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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 computationMon, 30 Nov 2009 11:50:07 -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/2009/Nov/30/t1259607086318od2t1aa6s8p2.htm/, Retrieved Wed, 01 May 2024 22:27:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61857, Retrieved Wed, 01 May 2024 22:27:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [acf methode] [2009-11-25 20:17:41] [21324e9cdf3569788a3d630236984d87]
-   P     [(Partial) Autocorrelation Function] [acf methode] [2009-11-30 18:50:07] [bef26de542bed2eafc60fe4615b06e47] [Current]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-16 14:40:12] [f47feae0308dca73181bb669fbad1c56]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-16 14:50:06] [f47feae0308dca73181bb669fbad1c56]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-20 09:18:41] [f47feae0308dca73181bb669fbad1c56]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-20 09:30:33] [f47feae0308dca73181bb669fbad1c56]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-20 09:36:47] [f47feae0308dca73181bb669fbad1c56]
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Dataseries X:
121.6
118.8
114.0
111.5
97.2
102.5
113.4
109.8
104.9
126.1
80.0
96.8
117.2
112.3
117.3
111.1
102.2
104.3
122.9
107.6
121.3
131.5
89.0
104.4
128.9
135.9
133.3
121.3
120.5
120.4
137.9
126.1
133.2
151.1
105.0
119.0
140.4
156.6
137.1
122.7
125.8
139.3
134.9
149.2
132.3
149.0
117.2
119.6
152.0
149.4
127.3
114.1
102.1
107.7
104.4
102.1
96.0
109.3
90.0
83.9




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=61857&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=61857&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61857&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
10.5140893.98219.4e-05
20.2863532.21810.015173
30.3395612.63020.005413
40.3270692.53350.006962
50.384162.97570.002104
60.3992573.09260.001505
70.2596752.01140.024389
80.1014370.78570.217558
9-0.013223-0.10240.459382
10-0.122561-0.94940.173124
110.0274850.21290.416063
120.335012.5950.005937
13-0.010602-0.08210.467412
14-0.256963-1.99040.025553
15-0.158708-1.22930.11187
16-0.130946-1.01430.157256
17-0.063386-0.4910.312614
18-0.048742-0.37760.353546
19-0.118147-0.91520.181885
20-0.221249-1.71380.045865
21-0.28031-2.17130.016938
22-0.306575-2.37470.010388
23-0.196204-1.51980.066909
24-0.001257-0.00970.496133
25-0.19587-1.51720.067233
26-0.402158-3.11510.00141
27-0.282134-2.18540.016387
28-0.217903-1.68790.048314
29-0.188856-1.46290.074361
30-0.125673-0.97350.167116
31-0.166988-1.29350.1004
32-0.212469-1.64580.052519
33-0.226377-1.75350.042311
34-0.158773-1.22980.111778
35-0.114699-0.88850.188922
360.0384760.2980.383355
37-0.047907-0.37110.355939
38-0.171363-1.32740.094707
39-0.071759-0.55580.290192
40-0.026007-0.20140.420515
41-0.009496-0.07360.470806
420.071180.55140.291718
430.0462490.35820.36071
440.0176170.13650.445957
450.037330.28920.386729
460.0632680.49010.312934
470.0817820.63350.264413
480.1641771.27170.104192
490.125280.97040.167867
500.0622430.48210.315732
510.0923930.71570.238484
520.0698120.54080.295337
530.0597290.46270.322642
540.0733560.56820.286006
550.0532070.41210.340852
560.018430.14280.44348
570.0080190.06210.475338
58-0.004143-0.03210.487253
59-0.005199-0.04030.484004
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.514089 & 3.9821 & 9.4e-05 \tabularnewline
2 & 0.286353 & 2.2181 & 0.015173 \tabularnewline
3 & 0.339561 & 2.6302 & 0.005413 \tabularnewline
4 & 0.327069 & 2.5335 & 0.006962 \tabularnewline
5 & 0.38416 & 2.9757 & 0.002104 \tabularnewline
6 & 0.399257 & 3.0926 & 0.001505 \tabularnewline
7 & 0.259675 & 2.0114 & 0.024389 \tabularnewline
8 & 0.101437 & 0.7857 & 0.217558 \tabularnewline
9 & -0.013223 & -0.1024 & 0.459382 \tabularnewline
10 & -0.122561 & -0.9494 & 0.173124 \tabularnewline
11 & 0.027485 & 0.2129 & 0.416063 \tabularnewline
12 & 0.33501 & 2.595 & 0.005937 \tabularnewline
13 & -0.010602 & -0.0821 & 0.467412 \tabularnewline
14 & -0.256963 & -1.9904 & 0.025553 \tabularnewline
15 & -0.158708 & -1.2293 & 0.11187 \tabularnewline
16 & -0.130946 & -1.0143 & 0.157256 \tabularnewline
17 & -0.063386 & -0.491 & 0.312614 \tabularnewline
18 & -0.048742 & -0.3776 & 0.353546 \tabularnewline
19 & -0.118147 & -0.9152 & 0.181885 \tabularnewline
20 & -0.221249 & -1.7138 & 0.045865 \tabularnewline
21 & -0.28031 & -2.1713 & 0.016938 \tabularnewline
22 & -0.306575 & -2.3747 & 0.010388 \tabularnewline
23 & -0.196204 & -1.5198 & 0.066909 \tabularnewline
24 & -0.001257 & -0.0097 & 0.496133 \tabularnewline
25 & -0.19587 & -1.5172 & 0.067233 \tabularnewline
26 & -0.402158 & -3.1151 & 0.00141 \tabularnewline
27 & -0.282134 & -2.1854 & 0.016387 \tabularnewline
28 & -0.217903 & -1.6879 & 0.048314 \tabularnewline
29 & -0.188856 & -1.4629 & 0.074361 \tabularnewline
30 & -0.125673 & -0.9735 & 0.167116 \tabularnewline
31 & -0.166988 & -1.2935 & 0.1004 \tabularnewline
32 & -0.212469 & -1.6458 & 0.052519 \tabularnewline
33 & -0.226377 & -1.7535 & 0.042311 \tabularnewline
34 & -0.158773 & -1.2298 & 0.111778 \tabularnewline
35 & -0.114699 & -0.8885 & 0.188922 \tabularnewline
36 & 0.038476 & 0.298 & 0.383355 \tabularnewline
37 & -0.047907 & -0.3711 & 0.355939 \tabularnewline
38 & -0.171363 & -1.3274 & 0.094707 \tabularnewline
39 & -0.071759 & -0.5558 & 0.290192 \tabularnewline
40 & -0.026007 & -0.2014 & 0.420515 \tabularnewline
41 & -0.009496 & -0.0736 & 0.470806 \tabularnewline
42 & 0.07118 & 0.5514 & 0.291718 \tabularnewline
43 & 0.046249 & 0.3582 & 0.36071 \tabularnewline
44 & 0.017617 & 0.1365 & 0.445957 \tabularnewline
45 & 0.03733 & 0.2892 & 0.386729 \tabularnewline
46 & 0.063268 & 0.4901 & 0.312934 \tabularnewline
47 & 0.081782 & 0.6335 & 0.264413 \tabularnewline
48 & 0.164177 & 1.2717 & 0.104192 \tabularnewline
49 & 0.12528 & 0.9704 & 0.167867 \tabularnewline
50 & 0.062243 & 0.4821 & 0.315732 \tabularnewline
51 & 0.092393 & 0.7157 & 0.238484 \tabularnewline
52 & 0.069812 & 0.5408 & 0.295337 \tabularnewline
53 & 0.059729 & 0.4627 & 0.322642 \tabularnewline
54 & 0.073356 & 0.5682 & 0.286006 \tabularnewline
55 & 0.053207 & 0.4121 & 0.340852 \tabularnewline
56 & 0.01843 & 0.1428 & 0.44348 \tabularnewline
57 & 0.008019 & 0.0621 & 0.475338 \tabularnewline
58 & -0.004143 & -0.0321 & 0.487253 \tabularnewline
59 & -0.005199 & -0.0403 & 0.484004 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61857&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]0.514089[/C][C]3.9821[/C][C]9.4e-05[/C][/ROW]
[ROW][C]2[/C][C]0.286353[/C][C]2.2181[/C][C]0.015173[/C][/ROW]
[ROW][C]3[/C][C]0.339561[/C][C]2.6302[/C][C]0.005413[/C][/ROW]
[ROW][C]4[/C][C]0.327069[/C][C]2.5335[/C][C]0.006962[/C][/ROW]
[ROW][C]5[/C][C]0.38416[/C][C]2.9757[/C][C]0.002104[/C][/ROW]
[ROW][C]6[/C][C]0.399257[/C][C]3.0926[/C][C]0.001505[/C][/ROW]
[ROW][C]7[/C][C]0.259675[/C][C]2.0114[/C][C]0.024389[/C][/ROW]
[ROW][C]8[/C][C]0.101437[/C][C]0.7857[/C][C]0.217558[/C][/ROW]
[ROW][C]9[/C][C]-0.013223[/C][C]-0.1024[/C][C]0.459382[/C][/ROW]
[ROW][C]10[/C][C]-0.122561[/C][C]-0.9494[/C][C]0.173124[/C][/ROW]
[ROW][C]11[/C][C]0.027485[/C][C]0.2129[/C][C]0.416063[/C][/ROW]
[ROW][C]12[/C][C]0.33501[/C][C]2.595[/C][C]0.005937[/C][/ROW]
[ROW][C]13[/C][C]-0.010602[/C][C]-0.0821[/C][C]0.467412[/C][/ROW]
[ROW][C]14[/C][C]-0.256963[/C][C]-1.9904[/C][C]0.025553[/C][/ROW]
[ROW][C]15[/C][C]-0.158708[/C][C]-1.2293[/C][C]0.11187[/C][/ROW]
[ROW][C]16[/C][C]-0.130946[/C][C]-1.0143[/C][C]0.157256[/C][/ROW]
[ROW][C]17[/C][C]-0.063386[/C][C]-0.491[/C][C]0.312614[/C][/ROW]
[ROW][C]18[/C][C]-0.048742[/C][C]-0.3776[/C][C]0.353546[/C][/ROW]
[ROW][C]19[/C][C]-0.118147[/C][C]-0.9152[/C][C]0.181885[/C][/ROW]
[ROW][C]20[/C][C]-0.221249[/C][C]-1.7138[/C][C]0.045865[/C][/ROW]
[ROW][C]21[/C][C]-0.28031[/C][C]-2.1713[/C][C]0.016938[/C][/ROW]
[ROW][C]22[/C][C]-0.306575[/C][C]-2.3747[/C][C]0.010388[/C][/ROW]
[ROW][C]23[/C][C]-0.196204[/C][C]-1.5198[/C][C]0.066909[/C][/ROW]
[ROW][C]24[/C][C]-0.001257[/C][C]-0.0097[/C][C]0.496133[/C][/ROW]
[ROW][C]25[/C][C]-0.19587[/C][C]-1.5172[/C][C]0.067233[/C][/ROW]
[ROW][C]26[/C][C]-0.402158[/C][C]-3.1151[/C][C]0.00141[/C][/ROW]
[ROW][C]27[/C][C]-0.282134[/C][C]-2.1854[/C][C]0.016387[/C][/ROW]
[ROW][C]28[/C][C]-0.217903[/C][C]-1.6879[/C][C]0.048314[/C][/ROW]
[ROW][C]29[/C][C]-0.188856[/C][C]-1.4629[/C][C]0.074361[/C][/ROW]
[ROW][C]30[/C][C]-0.125673[/C][C]-0.9735[/C][C]0.167116[/C][/ROW]
[ROW][C]31[/C][C]-0.166988[/C][C]-1.2935[/C][C]0.1004[/C][/ROW]
[ROW][C]32[/C][C]-0.212469[/C][C]-1.6458[/C][C]0.052519[/C][/ROW]
[ROW][C]33[/C][C]-0.226377[/C][C]-1.7535[/C][C]0.042311[/C][/ROW]
[ROW][C]34[/C][C]-0.158773[/C][C]-1.2298[/C][C]0.111778[/C][/ROW]
[ROW][C]35[/C][C]-0.114699[/C][C]-0.8885[/C][C]0.188922[/C][/ROW]
[ROW][C]36[/C][C]0.038476[/C][C]0.298[/C][C]0.383355[/C][/ROW]
[ROW][C]37[/C][C]-0.047907[/C][C]-0.3711[/C][C]0.355939[/C][/ROW]
[ROW][C]38[/C][C]-0.171363[/C][C]-1.3274[/C][C]0.094707[/C][/ROW]
[ROW][C]39[/C][C]-0.071759[/C][C]-0.5558[/C][C]0.290192[/C][/ROW]
[ROW][C]40[/C][C]-0.026007[/C][C]-0.2014[/C][C]0.420515[/C][/ROW]
[ROW][C]41[/C][C]-0.009496[/C][C]-0.0736[/C][C]0.470806[/C][/ROW]
[ROW][C]42[/C][C]0.07118[/C][C]0.5514[/C][C]0.291718[/C][/ROW]
[ROW][C]43[/C][C]0.046249[/C][C]0.3582[/C][C]0.36071[/C][/ROW]
[ROW][C]44[/C][C]0.017617[/C][C]0.1365[/C][C]0.445957[/C][/ROW]
[ROW][C]45[/C][C]0.03733[/C][C]0.2892[/C][C]0.386729[/C][/ROW]
[ROW][C]46[/C][C]0.063268[/C][C]0.4901[/C][C]0.312934[/C][/ROW]
[ROW][C]47[/C][C]0.081782[/C][C]0.6335[/C][C]0.264413[/C][/ROW]
[ROW][C]48[/C][C]0.164177[/C][C]1.2717[/C][C]0.104192[/C][/ROW]
[ROW][C]49[/C][C]0.12528[/C][C]0.9704[/C][C]0.167867[/C][/ROW]
[ROW][C]50[/C][C]0.062243[/C][C]0.4821[/C][C]0.315732[/C][/ROW]
[ROW][C]51[/C][C]0.092393[/C][C]0.7157[/C][C]0.238484[/C][/ROW]
[ROW][C]52[/C][C]0.069812[/C][C]0.5408[/C][C]0.295337[/C][/ROW]
[ROW][C]53[/C][C]0.059729[/C][C]0.4627[/C][C]0.322642[/C][/ROW]
[ROW][C]54[/C][C]0.073356[/C][C]0.5682[/C][C]0.286006[/C][/ROW]
[ROW][C]55[/C][C]0.053207[/C][C]0.4121[/C][C]0.340852[/C][/ROW]
[ROW][C]56[/C][C]0.01843[/C][C]0.1428[/C][C]0.44348[/C][/ROW]
[ROW][C]57[/C][C]0.008019[/C][C]0.0621[/C][C]0.475338[/C][/ROW]
[ROW][C]58[/C][C]-0.004143[/C][C]-0.0321[/C][C]0.487253[/C][/ROW]
[ROW][C]59[/C][C]-0.005199[/C][C]-0.0403[/C][C]0.484004[/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=61857&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61857&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
10.5140893.98219.4e-05
20.2863532.21810.015173
30.3395612.63020.005413
40.3270692.53350.006962
50.384162.97570.002104
60.3992573.09260.001505
70.2596752.01140.024389
80.1014370.78570.217558
9-0.013223-0.10240.459382
10-0.122561-0.94940.173124
110.0274850.21290.416063
120.335012.5950.005937
13-0.010602-0.08210.467412
14-0.256963-1.99040.025553
15-0.158708-1.22930.11187
16-0.130946-1.01430.157256
17-0.063386-0.4910.312614
18-0.048742-0.37760.353546
19-0.118147-0.91520.181885
20-0.221249-1.71380.045865
21-0.28031-2.17130.016938
22-0.306575-2.37470.010388
23-0.196204-1.51980.066909
24-0.001257-0.00970.496133
25-0.19587-1.51720.067233
26-0.402158-3.11510.00141
27-0.282134-2.18540.016387
28-0.217903-1.68790.048314
29-0.188856-1.46290.074361
30-0.125673-0.97350.167116
31-0.166988-1.29350.1004
32-0.212469-1.64580.052519
33-0.226377-1.75350.042311
34-0.158773-1.22980.111778
35-0.114699-0.88850.188922
360.0384760.2980.383355
37-0.047907-0.37110.355939
38-0.171363-1.32740.094707
39-0.071759-0.55580.290192
40-0.026007-0.20140.420515
41-0.009496-0.07360.470806
420.071180.55140.291718
430.0462490.35820.36071
440.0176170.13650.445957
450.037330.28920.386729
460.0632680.49010.312934
470.0817820.63350.264413
480.1641771.27170.104192
490.125280.97040.167867
500.0622430.48210.315732
510.0923930.71570.238484
520.0698120.54080.295337
530.0597290.46270.322642
540.0733560.56820.286006
550.0532070.41210.340852
560.018430.14280.44348
570.0080190.06210.475338
58-0.004143-0.03210.487253
59-0.005199-0.04030.484004
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5140893.98219.4e-05
20.0299910.23230.408543
30.2467131.9110.030391
40.0870060.67390.251468
50.2280131.76620.041226
60.1264050.97910.165725
7-0.055646-0.4310.333996
8-0.171624-1.32940.094375
9-0.241126-1.86780.033341
10-0.322286-2.49640.007655
110.0631750.48940.313187
120.5406714.1884.7e-05
13-0.229463-1.77740.040285
14-0.229359-1.77660.040351
150.0085630.06630.473668
160.0228620.17710.430019
17-0.050683-0.39260.348008
18-0.19276-1.49310.070323
19-0.024499-0.18980.425067
20-0.021352-0.16540.434596
210.0508450.39380.347545
220.0688470.53330.297904
23-0.125292-0.97050.167845
24-0.196274-1.52030.06684
250.0209440.16220.435835
260.0345010.26720.395099
27-0.016173-0.12530.450363
28-0.109123-0.84530.20066
29-0.111731-0.86550.195117
300.1459551.13060.131369
310.0365150.28280.389136
32-0.008159-0.06320.47491
33-0.140487-1.08820.140428
340.0601510.46590.321476
35-0.095257-0.73790.23174
360.0238230.18450.42711
37-0.036291-0.28110.389797
380.0351480.27230.39318
39-0.063981-0.49560.310995
40-0.084935-0.65790.256557
410.0652980.50580.307427
420.0561710.43510.332527
430.0174710.13530.446402
44-0.005282-0.04090.483749
450.053620.41530.339688
46-0.137098-1.0620.146256
470.0112370.0870.465464
480.0142980.11070.456092
49-0.070647-0.54720.293124
50-0.03773-0.29230.385551
51-0.062842-0.48680.314097
520.036080.27950.390421
53-0.034442-0.26680.395274
54-0.145843-1.12970.131551
55-0.049129-0.38060.35244
560.0511790.39640.346596
57-0.013579-0.10520.458291
580.0100220.07760.469192
590.0371410.28770.387287
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.514089 & 3.9821 & 9.4e-05 \tabularnewline
2 & 0.029991 & 0.2323 & 0.408543 \tabularnewline
3 & 0.246713 & 1.911 & 0.030391 \tabularnewline
4 & 0.087006 & 0.6739 & 0.251468 \tabularnewline
5 & 0.228013 & 1.7662 & 0.041226 \tabularnewline
6 & 0.126405 & 0.9791 & 0.165725 \tabularnewline
7 & -0.055646 & -0.431 & 0.333996 \tabularnewline
8 & -0.171624 & -1.3294 & 0.094375 \tabularnewline
9 & -0.241126 & -1.8678 & 0.033341 \tabularnewline
10 & -0.322286 & -2.4964 & 0.007655 \tabularnewline
11 & 0.063175 & 0.4894 & 0.313187 \tabularnewline
12 & 0.540671 & 4.188 & 4.7e-05 \tabularnewline
13 & -0.229463 & -1.7774 & 0.040285 \tabularnewline
14 & -0.229359 & -1.7766 & 0.040351 \tabularnewline
15 & 0.008563 & 0.0663 & 0.473668 \tabularnewline
16 & 0.022862 & 0.1771 & 0.430019 \tabularnewline
17 & -0.050683 & -0.3926 & 0.348008 \tabularnewline
18 & -0.19276 & -1.4931 & 0.070323 \tabularnewline
19 & -0.024499 & -0.1898 & 0.425067 \tabularnewline
20 & -0.021352 & -0.1654 & 0.434596 \tabularnewline
21 & 0.050845 & 0.3938 & 0.347545 \tabularnewline
22 & 0.068847 & 0.5333 & 0.297904 \tabularnewline
23 & -0.125292 & -0.9705 & 0.167845 \tabularnewline
24 & -0.196274 & -1.5203 & 0.06684 \tabularnewline
25 & 0.020944 & 0.1622 & 0.435835 \tabularnewline
26 & 0.034501 & 0.2672 & 0.395099 \tabularnewline
27 & -0.016173 & -0.1253 & 0.450363 \tabularnewline
28 & -0.109123 & -0.8453 & 0.20066 \tabularnewline
29 & -0.111731 & -0.8655 & 0.195117 \tabularnewline
30 & 0.145955 & 1.1306 & 0.131369 \tabularnewline
31 & 0.036515 & 0.2828 & 0.389136 \tabularnewline
32 & -0.008159 & -0.0632 & 0.47491 \tabularnewline
33 & -0.140487 & -1.0882 & 0.140428 \tabularnewline
34 & 0.060151 & 0.4659 & 0.321476 \tabularnewline
35 & -0.095257 & -0.7379 & 0.23174 \tabularnewline
36 & 0.023823 & 0.1845 & 0.42711 \tabularnewline
37 & -0.036291 & -0.2811 & 0.389797 \tabularnewline
38 & 0.035148 & 0.2723 & 0.39318 \tabularnewline
39 & -0.063981 & -0.4956 & 0.310995 \tabularnewline
40 & -0.084935 & -0.6579 & 0.256557 \tabularnewline
41 & 0.065298 & 0.5058 & 0.307427 \tabularnewline
42 & 0.056171 & 0.4351 & 0.332527 \tabularnewline
43 & 0.017471 & 0.1353 & 0.446402 \tabularnewline
44 & -0.005282 & -0.0409 & 0.483749 \tabularnewline
45 & 0.05362 & 0.4153 & 0.339688 \tabularnewline
46 & -0.137098 & -1.062 & 0.146256 \tabularnewline
47 & 0.011237 & 0.087 & 0.465464 \tabularnewline
48 & 0.014298 & 0.1107 & 0.456092 \tabularnewline
49 & -0.070647 & -0.5472 & 0.293124 \tabularnewline
50 & -0.03773 & -0.2923 & 0.385551 \tabularnewline
51 & -0.062842 & -0.4868 & 0.314097 \tabularnewline
52 & 0.03608 & 0.2795 & 0.390421 \tabularnewline
53 & -0.034442 & -0.2668 & 0.395274 \tabularnewline
54 & -0.145843 & -1.1297 & 0.131551 \tabularnewline
55 & -0.049129 & -0.3806 & 0.35244 \tabularnewline
56 & 0.051179 & 0.3964 & 0.346596 \tabularnewline
57 & -0.013579 & -0.1052 & 0.458291 \tabularnewline
58 & 0.010022 & 0.0776 & 0.469192 \tabularnewline
59 & 0.037141 & 0.2877 & 0.387287 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61857&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]0.514089[/C][C]3.9821[/C][C]9.4e-05[/C][/ROW]
[ROW][C]2[/C][C]0.029991[/C][C]0.2323[/C][C]0.408543[/C][/ROW]
[ROW][C]3[/C][C]0.246713[/C][C]1.911[/C][C]0.030391[/C][/ROW]
[ROW][C]4[/C][C]0.087006[/C][C]0.6739[/C][C]0.251468[/C][/ROW]
[ROW][C]5[/C][C]0.228013[/C][C]1.7662[/C][C]0.041226[/C][/ROW]
[ROW][C]6[/C][C]0.126405[/C][C]0.9791[/C][C]0.165725[/C][/ROW]
[ROW][C]7[/C][C]-0.055646[/C][C]-0.431[/C][C]0.333996[/C][/ROW]
[ROW][C]8[/C][C]-0.171624[/C][C]-1.3294[/C][C]0.094375[/C][/ROW]
[ROW][C]9[/C][C]-0.241126[/C][C]-1.8678[/C][C]0.033341[/C][/ROW]
[ROW][C]10[/C][C]-0.322286[/C][C]-2.4964[/C][C]0.007655[/C][/ROW]
[ROW][C]11[/C][C]0.063175[/C][C]0.4894[/C][C]0.313187[/C][/ROW]
[ROW][C]12[/C][C]0.540671[/C][C]4.188[/C][C]4.7e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.229463[/C][C]-1.7774[/C][C]0.040285[/C][/ROW]
[ROW][C]14[/C][C]-0.229359[/C][C]-1.7766[/C][C]0.040351[/C][/ROW]
[ROW][C]15[/C][C]0.008563[/C][C]0.0663[/C][C]0.473668[/C][/ROW]
[ROW][C]16[/C][C]0.022862[/C][C]0.1771[/C][C]0.430019[/C][/ROW]
[ROW][C]17[/C][C]-0.050683[/C][C]-0.3926[/C][C]0.348008[/C][/ROW]
[ROW][C]18[/C][C]-0.19276[/C][C]-1.4931[/C][C]0.070323[/C][/ROW]
[ROW][C]19[/C][C]-0.024499[/C][C]-0.1898[/C][C]0.425067[/C][/ROW]
[ROW][C]20[/C][C]-0.021352[/C][C]-0.1654[/C][C]0.434596[/C][/ROW]
[ROW][C]21[/C][C]0.050845[/C][C]0.3938[/C][C]0.347545[/C][/ROW]
[ROW][C]22[/C][C]0.068847[/C][C]0.5333[/C][C]0.297904[/C][/ROW]
[ROW][C]23[/C][C]-0.125292[/C][C]-0.9705[/C][C]0.167845[/C][/ROW]
[ROW][C]24[/C][C]-0.196274[/C][C]-1.5203[/C][C]0.06684[/C][/ROW]
[ROW][C]25[/C][C]0.020944[/C][C]0.1622[/C][C]0.435835[/C][/ROW]
[ROW][C]26[/C][C]0.034501[/C][C]0.2672[/C][C]0.395099[/C][/ROW]
[ROW][C]27[/C][C]-0.016173[/C][C]-0.1253[/C][C]0.450363[/C][/ROW]
[ROW][C]28[/C][C]-0.109123[/C][C]-0.8453[/C][C]0.20066[/C][/ROW]
[ROW][C]29[/C][C]-0.111731[/C][C]-0.8655[/C][C]0.195117[/C][/ROW]
[ROW][C]30[/C][C]0.145955[/C][C]1.1306[/C][C]0.131369[/C][/ROW]
[ROW][C]31[/C][C]0.036515[/C][C]0.2828[/C][C]0.389136[/C][/ROW]
[ROW][C]32[/C][C]-0.008159[/C][C]-0.0632[/C][C]0.47491[/C][/ROW]
[ROW][C]33[/C][C]-0.140487[/C][C]-1.0882[/C][C]0.140428[/C][/ROW]
[ROW][C]34[/C][C]0.060151[/C][C]0.4659[/C][C]0.321476[/C][/ROW]
[ROW][C]35[/C][C]-0.095257[/C][C]-0.7379[/C][C]0.23174[/C][/ROW]
[ROW][C]36[/C][C]0.023823[/C][C]0.1845[/C][C]0.42711[/C][/ROW]
[ROW][C]37[/C][C]-0.036291[/C][C]-0.2811[/C][C]0.389797[/C][/ROW]
[ROW][C]38[/C][C]0.035148[/C][C]0.2723[/C][C]0.39318[/C][/ROW]
[ROW][C]39[/C][C]-0.063981[/C][C]-0.4956[/C][C]0.310995[/C][/ROW]
[ROW][C]40[/C][C]-0.084935[/C][C]-0.6579[/C][C]0.256557[/C][/ROW]
[ROW][C]41[/C][C]0.065298[/C][C]0.5058[/C][C]0.307427[/C][/ROW]
[ROW][C]42[/C][C]0.056171[/C][C]0.4351[/C][C]0.332527[/C][/ROW]
[ROW][C]43[/C][C]0.017471[/C][C]0.1353[/C][C]0.446402[/C][/ROW]
[ROW][C]44[/C][C]-0.005282[/C][C]-0.0409[/C][C]0.483749[/C][/ROW]
[ROW][C]45[/C][C]0.05362[/C][C]0.4153[/C][C]0.339688[/C][/ROW]
[ROW][C]46[/C][C]-0.137098[/C][C]-1.062[/C][C]0.146256[/C][/ROW]
[ROW][C]47[/C][C]0.011237[/C][C]0.087[/C][C]0.465464[/C][/ROW]
[ROW][C]48[/C][C]0.014298[/C][C]0.1107[/C][C]0.456092[/C][/ROW]
[ROW][C]49[/C][C]-0.070647[/C][C]-0.5472[/C][C]0.293124[/C][/ROW]
[ROW][C]50[/C][C]-0.03773[/C][C]-0.2923[/C][C]0.385551[/C][/ROW]
[ROW][C]51[/C][C]-0.062842[/C][C]-0.4868[/C][C]0.314097[/C][/ROW]
[ROW][C]52[/C][C]0.03608[/C][C]0.2795[/C][C]0.390421[/C][/ROW]
[ROW][C]53[/C][C]-0.034442[/C][C]-0.2668[/C][C]0.395274[/C][/ROW]
[ROW][C]54[/C][C]-0.145843[/C][C]-1.1297[/C][C]0.131551[/C][/ROW]
[ROW][C]55[/C][C]-0.049129[/C][C]-0.3806[/C][C]0.35244[/C][/ROW]
[ROW][C]56[/C][C]0.051179[/C][C]0.3964[/C][C]0.346596[/C][/ROW]
[ROW][C]57[/C][C]-0.013579[/C][C]-0.1052[/C][C]0.458291[/C][/ROW]
[ROW][C]58[/C][C]0.010022[/C][C]0.0776[/C][C]0.469192[/C][/ROW]
[ROW][C]59[/C][C]0.037141[/C][C]0.2877[/C][C]0.387287[/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=61857&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61857&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
10.5140893.98219.4e-05
20.0299910.23230.408543
30.2467131.9110.030391
40.0870060.67390.251468
50.2280131.76620.041226
60.1264050.97910.165725
7-0.055646-0.4310.333996
8-0.171624-1.32940.094375
9-0.241126-1.86780.033341
10-0.322286-2.49640.007655
110.0631750.48940.313187
120.5406714.1884.7e-05
13-0.229463-1.77740.040285
14-0.229359-1.77660.040351
150.0085630.06630.473668
160.0228620.17710.430019
17-0.050683-0.39260.348008
18-0.19276-1.49310.070323
19-0.024499-0.18980.425067
20-0.021352-0.16540.434596
210.0508450.39380.347545
220.0688470.53330.297904
23-0.125292-0.97050.167845
24-0.196274-1.52030.06684
250.0209440.16220.435835
260.0345010.26720.395099
27-0.016173-0.12530.450363
28-0.109123-0.84530.20066
29-0.111731-0.86550.195117
300.1459551.13060.131369
310.0365150.28280.389136
32-0.008159-0.06320.47491
33-0.140487-1.08820.140428
340.0601510.46590.321476
35-0.095257-0.73790.23174
360.0238230.18450.42711
37-0.036291-0.28110.389797
380.0351480.27230.39318
39-0.063981-0.49560.310995
40-0.084935-0.65790.256557
410.0652980.50580.307427
420.0561710.43510.332527
430.0174710.13530.446402
44-0.005282-0.04090.483749
450.053620.41530.339688
46-0.137098-1.0620.146256
470.0112370.0870.465464
480.0142980.11070.456092
49-0.070647-0.54720.293124
50-0.03773-0.29230.385551
51-0.062842-0.48680.314097
520.036080.27950.390421
53-0.034442-0.26680.395274
54-0.145843-1.12970.131551
55-0.049129-0.38060.35244
560.0511790.39640.346596
57-0.013579-0.10520.458291
580.0100220.07760.469192
590.0371410.28770.387287
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')