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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 13 Dec 2008 09:18:42 -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/13/t1229185189lrq6ne7w14e9iq9.htm/, Retrieved Fri, 24 May 2024 22:21:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33177, Retrieved Fri, 24 May 2024 22:21:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [eraetzert] [2008-12-13 16:18:42] [a5ed2c45dea395ef181ba16fe56905d7] [Current]
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Dataseries X:
554.79
562.33
560.85
555.33
543.6
536.66
542.72
593.53
610.76
612.61
611.32
594.17
595.45
590.87
589.38
584.43
573.1
567.46
569.03
620.74
628.88
628.23
612.12
595.4
597.14
593.41
590.07
579.8
574.21
572.78
572.94
619.57
625.81
619.92
587.63
565.74
557.27
560.58
548.85
531.67
525.92
511.04
498.66
555.36
564.59
541.66
527.07
509.85
514.26
516.92
507.56
492.62
490.24
469.36
477.58
528.38
533.59
517.95
506.17
501.87




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33177&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33177&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33177&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'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.060545-0.41510.339987
20.1032290.70770.241313
30.1596271.09430.13969
40.0997590.68390.248693
50.0395790.27130.393658
60.04220.28930.38681
70.0235190.16120.436299
80.0996580.68320.24891
9-0.022572-0.15470.438842
10-0.095694-0.6560.257496
110.2819861.93320.029624
12-0.162115-1.11140.136024
13-0.090386-0.61970.269239
140.0401360.27520.392199
15-0.07085-0.48570.31471
16-0.098646-0.67630.251087
17-0.052118-0.35730.361231
18-0.059908-0.41070.341577
190.0254690.17460.431068
20-0.018526-0.1270.449738
21-0.02078-0.14250.443661
220.0542460.37190.355824
23-0.002749-0.01880.492521
24-0.146881-1.0070.159554
25-0.035326-0.24220.404847
26-0.090798-0.62250.268317
27-0.046444-0.31840.375796
28-0.041638-0.28550.388275
290.0791770.54280.294914
30-0.051981-0.35640.361582
310.0449040.30780.37978
32-0.052372-0.3590.360584
33-0.03016-0.20680.418542
34-0.045457-0.31160.378346
35-0.038017-0.26060.397759
36-0.033732-0.23130.409061
37-0.075959-0.52080.302492
38-0.014386-0.09860.460927
39-0.053271-0.36520.358298
400.0313710.21510.415321
41-0.08839-0.6060.273725
420.0326660.22390.411884
430.0216480.14840.441326
44-0.021051-0.14430.442933
45-0.00904-0.0620.475423
46-0.04938-0.33850.368234
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.060545 & -0.4151 & 0.339987 \tabularnewline
2 & 0.103229 & 0.7077 & 0.241313 \tabularnewline
3 & 0.159627 & 1.0943 & 0.13969 \tabularnewline
4 & 0.099759 & 0.6839 & 0.248693 \tabularnewline
5 & 0.039579 & 0.2713 & 0.393658 \tabularnewline
6 & 0.0422 & 0.2893 & 0.38681 \tabularnewline
7 & 0.023519 & 0.1612 & 0.436299 \tabularnewline
8 & 0.099658 & 0.6832 & 0.24891 \tabularnewline
9 & -0.022572 & -0.1547 & 0.438842 \tabularnewline
10 & -0.095694 & -0.656 & 0.257496 \tabularnewline
11 & 0.281986 & 1.9332 & 0.029624 \tabularnewline
12 & -0.162115 & -1.1114 & 0.136024 \tabularnewline
13 & -0.090386 & -0.6197 & 0.269239 \tabularnewline
14 & 0.040136 & 0.2752 & 0.392199 \tabularnewline
15 & -0.07085 & -0.4857 & 0.31471 \tabularnewline
16 & -0.098646 & -0.6763 & 0.251087 \tabularnewline
17 & -0.052118 & -0.3573 & 0.361231 \tabularnewline
18 & -0.059908 & -0.4107 & 0.341577 \tabularnewline
19 & 0.025469 & 0.1746 & 0.431068 \tabularnewline
20 & -0.018526 & -0.127 & 0.449738 \tabularnewline
21 & -0.02078 & -0.1425 & 0.443661 \tabularnewline
22 & 0.054246 & 0.3719 & 0.355824 \tabularnewline
23 & -0.002749 & -0.0188 & 0.492521 \tabularnewline
24 & -0.146881 & -1.007 & 0.159554 \tabularnewline
25 & -0.035326 & -0.2422 & 0.404847 \tabularnewline
26 & -0.090798 & -0.6225 & 0.268317 \tabularnewline
27 & -0.046444 & -0.3184 & 0.375796 \tabularnewline
28 & -0.041638 & -0.2855 & 0.388275 \tabularnewline
29 & 0.079177 & 0.5428 & 0.294914 \tabularnewline
30 & -0.051981 & -0.3564 & 0.361582 \tabularnewline
31 & 0.044904 & 0.3078 & 0.37978 \tabularnewline
32 & -0.052372 & -0.359 & 0.360584 \tabularnewline
33 & -0.03016 & -0.2068 & 0.418542 \tabularnewline
34 & -0.045457 & -0.3116 & 0.378346 \tabularnewline
35 & -0.038017 & -0.2606 & 0.397759 \tabularnewline
36 & -0.033732 & -0.2313 & 0.409061 \tabularnewline
37 & -0.075959 & -0.5208 & 0.302492 \tabularnewline
38 & -0.014386 & -0.0986 & 0.460927 \tabularnewline
39 & -0.053271 & -0.3652 & 0.358298 \tabularnewline
40 & 0.031371 & 0.2151 & 0.415321 \tabularnewline
41 & -0.08839 & -0.606 & 0.273725 \tabularnewline
42 & 0.032666 & 0.2239 & 0.411884 \tabularnewline
43 & 0.021648 & 0.1484 & 0.441326 \tabularnewline
44 & -0.021051 & -0.1443 & 0.442933 \tabularnewline
45 & -0.00904 & -0.062 & 0.475423 \tabularnewline
46 & -0.04938 & -0.3385 & 0.368234 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33177&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]-0.060545[/C][C]-0.4151[/C][C]0.339987[/C][/ROW]
[ROW][C]2[/C][C]0.103229[/C][C]0.7077[/C][C]0.241313[/C][/ROW]
[ROW][C]3[/C][C]0.159627[/C][C]1.0943[/C][C]0.13969[/C][/ROW]
[ROW][C]4[/C][C]0.099759[/C][C]0.6839[/C][C]0.248693[/C][/ROW]
[ROW][C]5[/C][C]0.039579[/C][C]0.2713[/C][C]0.393658[/C][/ROW]
[ROW][C]6[/C][C]0.0422[/C][C]0.2893[/C][C]0.38681[/C][/ROW]
[ROW][C]7[/C][C]0.023519[/C][C]0.1612[/C][C]0.436299[/C][/ROW]
[ROW][C]8[/C][C]0.099658[/C][C]0.6832[/C][C]0.24891[/C][/ROW]
[ROW][C]9[/C][C]-0.022572[/C][C]-0.1547[/C][C]0.438842[/C][/ROW]
[ROW][C]10[/C][C]-0.095694[/C][C]-0.656[/C][C]0.257496[/C][/ROW]
[ROW][C]11[/C][C]0.281986[/C][C]1.9332[/C][C]0.029624[/C][/ROW]
[ROW][C]12[/C][C]-0.162115[/C][C]-1.1114[/C][C]0.136024[/C][/ROW]
[ROW][C]13[/C][C]-0.090386[/C][C]-0.6197[/C][C]0.269239[/C][/ROW]
[ROW][C]14[/C][C]0.040136[/C][C]0.2752[/C][C]0.392199[/C][/ROW]
[ROW][C]15[/C][C]-0.07085[/C][C]-0.4857[/C][C]0.31471[/C][/ROW]
[ROW][C]16[/C][C]-0.098646[/C][C]-0.6763[/C][C]0.251087[/C][/ROW]
[ROW][C]17[/C][C]-0.052118[/C][C]-0.3573[/C][C]0.361231[/C][/ROW]
[ROW][C]18[/C][C]-0.059908[/C][C]-0.4107[/C][C]0.341577[/C][/ROW]
[ROW][C]19[/C][C]0.025469[/C][C]0.1746[/C][C]0.431068[/C][/ROW]
[ROW][C]20[/C][C]-0.018526[/C][C]-0.127[/C][C]0.449738[/C][/ROW]
[ROW][C]21[/C][C]-0.02078[/C][C]-0.1425[/C][C]0.443661[/C][/ROW]
[ROW][C]22[/C][C]0.054246[/C][C]0.3719[/C][C]0.355824[/C][/ROW]
[ROW][C]23[/C][C]-0.002749[/C][C]-0.0188[/C][C]0.492521[/C][/ROW]
[ROW][C]24[/C][C]-0.146881[/C][C]-1.007[/C][C]0.159554[/C][/ROW]
[ROW][C]25[/C][C]-0.035326[/C][C]-0.2422[/C][C]0.404847[/C][/ROW]
[ROW][C]26[/C][C]-0.090798[/C][C]-0.6225[/C][C]0.268317[/C][/ROW]
[ROW][C]27[/C][C]-0.046444[/C][C]-0.3184[/C][C]0.375796[/C][/ROW]
[ROW][C]28[/C][C]-0.041638[/C][C]-0.2855[/C][C]0.388275[/C][/ROW]
[ROW][C]29[/C][C]0.079177[/C][C]0.5428[/C][C]0.294914[/C][/ROW]
[ROW][C]30[/C][C]-0.051981[/C][C]-0.3564[/C][C]0.361582[/C][/ROW]
[ROW][C]31[/C][C]0.044904[/C][C]0.3078[/C][C]0.37978[/C][/ROW]
[ROW][C]32[/C][C]-0.052372[/C][C]-0.359[/C][C]0.360584[/C][/ROW]
[ROW][C]33[/C][C]-0.03016[/C][C]-0.2068[/C][C]0.418542[/C][/ROW]
[ROW][C]34[/C][C]-0.045457[/C][C]-0.3116[/C][C]0.378346[/C][/ROW]
[ROW][C]35[/C][C]-0.038017[/C][C]-0.2606[/C][C]0.397759[/C][/ROW]
[ROW][C]36[/C][C]-0.033732[/C][C]-0.2313[/C][C]0.409061[/C][/ROW]
[ROW][C]37[/C][C]-0.075959[/C][C]-0.5208[/C][C]0.302492[/C][/ROW]
[ROW][C]38[/C][C]-0.014386[/C][C]-0.0986[/C][C]0.460927[/C][/ROW]
[ROW][C]39[/C][C]-0.053271[/C][C]-0.3652[/C][C]0.358298[/C][/ROW]
[ROW][C]40[/C][C]0.031371[/C][C]0.2151[/C][C]0.415321[/C][/ROW]
[ROW][C]41[/C][C]-0.08839[/C][C]-0.606[/C][C]0.273725[/C][/ROW]
[ROW][C]42[/C][C]0.032666[/C][C]0.2239[/C][C]0.411884[/C][/ROW]
[ROW][C]43[/C][C]0.021648[/C][C]0.1484[/C][C]0.441326[/C][/ROW]
[ROW][C]44[/C][C]-0.021051[/C][C]-0.1443[/C][C]0.442933[/C][/ROW]
[ROW][C]45[/C][C]-0.00904[/C][C]-0.062[/C][C]0.475423[/C][/ROW]
[ROW][C]46[/C][C]-0.04938[/C][C]-0.3385[/C][C]0.368234[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33177&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33177&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
1-0.060545-0.41510.339987
20.1032290.70770.241313
30.1596271.09430.13969
40.0997590.68390.248693
50.0395790.27130.393658
60.04220.28930.38681
70.0235190.16120.436299
80.0996580.68320.24891
9-0.022572-0.15470.438842
10-0.095694-0.6560.257496
110.2819861.93320.029624
12-0.162115-1.11140.136024
13-0.090386-0.61970.269239
140.0401360.27520.392199
15-0.07085-0.48570.31471
16-0.098646-0.67630.251087
17-0.052118-0.35730.361231
18-0.059908-0.41070.341577
190.0254690.17460.431068
20-0.018526-0.1270.449738
21-0.02078-0.14250.443661
220.0542460.37190.355824
23-0.002749-0.01880.492521
24-0.146881-1.0070.159554
25-0.035326-0.24220.404847
26-0.090798-0.62250.268317
27-0.046444-0.31840.375796
28-0.041638-0.28550.388275
290.0791770.54280.294914
30-0.051981-0.35640.361582
310.0449040.30780.37978
32-0.052372-0.3590.360584
33-0.03016-0.20680.418542
34-0.045457-0.31160.378346
35-0.038017-0.26060.397759
36-0.033732-0.23130.409061
37-0.075959-0.52080.302492
38-0.014386-0.09860.460927
39-0.053271-0.36520.358298
400.0313710.21510.415321
41-0.08839-0.6060.273725
420.0326660.22390.411884
430.0216480.14840.441326
44-0.021051-0.14430.442933
45-0.00904-0.0620.475423
46-0.04938-0.33850.368234
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.060545-0.41510.339987
20.0999290.68510.248329
30.1736671.19060.119894
40.1154580.79150.216304
50.0227870.15620.438265
6-0.002912-0.020.492078
7-0.016395-0.11240.455494
80.0787940.54020.295809
9-0.022281-0.15280.439624
10-0.132247-0.90660.184611
110.2538111.740.044199
12-0.126995-0.87060.19419
13-0.145274-0.9960.162187
14-0.001267-0.00870.496553
15-0.059729-0.40950.342023
16-0.074726-0.51230.305422
17-0.029458-0.2020.420413
18-0.01206-0.08270.46723
190.0313880.21520.415277
200.0671450.46030.323704
210.0711140.48750.314075
22-0.055472-0.38030.35272
230.0690910.47370.318967
24-0.122996-0.84320.201689
25-0.146556-1.00470.160084
26-0.080338-0.55080.2922
270.0045750.03140.487556
28-0.007557-0.05180.479452
290.1594931.09340.139889
30-0.03033-0.20790.41809
310.0247880.16990.432894
32-0.050064-0.34320.366482
33-0.072317-0.49580.311179
34-0.122371-0.83890.202877
350.0517990.35510.362045
360.0121160.08310.467078
37-0.077481-0.53120.298897
380.0183110.12550.450319
39-0.027519-0.18870.425586
40-0.063613-0.43610.332376
41-0.03774-0.25870.398487
42-0.026309-0.18040.42882
430.0478940.32830.372055
440.0523760.35910.360574
450.0644620.44190.330285
46-0.094177-0.64560.260825
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.060545 & -0.4151 & 0.339987 \tabularnewline
2 & 0.099929 & 0.6851 & 0.248329 \tabularnewline
3 & 0.173667 & 1.1906 & 0.119894 \tabularnewline
4 & 0.115458 & 0.7915 & 0.216304 \tabularnewline
5 & 0.022787 & 0.1562 & 0.438265 \tabularnewline
6 & -0.002912 & -0.02 & 0.492078 \tabularnewline
7 & -0.016395 & -0.1124 & 0.455494 \tabularnewline
8 & 0.078794 & 0.5402 & 0.295809 \tabularnewline
9 & -0.022281 & -0.1528 & 0.439624 \tabularnewline
10 & -0.132247 & -0.9066 & 0.184611 \tabularnewline
11 & 0.253811 & 1.74 & 0.044199 \tabularnewline
12 & -0.126995 & -0.8706 & 0.19419 \tabularnewline
13 & -0.145274 & -0.996 & 0.162187 \tabularnewline
14 & -0.001267 & -0.0087 & 0.496553 \tabularnewline
15 & -0.059729 & -0.4095 & 0.342023 \tabularnewline
16 & -0.074726 & -0.5123 & 0.305422 \tabularnewline
17 & -0.029458 & -0.202 & 0.420413 \tabularnewline
18 & -0.01206 & -0.0827 & 0.46723 \tabularnewline
19 & 0.031388 & 0.2152 & 0.415277 \tabularnewline
20 & 0.067145 & 0.4603 & 0.323704 \tabularnewline
21 & 0.071114 & 0.4875 & 0.314075 \tabularnewline
22 & -0.055472 & -0.3803 & 0.35272 \tabularnewline
23 & 0.069091 & 0.4737 & 0.318967 \tabularnewline
24 & -0.122996 & -0.8432 & 0.201689 \tabularnewline
25 & -0.146556 & -1.0047 & 0.160084 \tabularnewline
26 & -0.080338 & -0.5508 & 0.2922 \tabularnewline
27 & 0.004575 & 0.0314 & 0.487556 \tabularnewline
28 & -0.007557 & -0.0518 & 0.479452 \tabularnewline
29 & 0.159493 & 1.0934 & 0.139889 \tabularnewline
30 & -0.03033 & -0.2079 & 0.41809 \tabularnewline
31 & 0.024788 & 0.1699 & 0.432894 \tabularnewline
32 & -0.050064 & -0.3432 & 0.366482 \tabularnewline
33 & -0.072317 & -0.4958 & 0.311179 \tabularnewline
34 & -0.122371 & -0.8389 & 0.202877 \tabularnewline
35 & 0.051799 & 0.3551 & 0.362045 \tabularnewline
36 & 0.012116 & 0.0831 & 0.467078 \tabularnewline
37 & -0.077481 & -0.5312 & 0.298897 \tabularnewline
38 & 0.018311 & 0.1255 & 0.450319 \tabularnewline
39 & -0.027519 & -0.1887 & 0.425586 \tabularnewline
40 & -0.063613 & -0.4361 & 0.332376 \tabularnewline
41 & -0.03774 & -0.2587 & 0.398487 \tabularnewline
42 & -0.026309 & -0.1804 & 0.42882 \tabularnewline
43 & 0.047894 & 0.3283 & 0.372055 \tabularnewline
44 & 0.052376 & 0.3591 & 0.360574 \tabularnewline
45 & 0.064462 & 0.4419 & 0.330285 \tabularnewline
46 & -0.094177 & -0.6456 & 0.260825 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33177&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]-0.060545[/C][C]-0.4151[/C][C]0.339987[/C][/ROW]
[ROW][C]2[/C][C]0.099929[/C][C]0.6851[/C][C]0.248329[/C][/ROW]
[ROW][C]3[/C][C]0.173667[/C][C]1.1906[/C][C]0.119894[/C][/ROW]
[ROW][C]4[/C][C]0.115458[/C][C]0.7915[/C][C]0.216304[/C][/ROW]
[ROW][C]5[/C][C]0.022787[/C][C]0.1562[/C][C]0.438265[/C][/ROW]
[ROW][C]6[/C][C]-0.002912[/C][C]-0.02[/C][C]0.492078[/C][/ROW]
[ROW][C]7[/C][C]-0.016395[/C][C]-0.1124[/C][C]0.455494[/C][/ROW]
[ROW][C]8[/C][C]0.078794[/C][C]0.5402[/C][C]0.295809[/C][/ROW]
[ROW][C]9[/C][C]-0.022281[/C][C]-0.1528[/C][C]0.439624[/C][/ROW]
[ROW][C]10[/C][C]-0.132247[/C][C]-0.9066[/C][C]0.184611[/C][/ROW]
[ROW][C]11[/C][C]0.253811[/C][C]1.74[/C][C]0.044199[/C][/ROW]
[ROW][C]12[/C][C]-0.126995[/C][C]-0.8706[/C][C]0.19419[/C][/ROW]
[ROW][C]13[/C][C]-0.145274[/C][C]-0.996[/C][C]0.162187[/C][/ROW]
[ROW][C]14[/C][C]-0.001267[/C][C]-0.0087[/C][C]0.496553[/C][/ROW]
[ROW][C]15[/C][C]-0.059729[/C][C]-0.4095[/C][C]0.342023[/C][/ROW]
[ROW][C]16[/C][C]-0.074726[/C][C]-0.5123[/C][C]0.305422[/C][/ROW]
[ROW][C]17[/C][C]-0.029458[/C][C]-0.202[/C][C]0.420413[/C][/ROW]
[ROW][C]18[/C][C]-0.01206[/C][C]-0.0827[/C][C]0.46723[/C][/ROW]
[ROW][C]19[/C][C]0.031388[/C][C]0.2152[/C][C]0.415277[/C][/ROW]
[ROW][C]20[/C][C]0.067145[/C][C]0.4603[/C][C]0.323704[/C][/ROW]
[ROW][C]21[/C][C]0.071114[/C][C]0.4875[/C][C]0.314075[/C][/ROW]
[ROW][C]22[/C][C]-0.055472[/C][C]-0.3803[/C][C]0.35272[/C][/ROW]
[ROW][C]23[/C][C]0.069091[/C][C]0.4737[/C][C]0.318967[/C][/ROW]
[ROW][C]24[/C][C]-0.122996[/C][C]-0.8432[/C][C]0.201689[/C][/ROW]
[ROW][C]25[/C][C]-0.146556[/C][C]-1.0047[/C][C]0.160084[/C][/ROW]
[ROW][C]26[/C][C]-0.080338[/C][C]-0.5508[/C][C]0.2922[/C][/ROW]
[ROW][C]27[/C][C]0.004575[/C][C]0.0314[/C][C]0.487556[/C][/ROW]
[ROW][C]28[/C][C]-0.007557[/C][C]-0.0518[/C][C]0.479452[/C][/ROW]
[ROW][C]29[/C][C]0.159493[/C][C]1.0934[/C][C]0.139889[/C][/ROW]
[ROW][C]30[/C][C]-0.03033[/C][C]-0.2079[/C][C]0.41809[/C][/ROW]
[ROW][C]31[/C][C]0.024788[/C][C]0.1699[/C][C]0.432894[/C][/ROW]
[ROW][C]32[/C][C]-0.050064[/C][C]-0.3432[/C][C]0.366482[/C][/ROW]
[ROW][C]33[/C][C]-0.072317[/C][C]-0.4958[/C][C]0.311179[/C][/ROW]
[ROW][C]34[/C][C]-0.122371[/C][C]-0.8389[/C][C]0.202877[/C][/ROW]
[ROW][C]35[/C][C]0.051799[/C][C]0.3551[/C][C]0.362045[/C][/ROW]
[ROW][C]36[/C][C]0.012116[/C][C]0.0831[/C][C]0.467078[/C][/ROW]
[ROW][C]37[/C][C]-0.077481[/C][C]-0.5312[/C][C]0.298897[/C][/ROW]
[ROW][C]38[/C][C]0.018311[/C][C]0.1255[/C][C]0.450319[/C][/ROW]
[ROW][C]39[/C][C]-0.027519[/C][C]-0.1887[/C][C]0.425586[/C][/ROW]
[ROW][C]40[/C][C]-0.063613[/C][C]-0.4361[/C][C]0.332376[/C][/ROW]
[ROW][C]41[/C][C]-0.03774[/C][C]-0.2587[/C][C]0.398487[/C][/ROW]
[ROW][C]42[/C][C]-0.026309[/C][C]-0.1804[/C][C]0.42882[/C][/ROW]
[ROW][C]43[/C][C]0.047894[/C][C]0.3283[/C][C]0.372055[/C][/ROW]
[ROW][C]44[/C][C]0.052376[/C][C]0.3591[/C][C]0.360574[/C][/ROW]
[ROW][C]45[/C][C]0.064462[/C][C]0.4419[/C][C]0.330285[/C][/ROW]
[ROW][C]46[/C][C]-0.094177[/C][C]-0.6456[/C][C]0.260825[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33177&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33177&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
1-0.060545-0.41510.339987
20.0999290.68510.248329
30.1736671.19060.119894
40.1154580.79150.216304
50.0227870.15620.438265
6-0.002912-0.020.492078
7-0.016395-0.11240.455494
80.0787940.54020.295809
9-0.022281-0.15280.439624
10-0.132247-0.90660.184611
110.2538111.740.044199
12-0.126995-0.87060.19419
13-0.145274-0.9960.162187
14-0.001267-0.00870.496553
15-0.059729-0.40950.342023
16-0.074726-0.51230.305422
17-0.029458-0.2020.420413
18-0.01206-0.08270.46723
190.0313880.21520.415277
200.0671450.46030.323704
210.0711140.48750.314075
22-0.055472-0.38030.35272
230.0690910.47370.318967
24-0.122996-0.84320.201689
25-0.146556-1.00470.160084
26-0.080338-0.55080.2922
270.0045750.03140.487556
28-0.007557-0.05180.479452
290.1594931.09340.139889
30-0.03033-0.20790.41809
310.0247880.16990.432894
32-0.050064-0.34320.366482
33-0.072317-0.49580.311179
34-0.122371-0.83890.202877
350.0517990.35510.362045
360.0121160.08310.467078
37-0.077481-0.53120.298897
380.0183110.12550.450319
39-0.027519-0.18870.425586
40-0.063613-0.43610.332376
41-0.03774-0.25870.398487
42-0.026309-0.18040.42882
430.0478940.32830.372055
440.0523760.35910.360574
450.0644620.44190.330285
46-0.094177-0.64560.260825
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')