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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 computationFri, 21 Dec 2012 16:29:41 -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/2012/Dec/21/t1356125403hngrqp67nl3bam3.htm/, Retrieved Fri, 29 Mar 2024 08:41:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204303, Retrieved Fri, 29 Mar 2024 08:41:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact70
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [WS 9 Autocorrelatie ] [2010-12-03 12:44:11] [8081b8996d5947580de3eb171e82db4f]
-   P       [(Partial) Autocorrelation Function] [Verbetering WS9] [2010-12-14 19:15:43] [3635fb7041b1998c5a1332cf9de22bce]
- R PD        [(Partial) Autocorrelation Function] [W9 - autocorrelatie] [2012-12-04 22:01:22] [3ae574fa1d645ef9b19cadb6c0dbd022]
- R P           [(Partial) Autocorrelation Function] [W9 - autocorrelatie] [2012-12-04 22:07:43] [3ae574fa1d645ef9b19cadb6c0dbd022]
-   P               [(Partial) Autocorrelation Function] [Paper - D4 - ACF] [2012-12-21 21:29:41] [bc8de944878a372a2f96eab55bfa1be2] [Current]
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Dataseries X:
46
62
66
59
58
61
41
27
58
70
49
59
44
36
72
45
56
54
53
35
61
52
47
51
52
63
74
45
51
64
36
30
55
64
39
40
63
45
59
55
40
64
27
28
45
57
45
69
60
56
58
50
51
53
37
22
55
70
62
58
39
49
58
47
42
62
39
40
72
70
54
65




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204303&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204303&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204303&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0118710.0920.46352
20.0388380.30080.382289
3-0.109458-0.84790.199943
4-0.051329-0.39760.34617
5-0.100997-0.78230.218551
6-0.053604-0.41520.339734
70.0281010.21770.414214
80.033530.25970.397983
9-0.006097-0.04720.481245
100.0649770.50330.308294
110.1569071.21540.114488
12-0.377489-2.9240.002435
13-0.09635-0.74630.229193
14-0.016226-0.12570.450201
150.0168480.13050.448301
16-0.034247-0.26530.395853
17-0.041658-0.32270.37403
180.0465180.36030.359933
190.0130480.10110.459917
20-0.034798-0.26950.394217
210.1215210.94130.175162
220.2013181.55940.06208
230.0024690.01910.492404
24-0.012794-0.09910.460694
250.1028630.79680.214362
26-0.175247-1.35750.08986
270.0306530.23740.406564
28-0.040357-0.31260.377833
290.1617031.25250.107615
30-0.038844-0.30090.382273
31-0.036432-0.28220.38938
320.1044060.80870.210933
330.0205350.15910.437077
34-0.141926-1.09940.138002
35-0.130004-1.0070.158988
36-0.089845-0.69590.244578
37-0.118484-0.91780.181206
380.1110920.86050.196465
39-0.007568-0.05860.476723
400.0894590.69290.245509
41-0.107584-0.83330.203979
420.0522580.40480.343536
430.0474430.36750.357272
44-0.03135-0.24280.40448
45-0.091577-0.70940.240426
46-0.002297-0.01780.49293
470.0737110.5710.285078
480.0497690.38550.350612

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.011871 & 0.092 & 0.46352 \tabularnewline
2 & 0.038838 & 0.3008 & 0.382289 \tabularnewline
3 & -0.109458 & -0.8479 & 0.199943 \tabularnewline
4 & -0.051329 & -0.3976 & 0.34617 \tabularnewline
5 & -0.100997 & -0.7823 & 0.218551 \tabularnewline
6 & -0.053604 & -0.4152 & 0.339734 \tabularnewline
7 & 0.028101 & 0.2177 & 0.414214 \tabularnewline
8 & 0.03353 & 0.2597 & 0.397983 \tabularnewline
9 & -0.006097 & -0.0472 & 0.481245 \tabularnewline
10 & 0.064977 & 0.5033 & 0.308294 \tabularnewline
11 & 0.156907 & 1.2154 & 0.114488 \tabularnewline
12 & -0.377489 & -2.924 & 0.002435 \tabularnewline
13 & -0.09635 & -0.7463 & 0.229193 \tabularnewline
14 & -0.016226 & -0.1257 & 0.450201 \tabularnewline
15 & 0.016848 & 0.1305 & 0.448301 \tabularnewline
16 & -0.034247 & -0.2653 & 0.395853 \tabularnewline
17 & -0.041658 & -0.3227 & 0.37403 \tabularnewline
18 & 0.046518 & 0.3603 & 0.359933 \tabularnewline
19 & 0.013048 & 0.1011 & 0.459917 \tabularnewline
20 & -0.034798 & -0.2695 & 0.394217 \tabularnewline
21 & 0.121521 & 0.9413 & 0.175162 \tabularnewline
22 & 0.201318 & 1.5594 & 0.06208 \tabularnewline
23 & 0.002469 & 0.0191 & 0.492404 \tabularnewline
24 & -0.012794 & -0.0991 & 0.460694 \tabularnewline
25 & 0.102863 & 0.7968 & 0.214362 \tabularnewline
26 & -0.175247 & -1.3575 & 0.08986 \tabularnewline
27 & 0.030653 & 0.2374 & 0.406564 \tabularnewline
28 & -0.040357 & -0.3126 & 0.377833 \tabularnewline
29 & 0.161703 & 1.2525 & 0.107615 \tabularnewline
30 & -0.038844 & -0.3009 & 0.382273 \tabularnewline
31 & -0.036432 & -0.2822 & 0.38938 \tabularnewline
32 & 0.104406 & 0.8087 & 0.210933 \tabularnewline
33 & 0.020535 & 0.1591 & 0.437077 \tabularnewline
34 & -0.141926 & -1.0994 & 0.138002 \tabularnewline
35 & -0.130004 & -1.007 & 0.158988 \tabularnewline
36 & -0.089845 & -0.6959 & 0.244578 \tabularnewline
37 & -0.118484 & -0.9178 & 0.181206 \tabularnewline
38 & 0.111092 & 0.8605 & 0.196465 \tabularnewline
39 & -0.007568 & -0.0586 & 0.476723 \tabularnewline
40 & 0.089459 & 0.6929 & 0.245509 \tabularnewline
41 & -0.107584 & -0.8333 & 0.203979 \tabularnewline
42 & 0.052258 & 0.4048 & 0.343536 \tabularnewline
43 & 0.047443 & 0.3675 & 0.357272 \tabularnewline
44 & -0.03135 & -0.2428 & 0.40448 \tabularnewline
45 & -0.091577 & -0.7094 & 0.240426 \tabularnewline
46 & -0.002297 & -0.0178 & 0.49293 \tabularnewline
47 & 0.073711 & 0.571 & 0.285078 \tabularnewline
48 & 0.049769 & 0.3855 & 0.350612 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204303&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]0.011871[/C][C]0.092[/C][C]0.46352[/C][/ROW]
[ROW][C]2[/C][C]0.038838[/C][C]0.3008[/C][C]0.382289[/C][/ROW]
[ROW][C]3[/C][C]-0.109458[/C][C]-0.8479[/C][C]0.199943[/C][/ROW]
[ROW][C]4[/C][C]-0.051329[/C][C]-0.3976[/C][C]0.34617[/C][/ROW]
[ROW][C]5[/C][C]-0.100997[/C][C]-0.7823[/C][C]0.218551[/C][/ROW]
[ROW][C]6[/C][C]-0.053604[/C][C]-0.4152[/C][C]0.339734[/C][/ROW]
[ROW][C]7[/C][C]0.028101[/C][C]0.2177[/C][C]0.414214[/C][/ROW]
[ROW][C]8[/C][C]0.03353[/C][C]0.2597[/C][C]0.397983[/C][/ROW]
[ROW][C]9[/C][C]-0.006097[/C][C]-0.0472[/C][C]0.481245[/C][/ROW]
[ROW][C]10[/C][C]0.064977[/C][C]0.5033[/C][C]0.308294[/C][/ROW]
[ROW][C]11[/C][C]0.156907[/C][C]1.2154[/C][C]0.114488[/C][/ROW]
[ROW][C]12[/C][C]-0.377489[/C][C]-2.924[/C][C]0.002435[/C][/ROW]
[ROW][C]13[/C][C]-0.09635[/C][C]-0.7463[/C][C]0.229193[/C][/ROW]
[ROW][C]14[/C][C]-0.016226[/C][C]-0.1257[/C][C]0.450201[/C][/ROW]
[ROW][C]15[/C][C]0.016848[/C][C]0.1305[/C][C]0.448301[/C][/ROW]
[ROW][C]16[/C][C]-0.034247[/C][C]-0.2653[/C][C]0.395853[/C][/ROW]
[ROW][C]17[/C][C]-0.041658[/C][C]-0.3227[/C][C]0.37403[/C][/ROW]
[ROW][C]18[/C][C]0.046518[/C][C]0.3603[/C][C]0.359933[/C][/ROW]
[ROW][C]19[/C][C]0.013048[/C][C]0.1011[/C][C]0.459917[/C][/ROW]
[ROW][C]20[/C][C]-0.034798[/C][C]-0.2695[/C][C]0.394217[/C][/ROW]
[ROW][C]21[/C][C]0.121521[/C][C]0.9413[/C][C]0.175162[/C][/ROW]
[ROW][C]22[/C][C]0.201318[/C][C]1.5594[/C][C]0.06208[/C][/ROW]
[ROW][C]23[/C][C]0.002469[/C][C]0.0191[/C][C]0.492404[/C][/ROW]
[ROW][C]24[/C][C]-0.012794[/C][C]-0.0991[/C][C]0.460694[/C][/ROW]
[ROW][C]25[/C][C]0.102863[/C][C]0.7968[/C][C]0.214362[/C][/ROW]
[ROW][C]26[/C][C]-0.175247[/C][C]-1.3575[/C][C]0.08986[/C][/ROW]
[ROW][C]27[/C][C]0.030653[/C][C]0.2374[/C][C]0.406564[/C][/ROW]
[ROW][C]28[/C][C]-0.040357[/C][C]-0.3126[/C][C]0.377833[/C][/ROW]
[ROW][C]29[/C][C]0.161703[/C][C]1.2525[/C][C]0.107615[/C][/ROW]
[ROW][C]30[/C][C]-0.038844[/C][C]-0.3009[/C][C]0.382273[/C][/ROW]
[ROW][C]31[/C][C]-0.036432[/C][C]-0.2822[/C][C]0.38938[/C][/ROW]
[ROW][C]32[/C][C]0.104406[/C][C]0.8087[/C][C]0.210933[/C][/ROW]
[ROW][C]33[/C][C]0.020535[/C][C]0.1591[/C][C]0.437077[/C][/ROW]
[ROW][C]34[/C][C]-0.141926[/C][C]-1.0994[/C][C]0.138002[/C][/ROW]
[ROW][C]35[/C][C]-0.130004[/C][C]-1.007[/C][C]0.158988[/C][/ROW]
[ROW][C]36[/C][C]-0.089845[/C][C]-0.6959[/C][C]0.244578[/C][/ROW]
[ROW][C]37[/C][C]-0.118484[/C][C]-0.9178[/C][C]0.181206[/C][/ROW]
[ROW][C]38[/C][C]0.111092[/C][C]0.8605[/C][C]0.196465[/C][/ROW]
[ROW][C]39[/C][C]-0.007568[/C][C]-0.0586[/C][C]0.476723[/C][/ROW]
[ROW][C]40[/C][C]0.089459[/C][C]0.6929[/C][C]0.245509[/C][/ROW]
[ROW][C]41[/C][C]-0.107584[/C][C]-0.8333[/C][C]0.203979[/C][/ROW]
[ROW][C]42[/C][C]0.052258[/C][C]0.4048[/C][C]0.343536[/C][/ROW]
[ROW][C]43[/C][C]0.047443[/C][C]0.3675[/C][C]0.357272[/C][/ROW]
[ROW][C]44[/C][C]-0.03135[/C][C]-0.2428[/C][C]0.40448[/C][/ROW]
[ROW][C]45[/C][C]-0.091577[/C][C]-0.7094[/C][C]0.240426[/C][/ROW]
[ROW][C]46[/C][C]-0.002297[/C][C]-0.0178[/C][C]0.49293[/C][/ROW]
[ROW][C]47[/C][C]0.073711[/C][C]0.571[/C][C]0.285078[/C][/ROW]
[ROW][C]48[/C][C]0.049769[/C][C]0.3855[/C][C]0.350612[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204303&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204303&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
10.0118710.0920.46352
20.0388380.30080.382289
3-0.109458-0.84790.199943
4-0.051329-0.39760.34617
5-0.100997-0.78230.218551
6-0.053604-0.41520.339734
70.0281010.21770.414214
80.033530.25970.397983
9-0.006097-0.04720.481245
100.0649770.50330.308294
110.1569071.21540.114488
12-0.377489-2.9240.002435
13-0.09635-0.74630.229193
14-0.016226-0.12570.450201
150.0168480.13050.448301
16-0.034247-0.26530.395853
17-0.041658-0.32270.37403
180.0465180.36030.359933
190.0130480.10110.459917
20-0.034798-0.26950.394217
210.1215210.94130.175162
220.2013181.55940.06208
230.0024690.01910.492404
24-0.012794-0.09910.460694
250.1028630.79680.214362
26-0.175247-1.35750.08986
270.0306530.23740.406564
28-0.040357-0.31260.377833
290.1617031.25250.107615
30-0.038844-0.30090.382273
31-0.036432-0.28220.38938
320.1044060.80870.210933
330.0205350.15910.437077
34-0.141926-1.09940.138002
35-0.130004-1.0070.158988
36-0.089845-0.69590.244578
37-0.118484-0.91780.181206
380.1110920.86050.196465
39-0.007568-0.05860.476723
400.0894590.69290.245509
41-0.107584-0.83330.203979
420.0522580.40480.343536
430.0474430.36750.357272
44-0.03135-0.24280.40448
45-0.091577-0.70940.240426
46-0.002297-0.01780.49293
470.0737110.5710.285078
480.0497690.38550.350612







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0118710.0920.46352
20.0387030.29980.382687
3-0.110542-0.85630.197632
4-0.050551-0.39160.348382
5-0.092534-0.71680.238149
6-0.061508-0.47640.317745
70.0250320.19390.423457
80.0139560.10810.457137
9-0.030892-0.23930.405848
100.0561540.4350.332573
110.1597281.23720.110408
12-0.404385-3.13240.00134
13-0.085833-0.66490.254343
140.0852240.66010.255844
15-0.058001-0.44930.327428
16-0.078982-0.61180.271493
17-0.101249-0.78430.217984
18-0.014741-0.11420.454737
190.0186150.14420.442918
20-0.044979-0.34840.364376
210.0715690.55440.290692
220.2709462.09870.020028
230.1488741.15320.126707
24-0.218469-1.69230.047892
250.1068920.8280.20548
26-0.112728-0.87320.193021
270.095170.73720.231942
280.003770.02920.488399
290.0449510.34820.364458
30-0.028402-0.220.413309
31-0.050087-0.3880.349705
320.0364450.28230.389341
330.0220790.1710.432389
340.0927040.71810.237748
35-0.06715-0.52010.30244
36-0.203944-1.57970.059712
370.0081320.0630.47499
380.0403830.31280.377756
39-0.008698-0.06740.473255
40-0.033694-0.2610.397496
41-0.014272-0.11060.456171
420.0524120.4060.343101
43-0.09859-0.76370.224028
44-0.09507-0.73640.232176
45-0.004163-0.03220.487192
460.0981840.76050.224959
470.014080.10910.456759
48-0.098513-0.76310.224203

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.011871 & 0.092 & 0.46352 \tabularnewline
2 & 0.038703 & 0.2998 & 0.382687 \tabularnewline
3 & -0.110542 & -0.8563 & 0.197632 \tabularnewline
4 & -0.050551 & -0.3916 & 0.348382 \tabularnewline
5 & -0.092534 & -0.7168 & 0.238149 \tabularnewline
6 & -0.061508 & -0.4764 & 0.317745 \tabularnewline
7 & 0.025032 & 0.1939 & 0.423457 \tabularnewline
8 & 0.013956 & 0.1081 & 0.457137 \tabularnewline
9 & -0.030892 & -0.2393 & 0.405848 \tabularnewline
10 & 0.056154 & 0.435 & 0.332573 \tabularnewline
11 & 0.159728 & 1.2372 & 0.110408 \tabularnewline
12 & -0.404385 & -3.1324 & 0.00134 \tabularnewline
13 & -0.085833 & -0.6649 & 0.254343 \tabularnewline
14 & 0.085224 & 0.6601 & 0.255844 \tabularnewline
15 & -0.058001 & -0.4493 & 0.327428 \tabularnewline
16 & -0.078982 & -0.6118 & 0.271493 \tabularnewline
17 & -0.101249 & -0.7843 & 0.217984 \tabularnewline
18 & -0.014741 & -0.1142 & 0.454737 \tabularnewline
19 & 0.018615 & 0.1442 & 0.442918 \tabularnewline
20 & -0.044979 & -0.3484 & 0.364376 \tabularnewline
21 & 0.071569 & 0.5544 & 0.290692 \tabularnewline
22 & 0.270946 & 2.0987 & 0.020028 \tabularnewline
23 & 0.148874 & 1.1532 & 0.126707 \tabularnewline
24 & -0.218469 & -1.6923 & 0.047892 \tabularnewline
25 & 0.106892 & 0.828 & 0.20548 \tabularnewline
26 & -0.112728 & -0.8732 & 0.193021 \tabularnewline
27 & 0.09517 & 0.7372 & 0.231942 \tabularnewline
28 & 0.00377 & 0.0292 & 0.488399 \tabularnewline
29 & 0.044951 & 0.3482 & 0.364458 \tabularnewline
30 & -0.028402 & -0.22 & 0.413309 \tabularnewline
31 & -0.050087 & -0.388 & 0.349705 \tabularnewline
32 & 0.036445 & 0.2823 & 0.389341 \tabularnewline
33 & 0.022079 & 0.171 & 0.432389 \tabularnewline
34 & 0.092704 & 0.7181 & 0.237748 \tabularnewline
35 & -0.06715 & -0.5201 & 0.30244 \tabularnewline
36 & -0.203944 & -1.5797 & 0.059712 \tabularnewline
37 & 0.008132 & 0.063 & 0.47499 \tabularnewline
38 & 0.040383 & 0.3128 & 0.377756 \tabularnewline
39 & -0.008698 & -0.0674 & 0.473255 \tabularnewline
40 & -0.033694 & -0.261 & 0.397496 \tabularnewline
41 & -0.014272 & -0.1106 & 0.456171 \tabularnewline
42 & 0.052412 & 0.406 & 0.343101 \tabularnewline
43 & -0.09859 & -0.7637 & 0.224028 \tabularnewline
44 & -0.09507 & -0.7364 & 0.232176 \tabularnewline
45 & -0.004163 & -0.0322 & 0.487192 \tabularnewline
46 & 0.098184 & 0.7605 & 0.224959 \tabularnewline
47 & 0.01408 & 0.1091 & 0.456759 \tabularnewline
48 & -0.098513 & -0.7631 & 0.224203 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204303&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]0.011871[/C][C]0.092[/C][C]0.46352[/C][/ROW]
[ROW][C]2[/C][C]0.038703[/C][C]0.2998[/C][C]0.382687[/C][/ROW]
[ROW][C]3[/C][C]-0.110542[/C][C]-0.8563[/C][C]0.197632[/C][/ROW]
[ROW][C]4[/C][C]-0.050551[/C][C]-0.3916[/C][C]0.348382[/C][/ROW]
[ROW][C]5[/C][C]-0.092534[/C][C]-0.7168[/C][C]0.238149[/C][/ROW]
[ROW][C]6[/C][C]-0.061508[/C][C]-0.4764[/C][C]0.317745[/C][/ROW]
[ROW][C]7[/C][C]0.025032[/C][C]0.1939[/C][C]0.423457[/C][/ROW]
[ROW][C]8[/C][C]0.013956[/C][C]0.1081[/C][C]0.457137[/C][/ROW]
[ROW][C]9[/C][C]-0.030892[/C][C]-0.2393[/C][C]0.405848[/C][/ROW]
[ROW][C]10[/C][C]0.056154[/C][C]0.435[/C][C]0.332573[/C][/ROW]
[ROW][C]11[/C][C]0.159728[/C][C]1.2372[/C][C]0.110408[/C][/ROW]
[ROW][C]12[/C][C]-0.404385[/C][C]-3.1324[/C][C]0.00134[/C][/ROW]
[ROW][C]13[/C][C]-0.085833[/C][C]-0.6649[/C][C]0.254343[/C][/ROW]
[ROW][C]14[/C][C]0.085224[/C][C]0.6601[/C][C]0.255844[/C][/ROW]
[ROW][C]15[/C][C]-0.058001[/C][C]-0.4493[/C][C]0.327428[/C][/ROW]
[ROW][C]16[/C][C]-0.078982[/C][C]-0.6118[/C][C]0.271493[/C][/ROW]
[ROW][C]17[/C][C]-0.101249[/C][C]-0.7843[/C][C]0.217984[/C][/ROW]
[ROW][C]18[/C][C]-0.014741[/C][C]-0.1142[/C][C]0.454737[/C][/ROW]
[ROW][C]19[/C][C]0.018615[/C][C]0.1442[/C][C]0.442918[/C][/ROW]
[ROW][C]20[/C][C]-0.044979[/C][C]-0.3484[/C][C]0.364376[/C][/ROW]
[ROW][C]21[/C][C]0.071569[/C][C]0.5544[/C][C]0.290692[/C][/ROW]
[ROW][C]22[/C][C]0.270946[/C][C]2.0987[/C][C]0.020028[/C][/ROW]
[ROW][C]23[/C][C]0.148874[/C][C]1.1532[/C][C]0.126707[/C][/ROW]
[ROW][C]24[/C][C]-0.218469[/C][C]-1.6923[/C][C]0.047892[/C][/ROW]
[ROW][C]25[/C][C]0.106892[/C][C]0.828[/C][C]0.20548[/C][/ROW]
[ROW][C]26[/C][C]-0.112728[/C][C]-0.8732[/C][C]0.193021[/C][/ROW]
[ROW][C]27[/C][C]0.09517[/C][C]0.7372[/C][C]0.231942[/C][/ROW]
[ROW][C]28[/C][C]0.00377[/C][C]0.0292[/C][C]0.488399[/C][/ROW]
[ROW][C]29[/C][C]0.044951[/C][C]0.3482[/C][C]0.364458[/C][/ROW]
[ROW][C]30[/C][C]-0.028402[/C][C]-0.22[/C][C]0.413309[/C][/ROW]
[ROW][C]31[/C][C]-0.050087[/C][C]-0.388[/C][C]0.349705[/C][/ROW]
[ROW][C]32[/C][C]0.036445[/C][C]0.2823[/C][C]0.389341[/C][/ROW]
[ROW][C]33[/C][C]0.022079[/C][C]0.171[/C][C]0.432389[/C][/ROW]
[ROW][C]34[/C][C]0.092704[/C][C]0.7181[/C][C]0.237748[/C][/ROW]
[ROW][C]35[/C][C]-0.06715[/C][C]-0.5201[/C][C]0.30244[/C][/ROW]
[ROW][C]36[/C][C]-0.203944[/C][C]-1.5797[/C][C]0.059712[/C][/ROW]
[ROW][C]37[/C][C]0.008132[/C][C]0.063[/C][C]0.47499[/C][/ROW]
[ROW][C]38[/C][C]0.040383[/C][C]0.3128[/C][C]0.377756[/C][/ROW]
[ROW][C]39[/C][C]-0.008698[/C][C]-0.0674[/C][C]0.473255[/C][/ROW]
[ROW][C]40[/C][C]-0.033694[/C][C]-0.261[/C][C]0.397496[/C][/ROW]
[ROW][C]41[/C][C]-0.014272[/C][C]-0.1106[/C][C]0.456171[/C][/ROW]
[ROW][C]42[/C][C]0.052412[/C][C]0.406[/C][C]0.343101[/C][/ROW]
[ROW][C]43[/C][C]-0.09859[/C][C]-0.7637[/C][C]0.224028[/C][/ROW]
[ROW][C]44[/C][C]-0.09507[/C][C]-0.7364[/C][C]0.232176[/C][/ROW]
[ROW][C]45[/C][C]-0.004163[/C][C]-0.0322[/C][C]0.487192[/C][/ROW]
[ROW][C]46[/C][C]0.098184[/C][C]0.7605[/C][C]0.224959[/C][/ROW]
[ROW][C]47[/C][C]0.01408[/C][C]0.1091[/C][C]0.456759[/C][/ROW]
[ROW][C]48[/C][C]-0.098513[/C][C]-0.7631[/C][C]0.224203[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204303&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204303&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
10.0118710.0920.46352
20.0387030.29980.382687
3-0.110542-0.85630.197632
4-0.050551-0.39160.348382
5-0.092534-0.71680.238149
6-0.061508-0.47640.317745
70.0250320.19390.423457
80.0139560.10810.457137
9-0.030892-0.23930.405848
100.0561540.4350.332573
110.1597281.23720.110408
12-0.404385-3.13240.00134
13-0.085833-0.66490.254343
140.0852240.66010.255844
15-0.058001-0.44930.327428
16-0.078982-0.61180.271493
17-0.101249-0.78430.217984
18-0.014741-0.11420.454737
190.0186150.14420.442918
20-0.044979-0.34840.364376
210.0715690.55440.290692
220.2709462.09870.020028
230.1488741.15320.126707
24-0.218469-1.69230.047892
250.1068920.8280.20548
26-0.112728-0.87320.193021
270.095170.73720.231942
280.003770.02920.488399
290.0449510.34820.364458
30-0.028402-0.220.413309
31-0.050087-0.3880.349705
320.0364450.28230.389341
330.0220790.1710.432389
340.0927040.71810.237748
35-0.06715-0.52010.30244
36-0.203944-1.57970.059712
370.0081320.0630.47499
380.0403830.31280.377756
39-0.008698-0.06740.473255
40-0.033694-0.2610.397496
41-0.014272-0.11060.456171
420.0524120.4060.343101
43-0.09859-0.76370.224028
44-0.09507-0.73640.232176
45-0.004163-0.03220.487192
460.0981840.76050.224959
470.014080.10910.456759
48-0.098513-0.76310.224203



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