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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 14 Dec 2007 03:26:18 -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/2007/Dec/14/t1197627092av5htdw0hp2cyx7.htm/, Retrieved Thu, 02 May 2024 15:29:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3805, Retrieved Thu, 02 May 2024 15:29:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordss0650550 s0650062
Estimated Impact235
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [Inducing Stationa...] [2007-11-29 14:28:06] [68a1fecd8f1c75119cd425050381cede]
- RMPD    [(Partial) Autocorrelation Function] [Time series] [2007-12-14 10:26:18] [ab924f39c1cc7a5dd22761038b10db61] [Current]
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Dataseries X:
263418000000
262752000000
266433000000
267722000000
266003000000
262971000000
265521000000
264676000000
270223000000
269508000000
268457000000
265814000000
266680000000
263018000000
269285000000
269829000000
270911000000
266844000000
271244000000
269907000000
271296000000
270157000000
271322000000
267179000000
264101000000
265518000000
269419000000
268714000000
272482000000
268351000000
268175000000
270674000000
272764000000
272599000000
270333000000
270846000000
270491000000
269160000000
274027000000
273784000000
276663000000
274525000000
271344000000
271115000000
270798000000
273911000000
273985000000
271917000000
273338000000
270601000000
273547000000
275363000000
281229000000
277793000000
279913000000
282500000000
280041000000
282166000000
290304000000
283519000000




Summary of compuational 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 compuational 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=3805&T=0

[TABLE]
[ROW][C]Summary of compuational 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=3805&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3805&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 compuational 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
015.91610
1-0.259491-1.53520.933133
2-0.322133-1.90580.96754
30.2628991.55530.064432
40.1935971.14530.12992
5-0.381466-2.25680.984815
60.1076690.6370.264141
70.110920.65620.25799
8-0.179294-1.06070.851958
9-0.114862-0.67950.749366
100.3177911.88010.034221
11-0.156262-0.92450.819212
12-0.324878-1.9220.968612
130.2701271.59810.059506
140.0668890.39570.347357
15-0.231605-1.37020.910324
160.0972410.57530.284389
170.0879690.52040.303019
18-0.15496-0.91680.817228
190.0765620.45290.326692
200.088930.52610.301063
21-0.049082-0.29040.613377
22-0.027415-0.16220.563954
230.1532620.90670.185381
24-0.093287-0.55190.707735
25-0.090137-0.53330.701387
26-0.006224-0.03680.514582
270.1076430.63680.264192
28-0.173876-1.02870.844653
290.0777060.45970.324282
300.0557560.32990.371737
310.0286490.16950.433194
32-0.086504-0.51180.693984
330.0755160.44680.3289
34-0.02765-0.16360.564498
35NANANA
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 5.9161 & 0 \tabularnewline
1 & -0.259491 & -1.5352 & 0.933133 \tabularnewline
2 & -0.322133 & -1.9058 & 0.96754 \tabularnewline
3 & 0.262899 & 1.5553 & 0.064432 \tabularnewline
4 & 0.193597 & 1.1453 & 0.12992 \tabularnewline
5 & -0.381466 & -2.2568 & 0.984815 \tabularnewline
6 & 0.107669 & 0.637 & 0.264141 \tabularnewline
7 & 0.11092 & 0.6562 & 0.25799 \tabularnewline
8 & -0.179294 & -1.0607 & 0.851958 \tabularnewline
9 & -0.114862 & -0.6795 & 0.749366 \tabularnewline
10 & 0.317791 & 1.8801 & 0.034221 \tabularnewline
11 & -0.156262 & -0.9245 & 0.819212 \tabularnewline
12 & -0.324878 & -1.922 & 0.968612 \tabularnewline
13 & 0.270127 & 1.5981 & 0.059506 \tabularnewline
14 & 0.066889 & 0.3957 & 0.347357 \tabularnewline
15 & -0.231605 & -1.3702 & 0.910324 \tabularnewline
16 & 0.097241 & 0.5753 & 0.284389 \tabularnewline
17 & 0.087969 & 0.5204 & 0.303019 \tabularnewline
18 & -0.15496 & -0.9168 & 0.817228 \tabularnewline
19 & 0.076562 & 0.4529 & 0.326692 \tabularnewline
20 & 0.08893 & 0.5261 & 0.301063 \tabularnewline
21 & -0.049082 & -0.2904 & 0.613377 \tabularnewline
22 & -0.027415 & -0.1622 & 0.563954 \tabularnewline
23 & 0.153262 & 0.9067 & 0.185381 \tabularnewline
24 & -0.093287 & -0.5519 & 0.707735 \tabularnewline
25 & -0.090137 & -0.5333 & 0.701387 \tabularnewline
26 & -0.006224 & -0.0368 & 0.514582 \tabularnewline
27 & 0.107643 & 0.6368 & 0.264192 \tabularnewline
28 & -0.173876 & -1.0287 & 0.844653 \tabularnewline
29 & 0.077706 & 0.4597 & 0.324282 \tabularnewline
30 & 0.055756 & 0.3299 & 0.371737 \tabularnewline
31 & 0.028649 & 0.1695 & 0.433194 \tabularnewline
32 & -0.086504 & -0.5118 & 0.693984 \tabularnewline
33 & 0.075516 & 0.4468 & 0.3289 \tabularnewline
34 & -0.02765 & -0.1636 & 0.564498 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
37 & NA & NA & NA \tabularnewline
38 & NA & NA & NA \tabularnewline
39 & NA & NA & NA \tabularnewline
40 & NA & NA & NA \tabularnewline
41 & NA & NA & NA \tabularnewline
42 & NA & NA & NA \tabularnewline
43 & NA & NA & NA \tabularnewline
44 & NA & NA & NA \tabularnewline
45 & NA & NA & NA \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3805&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]0[/C][C]1[/C][C]5.9161[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]-0.259491[/C][C]-1.5352[/C][C]0.933133[/C][/ROW]
[ROW][C]2[/C][C]-0.322133[/C][C]-1.9058[/C][C]0.96754[/C][/ROW]
[ROW][C]3[/C][C]0.262899[/C][C]1.5553[/C][C]0.064432[/C][/ROW]
[ROW][C]4[/C][C]0.193597[/C][C]1.1453[/C][C]0.12992[/C][/ROW]
[ROW][C]5[/C][C]-0.381466[/C][C]-2.2568[/C][C]0.984815[/C][/ROW]
[ROW][C]6[/C][C]0.107669[/C][C]0.637[/C][C]0.264141[/C][/ROW]
[ROW][C]7[/C][C]0.11092[/C][C]0.6562[/C][C]0.25799[/C][/ROW]
[ROW][C]8[/C][C]-0.179294[/C][C]-1.0607[/C][C]0.851958[/C][/ROW]
[ROW][C]9[/C][C]-0.114862[/C][C]-0.6795[/C][C]0.749366[/C][/ROW]
[ROW][C]10[/C][C]0.317791[/C][C]1.8801[/C][C]0.034221[/C][/ROW]
[ROW][C]11[/C][C]-0.156262[/C][C]-0.9245[/C][C]0.819212[/C][/ROW]
[ROW][C]12[/C][C]-0.324878[/C][C]-1.922[/C][C]0.968612[/C][/ROW]
[ROW][C]13[/C][C]0.270127[/C][C]1.5981[/C][C]0.059506[/C][/ROW]
[ROW][C]14[/C][C]0.066889[/C][C]0.3957[/C][C]0.347357[/C][/ROW]
[ROW][C]15[/C][C]-0.231605[/C][C]-1.3702[/C][C]0.910324[/C][/ROW]
[ROW][C]16[/C][C]0.097241[/C][C]0.5753[/C][C]0.284389[/C][/ROW]
[ROW][C]17[/C][C]0.087969[/C][C]0.5204[/C][C]0.303019[/C][/ROW]
[ROW][C]18[/C][C]-0.15496[/C][C]-0.9168[/C][C]0.817228[/C][/ROW]
[ROW][C]19[/C][C]0.076562[/C][C]0.4529[/C][C]0.326692[/C][/ROW]
[ROW][C]20[/C][C]0.08893[/C][C]0.5261[/C][C]0.301063[/C][/ROW]
[ROW][C]21[/C][C]-0.049082[/C][C]-0.2904[/C][C]0.613377[/C][/ROW]
[ROW][C]22[/C][C]-0.027415[/C][C]-0.1622[/C][C]0.563954[/C][/ROW]
[ROW][C]23[/C][C]0.153262[/C][C]0.9067[/C][C]0.185381[/C][/ROW]
[ROW][C]24[/C][C]-0.093287[/C][C]-0.5519[/C][C]0.707735[/C][/ROW]
[ROW][C]25[/C][C]-0.090137[/C][C]-0.5333[/C][C]0.701387[/C][/ROW]
[ROW][C]26[/C][C]-0.006224[/C][C]-0.0368[/C][C]0.514582[/C][/ROW]
[ROW][C]27[/C][C]0.107643[/C][C]0.6368[/C][C]0.264192[/C][/ROW]
[ROW][C]28[/C][C]-0.173876[/C][C]-1.0287[/C][C]0.844653[/C][/ROW]
[ROW][C]29[/C][C]0.077706[/C][C]0.4597[/C][C]0.324282[/C][/ROW]
[ROW][C]30[/C][C]0.055756[/C][C]0.3299[/C][C]0.371737[/C][/ROW]
[ROW][C]31[/C][C]0.028649[/C][C]0.1695[/C][C]0.433194[/C][/ROW]
[ROW][C]32[/C][C]-0.086504[/C][C]-0.5118[/C][C]0.693984[/C][/ROW]
[ROW][C]33[/C][C]0.075516[/C][C]0.4468[/C][C]0.3289[/C][/ROW]
[ROW][C]34[/C][C]-0.02765[/C][C]-0.1636[/C][C]0.564498[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]37[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]38[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]39[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]40[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]41[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]42[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]43[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]44[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]45[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3805&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3805&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
015.91610
1-0.259491-1.53520.933133
2-0.322133-1.90580.96754
30.2628991.55530.064432
40.1935971.14530.12992
5-0.381466-2.25680.984815
60.1076690.6370.264141
70.110920.65620.25799
8-0.179294-1.06070.851958
9-0.114862-0.67950.749366
100.3177911.88010.034221
11-0.156262-0.92450.819212
12-0.324878-1.9220.968612
130.2701271.59810.059506
140.0668890.39570.347357
15-0.231605-1.37020.910324
160.0972410.57530.284389
170.0879690.52040.303019
18-0.15496-0.91680.817228
190.0765620.45290.326692
200.088930.52610.301063
21-0.049082-0.29040.613377
22-0.027415-0.16220.563954
230.1532620.90670.185381
24-0.093287-0.55190.707735
25-0.090137-0.53330.701387
26-0.006224-0.03680.514582
270.1076430.63680.264192
28-0.173876-1.02870.844653
290.0777060.45970.324282
300.0557560.32990.371737
310.0286490.16950.433194
32-0.086504-0.51180.693984
330.0755160.44680.3289
34-0.02765-0.16360.564498
35NANANA
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
0-0.259491-1.53520.933133
1-0.417587-2.47050.990745
20.0468060.27690.391739
30.2190961.29620.101697
4-0.182294-1.07850.855899
50.0383850.22710.410837
6-0.097662-0.57780.716443
7-0.121059-0.71620.760689
8-0.146257-0.86530.803608
90.1399670.82810.206625
10-0.038118-0.22550.588553
11-0.306553-1.81360.960838
12-0.032558-0.19260.575813
13-0.133541-0.790.782587
140.0254240.15040.440653
150.050860.30090.382639
16-0.137258-0.8120.788868
17-0.102062-0.60380.725068
18-0.018929-0.1120.544263
19-0.065242-0.3860.649075
200.0556430.32920.371988
210.106190.62820.266966
220.0251310.14870.441332
23-0.162679-0.96240.82878
24-0.10034-0.59360.721708
25-0.248313-1.4690.924623
260.0482560.28550.388478
27-0.057349-0.33930.631786
28-0.028351-0.16770.566117
29-0.020556-0.12160.548049
300.0698630.41330.340948
31-0.046554-0.27540.607692
32-0.035694-0.21120.583011
330.0233060.13790.445562
34NANANA
35NANANA
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & -0.259491 & -1.5352 & 0.933133 \tabularnewline
1 & -0.417587 & -2.4705 & 0.990745 \tabularnewline
2 & 0.046806 & 0.2769 & 0.391739 \tabularnewline
3 & 0.219096 & 1.2962 & 0.101697 \tabularnewline
4 & -0.182294 & -1.0785 & 0.855899 \tabularnewline
5 & 0.038385 & 0.2271 & 0.410837 \tabularnewline
6 & -0.097662 & -0.5778 & 0.716443 \tabularnewline
7 & -0.121059 & -0.7162 & 0.760689 \tabularnewline
8 & -0.146257 & -0.8653 & 0.803608 \tabularnewline
9 & 0.139967 & 0.8281 & 0.206625 \tabularnewline
10 & -0.038118 & -0.2255 & 0.588553 \tabularnewline
11 & -0.306553 & -1.8136 & 0.960838 \tabularnewline
12 & -0.032558 & -0.1926 & 0.575813 \tabularnewline
13 & -0.133541 & -0.79 & 0.782587 \tabularnewline
14 & 0.025424 & 0.1504 & 0.440653 \tabularnewline
15 & 0.05086 & 0.3009 & 0.382639 \tabularnewline
16 & -0.137258 & -0.812 & 0.788868 \tabularnewline
17 & -0.102062 & -0.6038 & 0.725068 \tabularnewline
18 & -0.018929 & -0.112 & 0.544263 \tabularnewline
19 & -0.065242 & -0.386 & 0.649075 \tabularnewline
20 & 0.055643 & 0.3292 & 0.371988 \tabularnewline
21 & 0.10619 & 0.6282 & 0.266966 \tabularnewline
22 & 0.025131 & 0.1487 & 0.441332 \tabularnewline
23 & -0.162679 & -0.9624 & 0.82878 \tabularnewline
24 & -0.10034 & -0.5936 & 0.721708 \tabularnewline
25 & -0.248313 & -1.469 & 0.924623 \tabularnewline
26 & 0.048256 & 0.2855 & 0.388478 \tabularnewline
27 & -0.057349 & -0.3393 & 0.631786 \tabularnewline
28 & -0.028351 & -0.1677 & 0.566117 \tabularnewline
29 & -0.020556 & -0.1216 & 0.548049 \tabularnewline
30 & 0.069863 & 0.4133 & 0.340948 \tabularnewline
31 & -0.046554 & -0.2754 & 0.607692 \tabularnewline
32 & -0.035694 & -0.2112 & 0.583011 \tabularnewline
33 & 0.023306 & 0.1379 & 0.445562 \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
37 & NA & NA & NA \tabularnewline
38 & NA & NA & NA \tabularnewline
39 & NA & NA & NA \tabularnewline
40 & NA & NA & NA \tabularnewline
41 & NA & NA & NA \tabularnewline
42 & NA & NA & NA \tabularnewline
43 & NA & NA & NA \tabularnewline
44 & NA & NA & NA \tabularnewline
45 & NA & NA & NA \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3805&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]0[/C][C]-0.259491[/C][C]-1.5352[/C][C]0.933133[/C][/ROW]
[ROW][C]1[/C][C]-0.417587[/C][C]-2.4705[/C][C]0.990745[/C][/ROW]
[ROW][C]2[/C][C]0.046806[/C][C]0.2769[/C][C]0.391739[/C][/ROW]
[ROW][C]3[/C][C]0.219096[/C][C]1.2962[/C][C]0.101697[/C][/ROW]
[ROW][C]4[/C][C]-0.182294[/C][C]-1.0785[/C][C]0.855899[/C][/ROW]
[ROW][C]5[/C][C]0.038385[/C][C]0.2271[/C][C]0.410837[/C][/ROW]
[ROW][C]6[/C][C]-0.097662[/C][C]-0.5778[/C][C]0.716443[/C][/ROW]
[ROW][C]7[/C][C]-0.121059[/C][C]-0.7162[/C][C]0.760689[/C][/ROW]
[ROW][C]8[/C][C]-0.146257[/C][C]-0.8653[/C][C]0.803608[/C][/ROW]
[ROW][C]9[/C][C]0.139967[/C][C]0.8281[/C][C]0.206625[/C][/ROW]
[ROW][C]10[/C][C]-0.038118[/C][C]-0.2255[/C][C]0.588553[/C][/ROW]
[ROW][C]11[/C][C]-0.306553[/C][C]-1.8136[/C][C]0.960838[/C][/ROW]
[ROW][C]12[/C][C]-0.032558[/C][C]-0.1926[/C][C]0.575813[/C][/ROW]
[ROW][C]13[/C][C]-0.133541[/C][C]-0.79[/C][C]0.782587[/C][/ROW]
[ROW][C]14[/C][C]0.025424[/C][C]0.1504[/C][C]0.440653[/C][/ROW]
[ROW][C]15[/C][C]0.05086[/C][C]0.3009[/C][C]0.382639[/C][/ROW]
[ROW][C]16[/C][C]-0.137258[/C][C]-0.812[/C][C]0.788868[/C][/ROW]
[ROW][C]17[/C][C]-0.102062[/C][C]-0.6038[/C][C]0.725068[/C][/ROW]
[ROW][C]18[/C][C]-0.018929[/C][C]-0.112[/C][C]0.544263[/C][/ROW]
[ROW][C]19[/C][C]-0.065242[/C][C]-0.386[/C][C]0.649075[/C][/ROW]
[ROW][C]20[/C][C]0.055643[/C][C]0.3292[/C][C]0.371988[/C][/ROW]
[ROW][C]21[/C][C]0.10619[/C][C]0.6282[/C][C]0.266966[/C][/ROW]
[ROW][C]22[/C][C]0.025131[/C][C]0.1487[/C][C]0.441332[/C][/ROW]
[ROW][C]23[/C][C]-0.162679[/C][C]-0.9624[/C][C]0.82878[/C][/ROW]
[ROW][C]24[/C][C]-0.10034[/C][C]-0.5936[/C][C]0.721708[/C][/ROW]
[ROW][C]25[/C][C]-0.248313[/C][C]-1.469[/C][C]0.924623[/C][/ROW]
[ROW][C]26[/C][C]0.048256[/C][C]0.2855[/C][C]0.388478[/C][/ROW]
[ROW][C]27[/C][C]-0.057349[/C][C]-0.3393[/C][C]0.631786[/C][/ROW]
[ROW][C]28[/C][C]-0.028351[/C][C]-0.1677[/C][C]0.566117[/C][/ROW]
[ROW][C]29[/C][C]-0.020556[/C][C]-0.1216[/C][C]0.548049[/C][/ROW]
[ROW][C]30[/C][C]0.069863[/C][C]0.4133[/C][C]0.340948[/C][/ROW]
[ROW][C]31[/C][C]-0.046554[/C][C]-0.2754[/C][C]0.607692[/C][/ROW]
[ROW][C]32[/C][C]-0.035694[/C][C]-0.2112[/C][C]0.583011[/C][/ROW]
[ROW][C]33[/C][C]0.023306[/C][C]0.1379[/C][C]0.445562[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]37[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]38[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]39[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]40[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]41[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]42[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]43[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]44[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]45[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3805&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3805&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
0-0.259491-1.53520.933133
1-0.417587-2.47050.990745
20.0468060.27690.391739
30.2190961.29620.101697
4-0.182294-1.07850.855899
50.0383850.22710.410837
6-0.097662-0.57780.716443
7-0.121059-0.71620.760689
8-0.146257-0.86530.803608
90.1399670.82810.206625
10-0.038118-0.22550.588553
11-0.306553-1.81360.960838
12-0.032558-0.19260.575813
13-0.133541-0.790.782587
140.0254240.15040.440653
150.050860.30090.382639
16-0.137258-0.8120.788868
17-0.102062-0.60380.725068
18-0.018929-0.1120.544263
19-0.065242-0.3860.649075
200.0556430.32920.371988
210.106190.62820.266966
220.0251310.14870.441332
23-0.162679-0.96240.82878
24-0.10034-0.59360.721708
25-0.248313-1.4690.924623
260.0482560.28550.388478
27-0.057349-0.33930.631786
28-0.028351-0.16770.566117
29-0.020556-0.12160.548049
300.0698630.41330.340948
31-0.046554-0.27540.607692
32-0.035694-0.21120.583011
330.0233060.13790.445562
34NANANA
35NANANA
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')