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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 05 Dec 2011 04:59:47 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/05/t1323079224bj8d1dnwfn425rp.htm/, Retrieved Thu, 31 Oct 2024 22:50:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=150812, Retrieved Thu, 31 Oct 2024 22:50:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- R PD            [(Partial) Autocorrelation Function] [Workshop 9 (] [2011-12-05 09:59:47] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626




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

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150812&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150812&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150812&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' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5803234.92423e-06
20.1692921.43650.077597
3-0.022645-0.19210.424084
4-0.334884-2.84160.002917
5-0.557729-4.73255e-06
6-0.653629-5.54620
7-0.526616-4.46851.4e-05
8-0.269955-2.29060.012457
90.0043880.03720.4852
100.1702591.44470.076441
110.5059584.29322.7e-05
120.8235586.98810
130.4912064.1684.2e-05
140.1497161.27040.104019
15-0.009742-0.08270.467173
16-0.271984-2.30790.011942
17-0.452441-3.83910.000131
18-0.533287-4.52511.2e-05
19-0.427058-3.62370.000269
20-0.217796-1.84810.03435
21-0.009846-0.08350.466824
220.1307291.10930.135501
230.3909473.31730.000714
240.6494995.51120
250.4077613.460.000456
260.116830.99130.162422
27-0.003018-0.02560.489821
28-0.199177-1.69010.04767
29-0.35361-3.00050.001851
30-0.413491-3.50860.00039
31-0.333684-2.83140.003002
32-0.17491-1.48420.071065
33-0.009183-0.07790.469055
340.1013170.85970.196404
350.2823852.39610.009585
360.4935884.18823.9e-05
370.3142472.66650.00473
380.0909340.77160.221439
390.0020290.01720.493156
40-0.150154-1.27410.103363
41-0.258135-2.19030.015869
42-0.30089-2.55310.006397
43-0.239205-2.02970.02304
44-0.127352-1.08060.141737
45-0.0043-0.03650.485499
460.0733950.62280.267698
470.1886741.6010.056883
480.3350122.84270.002909

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.580323 & 4.9242 & 3e-06 \tabularnewline
2 & 0.169292 & 1.4365 & 0.077597 \tabularnewline
3 & -0.022645 & -0.1921 & 0.424084 \tabularnewline
4 & -0.334884 & -2.8416 & 0.002917 \tabularnewline
5 & -0.557729 & -4.7325 & 5e-06 \tabularnewline
6 & -0.653629 & -5.5462 & 0 \tabularnewline
7 & -0.526616 & -4.4685 & 1.4e-05 \tabularnewline
8 & -0.269955 & -2.2906 & 0.012457 \tabularnewline
9 & 0.004388 & 0.0372 & 0.4852 \tabularnewline
10 & 0.170259 & 1.4447 & 0.076441 \tabularnewline
11 & 0.505958 & 4.2932 & 2.7e-05 \tabularnewline
12 & 0.823558 & 6.9881 & 0 \tabularnewline
13 & 0.491206 & 4.168 & 4.2e-05 \tabularnewline
14 & 0.149716 & 1.2704 & 0.104019 \tabularnewline
15 & -0.009742 & -0.0827 & 0.467173 \tabularnewline
16 & -0.271984 & -2.3079 & 0.011942 \tabularnewline
17 & -0.452441 & -3.8391 & 0.000131 \tabularnewline
18 & -0.533287 & -4.5251 & 1.2e-05 \tabularnewline
19 & -0.427058 & -3.6237 & 0.000269 \tabularnewline
20 & -0.217796 & -1.8481 & 0.03435 \tabularnewline
21 & -0.009846 & -0.0835 & 0.466824 \tabularnewline
22 & 0.130729 & 1.1093 & 0.135501 \tabularnewline
23 & 0.390947 & 3.3173 & 0.000714 \tabularnewline
24 & 0.649499 & 5.5112 & 0 \tabularnewline
25 & 0.407761 & 3.46 & 0.000456 \tabularnewline
26 & 0.11683 & 0.9913 & 0.162422 \tabularnewline
27 & -0.003018 & -0.0256 & 0.489821 \tabularnewline
28 & -0.199177 & -1.6901 & 0.04767 \tabularnewline
29 & -0.35361 & -3.0005 & 0.001851 \tabularnewline
30 & -0.413491 & -3.5086 & 0.00039 \tabularnewline
31 & -0.333684 & -2.8314 & 0.003002 \tabularnewline
32 & -0.17491 & -1.4842 & 0.071065 \tabularnewline
33 & -0.009183 & -0.0779 & 0.469055 \tabularnewline
34 & 0.101317 & 0.8597 & 0.196404 \tabularnewline
35 & 0.282385 & 2.3961 & 0.009585 \tabularnewline
36 & 0.493588 & 4.1882 & 3.9e-05 \tabularnewline
37 & 0.314247 & 2.6665 & 0.00473 \tabularnewline
38 & 0.090934 & 0.7716 & 0.221439 \tabularnewline
39 & 0.002029 & 0.0172 & 0.493156 \tabularnewline
40 & -0.150154 & -1.2741 & 0.103363 \tabularnewline
41 & -0.258135 & -2.1903 & 0.015869 \tabularnewline
42 & -0.30089 & -2.5531 & 0.006397 \tabularnewline
43 & -0.239205 & -2.0297 & 0.02304 \tabularnewline
44 & -0.127352 & -1.0806 & 0.141737 \tabularnewline
45 & -0.0043 & -0.0365 & 0.485499 \tabularnewline
46 & 0.073395 & 0.6228 & 0.267698 \tabularnewline
47 & 0.188674 & 1.601 & 0.056883 \tabularnewline
48 & 0.335012 & 2.8427 & 0.002909 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150812&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]0.580323[/C][C]4.9242[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.169292[/C][C]1.4365[/C][C]0.077597[/C][/ROW]
[ROW][C]3[/C][C]-0.022645[/C][C]-0.1921[/C][C]0.424084[/C][/ROW]
[ROW][C]4[/C][C]-0.334884[/C][C]-2.8416[/C][C]0.002917[/C][/ROW]
[ROW][C]5[/C][C]-0.557729[/C][C]-4.7325[/C][C]5e-06[/C][/ROW]
[ROW][C]6[/C][C]-0.653629[/C][C]-5.5462[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.526616[/C][C]-4.4685[/C][C]1.4e-05[/C][/ROW]
[ROW][C]8[/C][C]-0.269955[/C][C]-2.2906[/C][C]0.012457[/C][/ROW]
[ROW][C]9[/C][C]0.004388[/C][C]0.0372[/C][C]0.4852[/C][/ROW]
[ROW][C]10[/C][C]0.170259[/C][C]1.4447[/C][C]0.076441[/C][/ROW]
[ROW][C]11[/C][C]0.505958[/C][C]4.2932[/C][C]2.7e-05[/C][/ROW]
[ROW][C]12[/C][C]0.823558[/C][C]6.9881[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.491206[/C][C]4.168[/C][C]4.2e-05[/C][/ROW]
[ROW][C]14[/C][C]0.149716[/C][C]1.2704[/C][C]0.104019[/C][/ROW]
[ROW][C]15[/C][C]-0.009742[/C][C]-0.0827[/C][C]0.467173[/C][/ROW]
[ROW][C]16[/C][C]-0.271984[/C][C]-2.3079[/C][C]0.011942[/C][/ROW]
[ROW][C]17[/C][C]-0.452441[/C][C]-3.8391[/C][C]0.000131[/C][/ROW]
[ROW][C]18[/C][C]-0.533287[/C][C]-4.5251[/C][C]1.2e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.427058[/C][C]-3.6237[/C][C]0.000269[/C][/ROW]
[ROW][C]20[/C][C]-0.217796[/C][C]-1.8481[/C][C]0.03435[/C][/ROW]
[ROW][C]21[/C][C]-0.009846[/C][C]-0.0835[/C][C]0.466824[/C][/ROW]
[ROW][C]22[/C][C]0.130729[/C][C]1.1093[/C][C]0.135501[/C][/ROW]
[ROW][C]23[/C][C]0.390947[/C][C]3.3173[/C][C]0.000714[/C][/ROW]
[ROW][C]24[/C][C]0.649499[/C][C]5.5112[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.407761[/C][C]3.46[/C][C]0.000456[/C][/ROW]
[ROW][C]26[/C][C]0.11683[/C][C]0.9913[/C][C]0.162422[/C][/ROW]
[ROW][C]27[/C][C]-0.003018[/C][C]-0.0256[/C][C]0.489821[/C][/ROW]
[ROW][C]28[/C][C]-0.199177[/C][C]-1.6901[/C][C]0.04767[/C][/ROW]
[ROW][C]29[/C][C]-0.35361[/C][C]-3.0005[/C][C]0.001851[/C][/ROW]
[ROW][C]30[/C][C]-0.413491[/C][C]-3.5086[/C][C]0.00039[/C][/ROW]
[ROW][C]31[/C][C]-0.333684[/C][C]-2.8314[/C][C]0.003002[/C][/ROW]
[ROW][C]32[/C][C]-0.17491[/C][C]-1.4842[/C][C]0.071065[/C][/ROW]
[ROW][C]33[/C][C]-0.009183[/C][C]-0.0779[/C][C]0.469055[/C][/ROW]
[ROW][C]34[/C][C]0.101317[/C][C]0.8597[/C][C]0.196404[/C][/ROW]
[ROW][C]35[/C][C]0.282385[/C][C]2.3961[/C][C]0.009585[/C][/ROW]
[ROW][C]36[/C][C]0.493588[/C][C]4.1882[/C][C]3.9e-05[/C][/ROW]
[ROW][C]37[/C][C]0.314247[/C][C]2.6665[/C][C]0.00473[/C][/ROW]
[ROW][C]38[/C][C]0.090934[/C][C]0.7716[/C][C]0.221439[/C][/ROW]
[ROW][C]39[/C][C]0.002029[/C][C]0.0172[/C][C]0.493156[/C][/ROW]
[ROW][C]40[/C][C]-0.150154[/C][C]-1.2741[/C][C]0.103363[/C][/ROW]
[ROW][C]41[/C][C]-0.258135[/C][C]-2.1903[/C][C]0.015869[/C][/ROW]
[ROW][C]42[/C][C]-0.30089[/C][C]-2.5531[/C][C]0.006397[/C][/ROW]
[ROW][C]43[/C][C]-0.239205[/C][C]-2.0297[/C][C]0.02304[/C][/ROW]
[ROW][C]44[/C][C]-0.127352[/C][C]-1.0806[/C][C]0.141737[/C][/ROW]
[ROW][C]45[/C][C]-0.0043[/C][C]-0.0365[/C][C]0.485499[/C][/ROW]
[ROW][C]46[/C][C]0.073395[/C][C]0.6228[/C][C]0.267698[/C][/ROW]
[ROW][C]47[/C][C]0.188674[/C][C]1.601[/C][C]0.056883[/C][/ROW]
[ROW][C]48[/C][C]0.335012[/C][C]2.8427[/C][C]0.002909[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150812&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150812&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
10.5803234.92423e-06
20.1692921.43650.077597
3-0.022645-0.19210.424084
4-0.334884-2.84160.002917
5-0.557729-4.73255e-06
6-0.653629-5.54620
7-0.526616-4.46851.4e-05
8-0.269955-2.29060.012457
90.0043880.03720.4852
100.1702591.44470.076441
110.5059584.29322.7e-05
120.8235586.98810
130.4912064.1684.2e-05
140.1497161.27040.104019
15-0.009742-0.08270.467173
16-0.271984-2.30790.011942
17-0.452441-3.83910.000131
18-0.533287-4.52511.2e-05
19-0.427058-3.62370.000269
20-0.217796-1.84810.03435
21-0.009846-0.08350.466824
220.1307291.10930.135501
230.3909473.31730.000714
240.6494995.51120
250.4077613.460.000456
260.116830.99130.162422
27-0.003018-0.02560.489821
28-0.199177-1.69010.04767
29-0.35361-3.00050.001851
30-0.413491-3.50860.00039
31-0.333684-2.83140.003002
32-0.17491-1.48420.071065
33-0.009183-0.07790.469055
340.1013170.85970.196404
350.2823852.39610.009585
360.4935884.18823.9e-05
370.3142472.66650.00473
380.0909340.77160.221439
390.0020290.01720.493156
40-0.150154-1.27410.103363
41-0.258135-2.19030.015869
42-0.30089-2.55310.006397
43-0.239205-2.02970.02304
44-0.127352-1.08060.141737
45-0.0043-0.03650.485499
460.0733950.62280.267698
470.1886741.6010.056883
480.3350122.84270.002909







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5803234.92423e-06
2-0.252529-2.14280.017756
30.001370.01160.49538
4-0.444964-3.77560.000163
5-0.239114-2.02890.023081
6-0.455135-3.86190.000122
7-0.155908-1.32290.095024
8-0.296482-2.51570.007055
9-0.137955-1.17060.122813
10-0.570015-4.83674e-06
110.2425912.05850.021583
120.2444862.07450.020803
13-0.384684-3.26420.000841
14-0.140458-1.19180.118622
15-0.111465-0.94580.173704
16-0.001189-0.01010.49599
170.0018820.0160.493652
180.0133290.11310.455132
190.0106440.09030.464142
20-0.109556-0.92960.177839
210.0173480.14720.441691
22-0.002071-0.01760.493013
23-0.029062-0.24660.40296
240.0292940.24860.402201
250.0163750.13890.44494
26-0.110983-0.94170.174743
270.0074310.06310.474948
280.0078010.06620.473705
29-0.017509-0.14860.441153
300.0219140.18590.426504
31-0.026431-0.22430.41159
32-0.01444-0.12250.451411
330.0378320.3210.374565
340.0275650.23390.407864
35-0.046318-0.3930.347731
360.0016120.01370.494563
37-0.064318-0.54580.293459
380.1071350.90910.183174
39-0.118181-1.00280.159658
400.0353760.30020.382454
41-0.025096-0.21290.415986
420.0231190.19620.422516
430.0226960.19260.423916
440.0153370.13010.448411
450.0216960.18410.427226
460.0302360.25660.399126
470.0018420.01560.493785
48-0.082264-0.6980.243703

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.580323 & 4.9242 & 3e-06 \tabularnewline
2 & -0.252529 & -2.1428 & 0.017756 \tabularnewline
3 & 0.00137 & 0.0116 & 0.49538 \tabularnewline
4 & -0.444964 & -3.7756 & 0.000163 \tabularnewline
5 & -0.239114 & -2.0289 & 0.023081 \tabularnewline
6 & -0.455135 & -3.8619 & 0.000122 \tabularnewline
7 & -0.155908 & -1.3229 & 0.095024 \tabularnewline
8 & -0.296482 & -2.5157 & 0.007055 \tabularnewline
9 & -0.137955 & -1.1706 & 0.122813 \tabularnewline
10 & -0.570015 & -4.8367 & 4e-06 \tabularnewline
11 & 0.242591 & 2.0585 & 0.021583 \tabularnewline
12 & 0.244486 & 2.0745 & 0.020803 \tabularnewline
13 & -0.384684 & -3.2642 & 0.000841 \tabularnewline
14 & -0.140458 & -1.1918 & 0.118622 \tabularnewline
15 & -0.111465 & -0.9458 & 0.173704 \tabularnewline
16 & -0.001189 & -0.0101 & 0.49599 \tabularnewline
17 & 0.001882 & 0.016 & 0.493652 \tabularnewline
18 & 0.013329 & 0.1131 & 0.455132 \tabularnewline
19 & 0.010644 & 0.0903 & 0.464142 \tabularnewline
20 & -0.109556 & -0.9296 & 0.177839 \tabularnewline
21 & 0.017348 & 0.1472 & 0.441691 \tabularnewline
22 & -0.002071 & -0.0176 & 0.493013 \tabularnewline
23 & -0.029062 & -0.2466 & 0.40296 \tabularnewline
24 & 0.029294 & 0.2486 & 0.402201 \tabularnewline
25 & 0.016375 & 0.1389 & 0.44494 \tabularnewline
26 & -0.110983 & -0.9417 & 0.174743 \tabularnewline
27 & 0.007431 & 0.0631 & 0.474948 \tabularnewline
28 & 0.007801 & 0.0662 & 0.473705 \tabularnewline
29 & -0.017509 & -0.1486 & 0.441153 \tabularnewline
30 & 0.021914 & 0.1859 & 0.426504 \tabularnewline
31 & -0.026431 & -0.2243 & 0.41159 \tabularnewline
32 & -0.01444 & -0.1225 & 0.451411 \tabularnewline
33 & 0.037832 & 0.321 & 0.374565 \tabularnewline
34 & 0.027565 & 0.2339 & 0.407864 \tabularnewline
35 & -0.046318 & -0.393 & 0.347731 \tabularnewline
36 & 0.001612 & 0.0137 & 0.494563 \tabularnewline
37 & -0.064318 & -0.5458 & 0.293459 \tabularnewline
38 & 0.107135 & 0.9091 & 0.183174 \tabularnewline
39 & -0.118181 & -1.0028 & 0.159658 \tabularnewline
40 & 0.035376 & 0.3002 & 0.382454 \tabularnewline
41 & -0.025096 & -0.2129 & 0.415986 \tabularnewline
42 & 0.023119 & 0.1962 & 0.422516 \tabularnewline
43 & 0.022696 & 0.1926 & 0.423916 \tabularnewline
44 & 0.015337 & 0.1301 & 0.448411 \tabularnewline
45 & 0.021696 & 0.1841 & 0.427226 \tabularnewline
46 & 0.030236 & 0.2566 & 0.399126 \tabularnewline
47 & 0.001842 & 0.0156 & 0.493785 \tabularnewline
48 & -0.082264 & -0.698 & 0.243703 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150812&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]0.580323[/C][C]4.9242[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.252529[/C][C]-2.1428[/C][C]0.017756[/C][/ROW]
[ROW][C]3[/C][C]0.00137[/C][C]0.0116[/C][C]0.49538[/C][/ROW]
[ROW][C]4[/C][C]-0.444964[/C][C]-3.7756[/C][C]0.000163[/C][/ROW]
[ROW][C]5[/C][C]-0.239114[/C][C]-2.0289[/C][C]0.023081[/C][/ROW]
[ROW][C]6[/C][C]-0.455135[/C][C]-3.8619[/C][C]0.000122[/C][/ROW]
[ROW][C]7[/C][C]-0.155908[/C][C]-1.3229[/C][C]0.095024[/C][/ROW]
[ROW][C]8[/C][C]-0.296482[/C][C]-2.5157[/C][C]0.007055[/C][/ROW]
[ROW][C]9[/C][C]-0.137955[/C][C]-1.1706[/C][C]0.122813[/C][/ROW]
[ROW][C]10[/C][C]-0.570015[/C][C]-4.8367[/C][C]4e-06[/C][/ROW]
[ROW][C]11[/C][C]0.242591[/C][C]2.0585[/C][C]0.021583[/C][/ROW]
[ROW][C]12[/C][C]0.244486[/C][C]2.0745[/C][C]0.020803[/C][/ROW]
[ROW][C]13[/C][C]-0.384684[/C][C]-3.2642[/C][C]0.000841[/C][/ROW]
[ROW][C]14[/C][C]-0.140458[/C][C]-1.1918[/C][C]0.118622[/C][/ROW]
[ROW][C]15[/C][C]-0.111465[/C][C]-0.9458[/C][C]0.173704[/C][/ROW]
[ROW][C]16[/C][C]-0.001189[/C][C]-0.0101[/C][C]0.49599[/C][/ROW]
[ROW][C]17[/C][C]0.001882[/C][C]0.016[/C][C]0.493652[/C][/ROW]
[ROW][C]18[/C][C]0.013329[/C][C]0.1131[/C][C]0.455132[/C][/ROW]
[ROW][C]19[/C][C]0.010644[/C][C]0.0903[/C][C]0.464142[/C][/ROW]
[ROW][C]20[/C][C]-0.109556[/C][C]-0.9296[/C][C]0.177839[/C][/ROW]
[ROW][C]21[/C][C]0.017348[/C][C]0.1472[/C][C]0.441691[/C][/ROW]
[ROW][C]22[/C][C]-0.002071[/C][C]-0.0176[/C][C]0.493013[/C][/ROW]
[ROW][C]23[/C][C]-0.029062[/C][C]-0.2466[/C][C]0.40296[/C][/ROW]
[ROW][C]24[/C][C]0.029294[/C][C]0.2486[/C][C]0.402201[/C][/ROW]
[ROW][C]25[/C][C]0.016375[/C][C]0.1389[/C][C]0.44494[/C][/ROW]
[ROW][C]26[/C][C]-0.110983[/C][C]-0.9417[/C][C]0.174743[/C][/ROW]
[ROW][C]27[/C][C]0.007431[/C][C]0.0631[/C][C]0.474948[/C][/ROW]
[ROW][C]28[/C][C]0.007801[/C][C]0.0662[/C][C]0.473705[/C][/ROW]
[ROW][C]29[/C][C]-0.017509[/C][C]-0.1486[/C][C]0.441153[/C][/ROW]
[ROW][C]30[/C][C]0.021914[/C][C]0.1859[/C][C]0.426504[/C][/ROW]
[ROW][C]31[/C][C]-0.026431[/C][C]-0.2243[/C][C]0.41159[/C][/ROW]
[ROW][C]32[/C][C]-0.01444[/C][C]-0.1225[/C][C]0.451411[/C][/ROW]
[ROW][C]33[/C][C]0.037832[/C][C]0.321[/C][C]0.374565[/C][/ROW]
[ROW][C]34[/C][C]0.027565[/C][C]0.2339[/C][C]0.407864[/C][/ROW]
[ROW][C]35[/C][C]-0.046318[/C][C]-0.393[/C][C]0.347731[/C][/ROW]
[ROW][C]36[/C][C]0.001612[/C][C]0.0137[/C][C]0.494563[/C][/ROW]
[ROW][C]37[/C][C]-0.064318[/C][C]-0.5458[/C][C]0.293459[/C][/ROW]
[ROW][C]38[/C][C]0.107135[/C][C]0.9091[/C][C]0.183174[/C][/ROW]
[ROW][C]39[/C][C]-0.118181[/C][C]-1.0028[/C][C]0.159658[/C][/ROW]
[ROW][C]40[/C][C]0.035376[/C][C]0.3002[/C][C]0.382454[/C][/ROW]
[ROW][C]41[/C][C]-0.025096[/C][C]-0.2129[/C][C]0.415986[/C][/ROW]
[ROW][C]42[/C][C]0.023119[/C][C]0.1962[/C][C]0.422516[/C][/ROW]
[ROW][C]43[/C][C]0.022696[/C][C]0.1926[/C][C]0.423916[/C][/ROW]
[ROW][C]44[/C][C]0.015337[/C][C]0.1301[/C][C]0.448411[/C][/ROW]
[ROW][C]45[/C][C]0.021696[/C][C]0.1841[/C][C]0.427226[/C][/ROW]
[ROW][C]46[/C][C]0.030236[/C][C]0.2566[/C][C]0.399126[/C][/ROW]
[ROW][C]47[/C][C]0.001842[/C][C]0.0156[/C][C]0.493785[/C][/ROW]
[ROW][C]48[/C][C]-0.082264[/C][C]-0.698[/C][C]0.243703[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150812&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150812&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
10.5803234.92423e-06
2-0.252529-2.14280.017756
30.001370.01160.49538
4-0.444964-3.77560.000163
5-0.239114-2.02890.023081
6-0.455135-3.86190.000122
7-0.155908-1.32290.095024
8-0.296482-2.51570.007055
9-0.137955-1.17060.122813
10-0.570015-4.83674e-06
110.2425912.05850.021583
120.2444862.07450.020803
13-0.384684-3.26420.000841
14-0.140458-1.19180.118622
15-0.111465-0.94580.173704
16-0.001189-0.01010.49599
170.0018820.0160.493652
180.0133290.11310.455132
190.0106440.09030.464142
20-0.109556-0.92960.177839
210.0173480.14720.441691
22-0.002071-0.01760.493013
23-0.029062-0.24660.40296
240.0292940.24860.402201
250.0163750.13890.44494
26-0.110983-0.94170.174743
270.0074310.06310.474948
280.0078010.06620.473705
29-0.017509-0.14860.441153
300.0219140.18590.426504
31-0.026431-0.22430.41159
32-0.01444-0.12250.451411
330.0378320.3210.374565
340.0275650.23390.407864
35-0.046318-0.3930.347731
360.0016120.01370.494563
37-0.064318-0.54580.293459
380.1071350.90910.183174
39-0.118181-1.00280.159658
400.0353760.30020.382454
41-0.025096-0.21290.415986
420.0231190.19620.422516
430.0226960.19260.423916
440.0153370.13010.448411
450.0216960.18410.427226
460.0302360.25660.399126
470.0018420.01560.493785
48-0.082264-0.6980.243703



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 (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')