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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 18 Nov 2011 05:44:45 -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/Nov/18/t1321613134zbdbw42vyocercp.htm/, Retrieved Fri, 29 Mar 2024 01:41:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145422, Retrieved Fri, 29 Mar 2024 01:41:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact135
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Inschrijvingen ni...] [2011-11-18 09:57:43] [d700a6813b2ef07b7398fe84f8eae4b7]
-   PD  [(Partial) Autocorrelation Function] [Gemiddelde prijs ...] [2011-11-18 10:32:28] [d700a6813b2ef07b7398fe84f8eae4b7]
- R PD    [(Partial) Autocorrelation Function] [Gemiddelde prijs ...] [2011-11-18 10:37:11] [d700a6813b2ef07b7398fe84f8eae4b7]
-   P         [(Partial) Autocorrelation Function] [Gemiddelde prijs ...] [2011-11-18 10:44:45] [9b00bb73e1719a6b710100764835da33] [Current]
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Dataseries X:
10.93
10.92
10.89
10.94
10.98
10.99
11.02
11.04
11.05
11.05
11.02
10.91
11.01
11.02
11.03
11.04
11.06
11.08
11.06
11.06
11.09
11.07
11.06
11.08
11.08
11.08
11.11
11.09
11.08
11.05
11.07
11.06
11.06
11.07
11.02
11.01
11.04
11.02
11.03
11.17
11.19
11.15
11.13
11.06
11.01
11.03
10.99
10.94
11
11.06
11.06
11.05
11.04
11.15
11.2
11.16
11.3
11.23
11.25
11.25
11.12
11.14
11.17
11.25
11.27
11.34
11.39
11.44
11.46
11.49
11.51
11.48
11.49
11.52
11.56
11.58
11.58
11.58
11.6
11.62
11.62
11.64
11.67
11.66
11.72
11.82
11.9
12.04
12.08
12.15
12.19
12.22
12.23
12.25
12.26
12.27
12.34
12.38
12.42
12.43
12.48
12.5
12.5
12.49
12.46
12.45
12.45
12.38
12.42
12.37
12.35
12.35
12.36
12.32
12.32
12.34
12.35
12.34
12.31
12.24




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=145422&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=145422&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145422&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
10.1349891.47260.071755
20.1272251.38790.083886
30.2148982.34430.010361
4-0.043386-0.47330.318438
50.0211470.23070.408975
6-0.022826-0.2490.401895
7-0.055253-0.60270.273915
80.0231810.25290.4004
90.142491.55440.061375
100.0872710.9520.17151
110.0585860.63910.261993
120.034270.37380.354593
130.0944861.03070.152381
140.1523951.66240.049529
15-0.033335-0.36360.358385
160.0528110.57610.282818
170.085010.92730.177812
18-0.073791-0.8050.211223
19-0.030654-0.33440.369335
20-0.045647-0.49790.30972
21-0.131194-1.43120.077503
22-0.095421-1.04090.150011
230.0555260.60570.272926
24-0.001344-0.01470.494163
25-0.076345-0.83280.203306
260.037910.41360.339973
27-0.081583-0.890.18764
28-0.086905-0.9480.172521
29-0.105299-1.14870.126496
30-0.045863-0.50030.308891
310.0009360.01020.495937
32-0.061296-0.66870.252503
330.1445181.57650.058782
34-0.025392-0.2770.391131
35-0.011145-0.12160.451721
360.0981011.07020.143357
37-0.051156-0.5580.288929
38-0.127333-1.3890.083708
39-0.048283-0.52670.299688
40-0.113653-1.23980.108743
41-0.068078-0.74260.229582
42-0.049432-0.53920.295365
43-0.153109-1.67020.048752
44-0.062345-0.68010.248879
45-0.12632-1.3780.085396
46-0.010933-0.11930.452632
470.0485870.530.298542
48-0.041402-0.45160.326174

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.134989 & 1.4726 & 0.071755 \tabularnewline
2 & 0.127225 & 1.3879 & 0.083886 \tabularnewline
3 & 0.214898 & 2.3443 & 0.010361 \tabularnewline
4 & -0.043386 & -0.4733 & 0.318438 \tabularnewline
5 & 0.021147 & 0.2307 & 0.408975 \tabularnewline
6 & -0.022826 & -0.249 & 0.401895 \tabularnewline
7 & -0.055253 & -0.6027 & 0.273915 \tabularnewline
8 & 0.023181 & 0.2529 & 0.4004 \tabularnewline
9 & 0.14249 & 1.5544 & 0.061375 \tabularnewline
10 & 0.087271 & 0.952 & 0.17151 \tabularnewline
11 & 0.058586 & 0.6391 & 0.261993 \tabularnewline
12 & 0.03427 & 0.3738 & 0.354593 \tabularnewline
13 & 0.094486 & 1.0307 & 0.152381 \tabularnewline
14 & 0.152395 & 1.6624 & 0.049529 \tabularnewline
15 & -0.033335 & -0.3636 & 0.358385 \tabularnewline
16 & 0.052811 & 0.5761 & 0.282818 \tabularnewline
17 & 0.08501 & 0.9273 & 0.177812 \tabularnewline
18 & -0.073791 & -0.805 & 0.211223 \tabularnewline
19 & -0.030654 & -0.3344 & 0.369335 \tabularnewline
20 & -0.045647 & -0.4979 & 0.30972 \tabularnewline
21 & -0.131194 & -1.4312 & 0.077503 \tabularnewline
22 & -0.095421 & -1.0409 & 0.150011 \tabularnewline
23 & 0.055526 & 0.6057 & 0.272926 \tabularnewline
24 & -0.001344 & -0.0147 & 0.494163 \tabularnewline
25 & -0.076345 & -0.8328 & 0.203306 \tabularnewline
26 & 0.03791 & 0.4136 & 0.339973 \tabularnewline
27 & -0.081583 & -0.89 & 0.18764 \tabularnewline
28 & -0.086905 & -0.948 & 0.172521 \tabularnewline
29 & -0.105299 & -1.1487 & 0.126496 \tabularnewline
30 & -0.045863 & -0.5003 & 0.308891 \tabularnewline
31 & 0.000936 & 0.0102 & 0.495937 \tabularnewline
32 & -0.061296 & -0.6687 & 0.252503 \tabularnewline
33 & 0.144518 & 1.5765 & 0.058782 \tabularnewline
34 & -0.025392 & -0.277 & 0.391131 \tabularnewline
35 & -0.011145 & -0.1216 & 0.451721 \tabularnewline
36 & 0.098101 & 1.0702 & 0.143357 \tabularnewline
37 & -0.051156 & -0.558 & 0.288929 \tabularnewline
38 & -0.127333 & -1.389 & 0.083708 \tabularnewline
39 & -0.048283 & -0.5267 & 0.299688 \tabularnewline
40 & -0.113653 & -1.2398 & 0.108743 \tabularnewline
41 & -0.068078 & -0.7426 & 0.229582 \tabularnewline
42 & -0.049432 & -0.5392 & 0.295365 \tabularnewline
43 & -0.153109 & -1.6702 & 0.048752 \tabularnewline
44 & -0.062345 & -0.6801 & 0.248879 \tabularnewline
45 & -0.12632 & -1.378 & 0.085396 \tabularnewline
46 & -0.010933 & -0.1193 & 0.452632 \tabularnewline
47 & 0.048587 & 0.53 & 0.298542 \tabularnewline
48 & -0.041402 & -0.4516 & 0.326174 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145422&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]0.134989[/C][C]1.4726[/C][C]0.071755[/C][/ROW]
[ROW][C]2[/C][C]0.127225[/C][C]1.3879[/C][C]0.083886[/C][/ROW]
[ROW][C]3[/C][C]0.214898[/C][C]2.3443[/C][C]0.010361[/C][/ROW]
[ROW][C]4[/C][C]-0.043386[/C][C]-0.4733[/C][C]0.318438[/C][/ROW]
[ROW][C]5[/C][C]0.021147[/C][C]0.2307[/C][C]0.408975[/C][/ROW]
[ROW][C]6[/C][C]-0.022826[/C][C]-0.249[/C][C]0.401895[/C][/ROW]
[ROW][C]7[/C][C]-0.055253[/C][C]-0.6027[/C][C]0.273915[/C][/ROW]
[ROW][C]8[/C][C]0.023181[/C][C]0.2529[/C][C]0.4004[/C][/ROW]
[ROW][C]9[/C][C]0.14249[/C][C]1.5544[/C][C]0.061375[/C][/ROW]
[ROW][C]10[/C][C]0.087271[/C][C]0.952[/C][C]0.17151[/C][/ROW]
[ROW][C]11[/C][C]0.058586[/C][C]0.6391[/C][C]0.261993[/C][/ROW]
[ROW][C]12[/C][C]0.03427[/C][C]0.3738[/C][C]0.354593[/C][/ROW]
[ROW][C]13[/C][C]0.094486[/C][C]1.0307[/C][C]0.152381[/C][/ROW]
[ROW][C]14[/C][C]0.152395[/C][C]1.6624[/C][C]0.049529[/C][/ROW]
[ROW][C]15[/C][C]-0.033335[/C][C]-0.3636[/C][C]0.358385[/C][/ROW]
[ROW][C]16[/C][C]0.052811[/C][C]0.5761[/C][C]0.282818[/C][/ROW]
[ROW][C]17[/C][C]0.08501[/C][C]0.9273[/C][C]0.177812[/C][/ROW]
[ROW][C]18[/C][C]-0.073791[/C][C]-0.805[/C][C]0.211223[/C][/ROW]
[ROW][C]19[/C][C]-0.030654[/C][C]-0.3344[/C][C]0.369335[/C][/ROW]
[ROW][C]20[/C][C]-0.045647[/C][C]-0.4979[/C][C]0.30972[/C][/ROW]
[ROW][C]21[/C][C]-0.131194[/C][C]-1.4312[/C][C]0.077503[/C][/ROW]
[ROW][C]22[/C][C]-0.095421[/C][C]-1.0409[/C][C]0.150011[/C][/ROW]
[ROW][C]23[/C][C]0.055526[/C][C]0.6057[/C][C]0.272926[/C][/ROW]
[ROW][C]24[/C][C]-0.001344[/C][C]-0.0147[/C][C]0.494163[/C][/ROW]
[ROW][C]25[/C][C]-0.076345[/C][C]-0.8328[/C][C]0.203306[/C][/ROW]
[ROW][C]26[/C][C]0.03791[/C][C]0.4136[/C][C]0.339973[/C][/ROW]
[ROW][C]27[/C][C]-0.081583[/C][C]-0.89[/C][C]0.18764[/C][/ROW]
[ROW][C]28[/C][C]-0.086905[/C][C]-0.948[/C][C]0.172521[/C][/ROW]
[ROW][C]29[/C][C]-0.105299[/C][C]-1.1487[/C][C]0.126496[/C][/ROW]
[ROW][C]30[/C][C]-0.045863[/C][C]-0.5003[/C][C]0.308891[/C][/ROW]
[ROW][C]31[/C][C]0.000936[/C][C]0.0102[/C][C]0.495937[/C][/ROW]
[ROW][C]32[/C][C]-0.061296[/C][C]-0.6687[/C][C]0.252503[/C][/ROW]
[ROW][C]33[/C][C]0.144518[/C][C]1.5765[/C][C]0.058782[/C][/ROW]
[ROW][C]34[/C][C]-0.025392[/C][C]-0.277[/C][C]0.391131[/C][/ROW]
[ROW][C]35[/C][C]-0.011145[/C][C]-0.1216[/C][C]0.451721[/C][/ROW]
[ROW][C]36[/C][C]0.098101[/C][C]1.0702[/C][C]0.143357[/C][/ROW]
[ROW][C]37[/C][C]-0.051156[/C][C]-0.558[/C][C]0.288929[/C][/ROW]
[ROW][C]38[/C][C]-0.127333[/C][C]-1.389[/C][C]0.083708[/C][/ROW]
[ROW][C]39[/C][C]-0.048283[/C][C]-0.5267[/C][C]0.299688[/C][/ROW]
[ROW][C]40[/C][C]-0.113653[/C][C]-1.2398[/C][C]0.108743[/C][/ROW]
[ROW][C]41[/C][C]-0.068078[/C][C]-0.7426[/C][C]0.229582[/C][/ROW]
[ROW][C]42[/C][C]-0.049432[/C][C]-0.5392[/C][C]0.295365[/C][/ROW]
[ROW][C]43[/C][C]-0.153109[/C][C]-1.6702[/C][C]0.048752[/C][/ROW]
[ROW][C]44[/C][C]-0.062345[/C][C]-0.6801[/C][C]0.248879[/C][/ROW]
[ROW][C]45[/C][C]-0.12632[/C][C]-1.378[/C][C]0.085396[/C][/ROW]
[ROW][C]46[/C][C]-0.010933[/C][C]-0.1193[/C][C]0.452632[/C][/ROW]
[ROW][C]47[/C][C]0.048587[/C][C]0.53[/C][C]0.298542[/C][/ROW]
[ROW][C]48[/C][C]-0.041402[/C][C]-0.4516[/C][C]0.326174[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145422&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145422&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
10.1349891.47260.071755
20.1272251.38790.083886
30.2148982.34430.010361
4-0.043386-0.47330.318438
50.0211470.23070.408975
6-0.022826-0.2490.401895
7-0.055253-0.60270.273915
80.0231810.25290.4004
90.142491.55440.061375
100.0872710.9520.17151
110.0585860.63910.261993
120.034270.37380.354593
130.0944861.03070.152381
140.1523951.66240.049529
15-0.033335-0.36360.358385
160.0528110.57610.282818
170.085010.92730.177812
18-0.073791-0.8050.211223
19-0.030654-0.33440.369335
20-0.045647-0.49790.30972
21-0.131194-1.43120.077503
22-0.095421-1.04090.150011
230.0555260.60570.272926
24-0.001344-0.01470.494163
25-0.076345-0.83280.203306
260.037910.41360.339973
27-0.081583-0.890.18764
28-0.086905-0.9480.172521
29-0.105299-1.14870.126496
30-0.045863-0.50030.308891
310.0009360.01020.495937
32-0.061296-0.66870.252503
330.1445181.57650.058782
34-0.025392-0.2770.391131
35-0.011145-0.12160.451721
360.0981011.07020.143357
37-0.051156-0.5580.288929
38-0.127333-1.3890.083708
39-0.048283-0.52670.299688
40-0.113653-1.23980.108743
41-0.068078-0.74260.229582
42-0.049432-0.53920.295365
43-0.153109-1.67020.048752
44-0.062345-0.68010.248879
45-0.12632-1.3780.085396
46-0.010933-0.11930.452632
470.0485870.530.298542
48-0.041402-0.45160.326174







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1349891.47260.071755
20.1110261.21120.114119
30.1904182.07720.019967
4-0.108669-1.18540.119102
5-0.006061-0.06610.473698
6-0.053984-0.58890.278525
7-0.017377-0.18960.424988
80.0343120.37430.354423
90.1756981.91660.028841
100.0645590.70430.241323
11-0.006888-0.07510.470116
12-0.060449-0.65940.255451
130.0810620.88430.189165
140.1493961.62970.052903
15-0.061683-0.67290.251163
160.0192870.21040.416857
170.0493640.53850.295618
18-0.092288-1.00670.158051
19-0.084763-0.92470.178509
20-0.027707-0.30230.381494
21-0.062772-0.68480.247411
22-0.100104-1.0920.138519
230.0750510.81870.207294
240.0468040.51060.305299
25-0.109426-1.19370.117485
26-0.034948-0.38120.351852
27-0.096828-1.05630.146492
28-0.048451-0.52850.299055
29-0.07509-0.81910.207173
300.0672840.7340.232202
310.0901640.98360.163661
32-0.035232-0.38430.350708
330.1322241.44240.075908
34-0.038177-0.41650.338912
350.0326590.35630.361134
360.0810740.88440.189127
37-0.0114-0.12440.450618
38-0.096626-1.05410.146995
39-0.02335-0.25470.399691
40-0.109541-1.19490.117242
410.0213750.23320.408013
42-0.037562-0.40980.34136
43-0.142446-1.55390.061432
44-0.067854-0.74020.23032
45-0.134597-1.46830.072333
460.0335920.36640.357343
470.0261280.2850.388059
480.0248390.2710.393446

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.134989 & 1.4726 & 0.071755 \tabularnewline
2 & 0.111026 & 1.2112 & 0.114119 \tabularnewline
3 & 0.190418 & 2.0772 & 0.019967 \tabularnewline
4 & -0.108669 & -1.1854 & 0.119102 \tabularnewline
5 & -0.006061 & -0.0661 & 0.473698 \tabularnewline
6 & -0.053984 & -0.5889 & 0.278525 \tabularnewline
7 & -0.017377 & -0.1896 & 0.424988 \tabularnewline
8 & 0.034312 & 0.3743 & 0.354423 \tabularnewline
9 & 0.175698 & 1.9166 & 0.028841 \tabularnewline
10 & 0.064559 & 0.7043 & 0.241323 \tabularnewline
11 & -0.006888 & -0.0751 & 0.470116 \tabularnewline
12 & -0.060449 & -0.6594 & 0.255451 \tabularnewline
13 & 0.081062 & 0.8843 & 0.189165 \tabularnewline
14 & 0.149396 & 1.6297 & 0.052903 \tabularnewline
15 & -0.061683 & -0.6729 & 0.251163 \tabularnewline
16 & 0.019287 & 0.2104 & 0.416857 \tabularnewline
17 & 0.049364 & 0.5385 & 0.295618 \tabularnewline
18 & -0.092288 & -1.0067 & 0.158051 \tabularnewline
19 & -0.084763 & -0.9247 & 0.178509 \tabularnewline
20 & -0.027707 & -0.3023 & 0.381494 \tabularnewline
21 & -0.062772 & -0.6848 & 0.247411 \tabularnewline
22 & -0.100104 & -1.092 & 0.138519 \tabularnewline
23 & 0.075051 & 0.8187 & 0.207294 \tabularnewline
24 & 0.046804 & 0.5106 & 0.305299 \tabularnewline
25 & -0.109426 & -1.1937 & 0.117485 \tabularnewline
26 & -0.034948 & -0.3812 & 0.351852 \tabularnewline
27 & -0.096828 & -1.0563 & 0.146492 \tabularnewline
28 & -0.048451 & -0.5285 & 0.299055 \tabularnewline
29 & -0.07509 & -0.8191 & 0.207173 \tabularnewline
30 & 0.067284 & 0.734 & 0.232202 \tabularnewline
31 & 0.090164 & 0.9836 & 0.163661 \tabularnewline
32 & -0.035232 & -0.3843 & 0.350708 \tabularnewline
33 & 0.132224 & 1.4424 & 0.075908 \tabularnewline
34 & -0.038177 & -0.4165 & 0.338912 \tabularnewline
35 & 0.032659 & 0.3563 & 0.361134 \tabularnewline
36 & 0.081074 & 0.8844 & 0.189127 \tabularnewline
37 & -0.0114 & -0.1244 & 0.450618 \tabularnewline
38 & -0.096626 & -1.0541 & 0.146995 \tabularnewline
39 & -0.02335 & -0.2547 & 0.399691 \tabularnewline
40 & -0.109541 & -1.1949 & 0.117242 \tabularnewline
41 & 0.021375 & 0.2332 & 0.408013 \tabularnewline
42 & -0.037562 & -0.4098 & 0.34136 \tabularnewline
43 & -0.142446 & -1.5539 & 0.061432 \tabularnewline
44 & -0.067854 & -0.7402 & 0.23032 \tabularnewline
45 & -0.134597 & -1.4683 & 0.072333 \tabularnewline
46 & 0.033592 & 0.3664 & 0.357343 \tabularnewline
47 & 0.026128 & 0.285 & 0.388059 \tabularnewline
48 & 0.024839 & 0.271 & 0.393446 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145422&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]0.134989[/C][C]1.4726[/C][C]0.071755[/C][/ROW]
[ROW][C]2[/C][C]0.111026[/C][C]1.2112[/C][C]0.114119[/C][/ROW]
[ROW][C]3[/C][C]0.190418[/C][C]2.0772[/C][C]0.019967[/C][/ROW]
[ROW][C]4[/C][C]-0.108669[/C][C]-1.1854[/C][C]0.119102[/C][/ROW]
[ROW][C]5[/C][C]-0.006061[/C][C]-0.0661[/C][C]0.473698[/C][/ROW]
[ROW][C]6[/C][C]-0.053984[/C][C]-0.5889[/C][C]0.278525[/C][/ROW]
[ROW][C]7[/C][C]-0.017377[/C][C]-0.1896[/C][C]0.424988[/C][/ROW]
[ROW][C]8[/C][C]0.034312[/C][C]0.3743[/C][C]0.354423[/C][/ROW]
[ROW][C]9[/C][C]0.175698[/C][C]1.9166[/C][C]0.028841[/C][/ROW]
[ROW][C]10[/C][C]0.064559[/C][C]0.7043[/C][C]0.241323[/C][/ROW]
[ROW][C]11[/C][C]-0.006888[/C][C]-0.0751[/C][C]0.470116[/C][/ROW]
[ROW][C]12[/C][C]-0.060449[/C][C]-0.6594[/C][C]0.255451[/C][/ROW]
[ROW][C]13[/C][C]0.081062[/C][C]0.8843[/C][C]0.189165[/C][/ROW]
[ROW][C]14[/C][C]0.149396[/C][C]1.6297[/C][C]0.052903[/C][/ROW]
[ROW][C]15[/C][C]-0.061683[/C][C]-0.6729[/C][C]0.251163[/C][/ROW]
[ROW][C]16[/C][C]0.019287[/C][C]0.2104[/C][C]0.416857[/C][/ROW]
[ROW][C]17[/C][C]0.049364[/C][C]0.5385[/C][C]0.295618[/C][/ROW]
[ROW][C]18[/C][C]-0.092288[/C][C]-1.0067[/C][C]0.158051[/C][/ROW]
[ROW][C]19[/C][C]-0.084763[/C][C]-0.9247[/C][C]0.178509[/C][/ROW]
[ROW][C]20[/C][C]-0.027707[/C][C]-0.3023[/C][C]0.381494[/C][/ROW]
[ROW][C]21[/C][C]-0.062772[/C][C]-0.6848[/C][C]0.247411[/C][/ROW]
[ROW][C]22[/C][C]-0.100104[/C][C]-1.092[/C][C]0.138519[/C][/ROW]
[ROW][C]23[/C][C]0.075051[/C][C]0.8187[/C][C]0.207294[/C][/ROW]
[ROW][C]24[/C][C]0.046804[/C][C]0.5106[/C][C]0.305299[/C][/ROW]
[ROW][C]25[/C][C]-0.109426[/C][C]-1.1937[/C][C]0.117485[/C][/ROW]
[ROW][C]26[/C][C]-0.034948[/C][C]-0.3812[/C][C]0.351852[/C][/ROW]
[ROW][C]27[/C][C]-0.096828[/C][C]-1.0563[/C][C]0.146492[/C][/ROW]
[ROW][C]28[/C][C]-0.048451[/C][C]-0.5285[/C][C]0.299055[/C][/ROW]
[ROW][C]29[/C][C]-0.07509[/C][C]-0.8191[/C][C]0.207173[/C][/ROW]
[ROW][C]30[/C][C]0.067284[/C][C]0.734[/C][C]0.232202[/C][/ROW]
[ROW][C]31[/C][C]0.090164[/C][C]0.9836[/C][C]0.163661[/C][/ROW]
[ROW][C]32[/C][C]-0.035232[/C][C]-0.3843[/C][C]0.350708[/C][/ROW]
[ROW][C]33[/C][C]0.132224[/C][C]1.4424[/C][C]0.075908[/C][/ROW]
[ROW][C]34[/C][C]-0.038177[/C][C]-0.4165[/C][C]0.338912[/C][/ROW]
[ROW][C]35[/C][C]0.032659[/C][C]0.3563[/C][C]0.361134[/C][/ROW]
[ROW][C]36[/C][C]0.081074[/C][C]0.8844[/C][C]0.189127[/C][/ROW]
[ROW][C]37[/C][C]-0.0114[/C][C]-0.1244[/C][C]0.450618[/C][/ROW]
[ROW][C]38[/C][C]-0.096626[/C][C]-1.0541[/C][C]0.146995[/C][/ROW]
[ROW][C]39[/C][C]-0.02335[/C][C]-0.2547[/C][C]0.399691[/C][/ROW]
[ROW][C]40[/C][C]-0.109541[/C][C]-1.1949[/C][C]0.117242[/C][/ROW]
[ROW][C]41[/C][C]0.021375[/C][C]0.2332[/C][C]0.408013[/C][/ROW]
[ROW][C]42[/C][C]-0.037562[/C][C]-0.4098[/C][C]0.34136[/C][/ROW]
[ROW][C]43[/C][C]-0.142446[/C][C]-1.5539[/C][C]0.061432[/C][/ROW]
[ROW][C]44[/C][C]-0.067854[/C][C]-0.7402[/C][C]0.23032[/C][/ROW]
[ROW][C]45[/C][C]-0.134597[/C][C]-1.4683[/C][C]0.072333[/C][/ROW]
[ROW][C]46[/C][C]0.033592[/C][C]0.3664[/C][C]0.357343[/C][/ROW]
[ROW][C]47[/C][C]0.026128[/C][C]0.285[/C][C]0.388059[/C][/ROW]
[ROW][C]48[/C][C]0.024839[/C][C]0.271[/C][C]0.393446[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145422&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145422&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
10.1349891.47260.071755
20.1110261.21120.114119
30.1904182.07720.019967
4-0.108669-1.18540.119102
5-0.006061-0.06610.473698
6-0.053984-0.58890.278525
7-0.017377-0.18960.424988
80.0343120.37430.354423
90.1756981.91660.028841
100.0645590.70430.241323
11-0.006888-0.07510.470116
12-0.060449-0.65940.255451
130.0810620.88430.189165
140.1493961.62970.052903
15-0.061683-0.67290.251163
160.0192870.21040.416857
170.0493640.53850.295618
18-0.092288-1.00670.158051
19-0.084763-0.92470.178509
20-0.027707-0.30230.381494
21-0.062772-0.68480.247411
22-0.100104-1.0920.138519
230.0750510.81870.207294
240.0468040.51060.305299
25-0.109426-1.19370.117485
26-0.034948-0.38120.351852
27-0.096828-1.05630.146492
28-0.048451-0.52850.299055
29-0.07509-0.81910.207173
300.0672840.7340.232202
310.0901640.98360.163661
32-0.035232-0.38430.350708
330.1322241.44240.075908
34-0.038177-0.41650.338912
350.0326590.35630.361134
360.0810740.88440.189127
37-0.0114-0.12440.450618
38-0.096626-1.05410.146995
39-0.02335-0.25470.399691
40-0.109541-1.19490.117242
410.0213750.23320.408013
42-0.037562-0.40980.34136
43-0.142446-1.55390.061432
44-0.067854-0.74020.23032
45-0.134597-1.46830.072333
460.0335920.36640.357343
470.0261280.2850.388059
480.0248390.2710.393446



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; 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 (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')