0.0641 & 0.474528 \tabularnewline
46 & 0.092976 & 0.9157 & 0.181046 \tabularnewline
47 & -0.050022 & -0.4927 & 0.311684 \tabularnewline
48 & 0.08971 & 0.8835 & 0.189563 \tabularnewline
49 & 0.105517 & 1.0392 & 0.150642 \tabularnewline
50 & -0.031251 & -0.3078 & 0.379451 \tabularnewline
51 & -0.083005 & -0.8175 & 0.207822 \tabularnewline
52 & 0.00613 & 0.0604 & 0.475993 \tabularnewline
53 & -0.115123 & -1.1338 & 0.12983 \tabularnewline
54 & -0.073809 & -0.7269 & 0.23451 \tabularnewline
55 & 0.081035 & 0.7981 & 0.21338 \tabularnewline
56 & -0.075651 & -0.7451 & 0.229015 \tabularnewline
57 & -0.047957 & -0.4723 & 0.31888 \tabularnewline
58 & -0.079336 & -0.7814 & 0.218245 \tabularnewline
59 & -0.025918 & -0.2553 & 0.399531 \tabularnewline
60 & -0.063019 & -0.6207 & 0.268137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31300&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]0.845169[/C][C]8.324[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.116001[/C][C]1.1425[/C][C]0.128033[/C][/ROW]
[ROW][C]3[/C][C]-0.07349[/C][C]-0.7238[/C][C]0.235467[/C][/ROW]
[ROW][C]4[/C][C]-0.039998[/C][C]-0.3939[/C][C]0.347247[/C][/ROW]
[ROW][C]5[/C][C]-0.06306[/C][C]-0.6211[/C][C]0.268005[/C][/ROW]
[ROW][C]6[/C][C]-0.104175[/C][C]-1.026[/C][C]0.153721[/C][/ROW]
[ROW][C]7[/C][C]-0.143417[/C][C]-1.4125[/C][C]0.080502[/C][/ROW]
[ROW][C]8[/C][C]-0.041019[/C][C]-0.404[/C][C]0.343555[/C][/ROW]
[ROW][C]9[/C][C]0.07399[/C][C]0.7287[/C][C]0.233965[/C][/ROW]
[ROW][C]10[/C][C]-0.081495[/C][C]-0.8026[/C][C]0.212075[/C][/ROW]
[ROW][C]11[/C][C]-0.007901[/C][C]-0.0778[/C][C]0.469069[/C][/ROW]
[ROW][C]12[/C][C]-0.096694[/C][C]-0.9523[/C][C]0.171649[/C][/ROW]
[ROW][C]13[/C][C]0.347406[/C][C]3.4216[/C][C]0.000456[/C][/ROW]
[ROW][C]14[/C][C]0.073761[/C][C]0.7265[/C][C]0.234654[/C][/ROW]
[ROW][C]15[/C][C]-0.271929[/C][C]-2.6782[/C][C]0.004347[/C][/ROW]
[ROW][C]16[/C][C]0.035027[/C][C]0.345[/C][C]0.365431[/C][/ROW]
[ROW][C]17[/C][C]-0.071827[/C][C]-0.7074[/C][C]0.240502[/C][/ROW]
[ROW][C]18[/C][C]-0.103994[/C][C]-1.0242[/C][C]0.154139[/C][/ROW]
[ROW][C]19[/C][C]-0.057211[/C][C]-0.5635[/C][C]0.28721[/C][/ROW]
[ROW][C]20[/C][C]-0.080379[/C][C]-0.7916[/C][C]0.21525[/C][/ROW]
[ROW][C]21[/C][C]0.008348[/C][C]0.0822[/C][C]0.467321[/C][/ROW]
[ROW][C]22[/C][C]0.03705[/C][C]0.3649[/C][C]0.357992[/C][/ROW]
[ROW][C]23[/C][C]-0.113389[/C][C]-1.1167[/C][C]0.13343[/C][/ROW]
[ROW][C]24[/C][C]0.034905[/C][C]0.3438[/C][C]0.36588[/C][/ROW]
[ROW][C]25[/C][C]0.173769[/C][C]1.7114[/C][C]0.045099[/C][/ROW]
[ROW][C]26[/C][C]-0.016389[/C][C]-0.1614[/C][C]0.436053[/C][/ROW]
[ROW][C]27[/C][C]-0.013306[/C][C]-0.131[/C][C]0.448004[/C][/ROW]
[ROW][C]28[/C][C]-0.109518[/C][C]-1.0786[/C][C]0.141714[/C][/ROW]
[ROW][C]29[/C][C]0.014641[/C][C]0.1442[/C][C]0.442824[/C][/ROW]
[ROW][C]30[/C][C]-0.09962[/C][C]-0.9811[/C][C]0.164481[/C][/ROW]
[ROW][C]31[/C][C]0.037618[/C][C]0.3705[/C][C]0.355912[/C][/ROW]
[ROW][C]32[/C][C]-0.029554[/C][C]-0.2911[/C][C]0.38581[/C][/ROW]
[ROW][C]33[/C][C]-0.015645[/C][C]-0.1541[/C][C]0.43893[/C][/ROW]
[ROW][C]34[/C][C]0.07484[/C][C]0.7371[/C][C]0.231424[/C][/ROW]
[ROW][C]35[/C][C]0.009573[/C][C]0.0943[/C][C]0.46254[/C][/ROW]
[ROW][C]36[/C][C]0.105019[/C][C]1.0343[/C][C]0.151779[/C][/ROW]
[ROW][C]37[/C][C]-0.009895[/C][C]-0.0975[/C][C]0.461282[/C][/ROW]
[ROW][C]38[/C][C]0.065327[/C][C]0.6434[/C][C]0.260744[/C][/ROW]
[ROW][C]39[/C][C]-0.03462[/C][C]-0.341[/C][C]0.366934[/C][/ROW]
[ROW][C]40[/C][C]-0.06833[/C][C]-0.673[/C][C]0.251284[/C][/ROW]
[ROW][C]41[/C][C]-0.047976[/C][C]-0.4725[/C][C]0.318814[/C][/ROW]
[ROW][C]42[/C][C]-0.123496[/C][C]-1.2163[/C][C]0.113412[/C][/ROW]
[ROW][C]43[/C][C]-0.01967[/C][C]-0.1937[/C][C]0.423396[/C][/ROW]
[ROW][C]44[/C][C]-0.033291[/C][C]-0.3279[/C][C]0.371854[/C][/ROW]
[ROW][C]45[/C][C]-0.006504[/C][C]-0.0641[/C][C]0.474528[/C][/ROW]
[ROW][C]46[/C][C]0.092976[/C][C]0.9157[/C][C]0.181046[/C][/ROW]
[ROW][C]47[/C][C]-0.050022[/C][C]-0.4927[/C][C]0.311684[/C][/ROW]
[ROW][C]48[/C][C]0.08971[/C][C]0.8835[/C][C]0.189563[/C][/ROW]
[ROW][C]49[/C][C]0.105517[/C][C]1.0392[/C][C]0.150642[/C][/ROW]
[ROW][C]50[/C][C]-0.031251[/C][C]-0.3078[/C][C]0.379451[/C][/ROW]
[ROW][C]51[/C][C]-0.083005[/C][C]-0.8175[/C][C]0.207822[/C][/ROW]
[ROW][C]52[/C][C]0.00613[/C][C]0.0604[/C][C]0.475993[/C][/ROW]
[ROW][C]53[/C][C]-0.115123[/C][C]-1.1338[/C][C]0.12983[/C][/ROW]
[ROW][C]54[/C][C]-0.073809[/C][C]-0.7269[/C][C]0.23451[/C][/ROW]
[ROW][C]55[/C][C]0.081035[/C][C]0.7981[/C][C]0.21338[/C][/ROW]
[ROW][C]56[/C][C]-0.075651[/C][C]-0.7451[/C][C]0.229015[/C][/ROW]
[ROW][C]57[/C][C]-0.047957[/C][C]-0.4723[/C][C]0.31888[/C][/ROW]
[ROW][C]58[/C][C]-0.079336[/C][C]-0.7814[/C][C]0.218245[/C][/ROW]
[ROW][C]59[/C][C]-0.025918[/C][C]-0.2553[/C][C]0.399531[/C][/ROW]
[ROW][C]60[/C][C]-0.063019[/C][C]-0.6207[/C][C]0.268137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31300&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31300&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
10.8451698.3240
20.1160011.14250.128033
3-0.07349-0.72380.235467
4-0.039998-0.39390.347247
5-0.06306-0.62110.268005
6-0.104175-1.0260.153721
7-0.143417-1.41250.080502
8-0.041019-0.4040.343555
90.073990.72870.233965
10-0.081495-0.80260.212075
11-0.007901-0.07780.469069
12-0.096694-0.95230.171649
130.3474063.42160.000456
140.0737610.72650.234654
15-0.271929-2.67820.004347
160.0350270.3450.365431
17-0.071827-0.70740.240502
18-0.103994-1.02420.154139
19-0.057211-0.56350.28721
20-0.080379-0.79160.21525
210.0083480.08220.467321
220.037050.36490.357992
23-0.113389-1.11670.13343
240.0349050.34380.36588
250.1737691.71140.045099
26-0.016389-0.16140.436053
27-0.013306-0.1310.448004
28-0.109518-1.07860.141714
290.0146410.14420.442824
30-0.09962-0.98110.164481
310.0376180.37050.355912
32-0.029554-0.29110.38581
33-0.015645-0.15410.43893
340.074840.73710.231424
350.0095730.09430.46254
360.1050191.03430.151779
37-0.009895-0.09750.461282
380.0653270.64340.260744
39-0.03462-0.3410.366934
40-0.06833-0.6730.251284
41-0.047976-0.47250.318814
42-0.123496-1.21630.113412
43-0.01967-0.19370.423396
44-0.033291-0.32790.371854
45-0.006504-0.06410.474528
460.0929760.91570.181046
47-0.050022-0.49270.311684
480.089710.88350.189563
490.1055171.03920.150642
50-0.031251-0.30780.379451
51-0.083005-0.81750.207822
520.006130.06040.475993
53-0.115123-1.13380.12983
54-0.073809-0.72690.23451
550.0810350.79810.21338
56-0.075651-0.74510.229015
57-0.047957-0.47230.31888
58-0.079336-0.78140.218245
59-0.025918-0.25530.399531
60-0.063019-0.62070.268137



Parameters (Session):
par1 = 60 ; par2 = -0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = -0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')