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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, 03 May 2010 15:19:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/03/t12729001331e9381145tyu97s.htm/, Retrieved Thu, 18 Apr 2024 13:56:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75228, Retrieved Thu, 18 Apr 2024 13:56:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelatie - ...] [2010-05-03 15:19:42] [2aa5bad7942f7e33426bcac9d4e6ffec] [Current]
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Dataseries X:
3592,21
5955,74
4652,25
4211,65
4787,85
3599,73
4174,27
5106,33
5325,75
6604,61
5711,90
6919,30
7048,76
8655,98
6658,53
7247,03
8779,57
6602,49
9832,48
9369,49
8582,76
8206,94
6515,83
8618,10
8505,39
9881,64
9375,29
15642,50
12232,73
6288,93
12473,94
11142,82
10236,32
10581,51
8763,71
10819,04
11636,25
14650,13
10671,38
17468,63
13873,19
13077,58
16866,81
14186,64
19919,87
17681,78
9984,28
17423,09
13514,45
12334,57
12274,56
11752,23
13054,00
12460,98
8626,68
13722,62
12066,22
6798,83
6593,82
6606,19
6315,28
7232,95
6747,44
7803,61
6700,31
5369,53
8081,19
10718,39
9447,21
6815,10
5497,80
6805,31




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75228&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75228&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75228&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.6965545.91050
20.6556065.5630
30.6862595.82310
40.5612764.76265e-06
50.5910355.01512e-06
60.4780064.0566.2e-05
70.4084363.46570.000448
80.4225233.58520.000305
90.3078922.61260.005466
100.2221031.88460.03176
110.2488072.11120.019114
120.2358882.00160.02455
130.0709030.60160.274655
140.0777260.65950.25583
15-0.028068-0.23820.406214
16-0.034759-0.29490.384444
17-0.018256-0.15490.438665
18-0.144582-1.22680.111944
19-0.136668-1.15970.125007
20-0.157899-1.33980.092258
21-0.216689-1.83870.035044
22-0.237008-2.01110.024031
23-0.238089-2.02030.023539
24-0.216453-1.83670.035194
25-0.252484-2.14240.017772
26-0.270379-2.29420.012348
27-0.314006-2.66440.004756
28-0.23038-1.95480.027242
29-0.225481-1.91330.029845
30-0.312731-2.65360.004897
31-0.295523-2.50760.007206
32-0.308801-2.62030.005355
33-0.333163-2.8270.00304
34-0.332509-2.82140.003087
35-0.321828-2.73080.00397
36-0.303332-2.57390.006058
37-0.332448-2.82090.003092
38-0.337375-2.86270.002749
39-0.343274-2.91280.002384
40-0.273911-2.32420.01147
41-0.267716-2.27160.013049
42-0.2728-2.31480.01174
43-0.229294-1.94560.027802
44-0.217816-1.84820.034338
45-0.168173-1.4270.078952
46-0.106296-0.9020.185044
47-0.103332-0.87680.191757
48-0.046409-0.39380.347449

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.696554 & 5.9105 & 0 \tabularnewline
2 & 0.655606 & 5.563 & 0 \tabularnewline
3 & 0.686259 & 5.8231 & 0 \tabularnewline
4 & 0.561276 & 4.7626 & 5e-06 \tabularnewline
5 & 0.591035 & 5.0151 & 2e-06 \tabularnewline
6 & 0.478006 & 4.056 & 6.2e-05 \tabularnewline
7 & 0.408436 & 3.4657 & 0.000448 \tabularnewline
8 & 0.422523 & 3.5852 & 0.000305 \tabularnewline
9 & 0.307892 & 2.6126 & 0.005466 \tabularnewline
10 & 0.222103 & 1.8846 & 0.03176 \tabularnewline
11 & 0.248807 & 2.1112 & 0.019114 \tabularnewline
12 & 0.235888 & 2.0016 & 0.02455 \tabularnewline
13 & 0.070903 & 0.6016 & 0.274655 \tabularnewline
14 & 0.077726 & 0.6595 & 0.25583 \tabularnewline
15 & -0.028068 & -0.2382 & 0.406214 \tabularnewline
16 & -0.034759 & -0.2949 & 0.384444 \tabularnewline
17 & -0.018256 & -0.1549 & 0.438665 \tabularnewline
18 & -0.144582 & -1.2268 & 0.111944 \tabularnewline
19 & -0.136668 & -1.1597 & 0.125007 \tabularnewline
20 & -0.157899 & -1.3398 & 0.092258 \tabularnewline
21 & -0.216689 & -1.8387 & 0.035044 \tabularnewline
22 & -0.237008 & -2.0111 & 0.024031 \tabularnewline
23 & -0.238089 & -2.0203 & 0.023539 \tabularnewline
24 & -0.216453 & -1.8367 & 0.035194 \tabularnewline
25 & -0.252484 & -2.1424 & 0.017772 \tabularnewline
26 & -0.270379 & -2.2942 & 0.012348 \tabularnewline
27 & -0.314006 & -2.6644 & 0.004756 \tabularnewline
28 & -0.23038 & -1.9548 & 0.027242 \tabularnewline
29 & -0.225481 & -1.9133 & 0.029845 \tabularnewline
30 & -0.312731 & -2.6536 & 0.004897 \tabularnewline
31 & -0.295523 & -2.5076 & 0.007206 \tabularnewline
32 & -0.308801 & -2.6203 & 0.005355 \tabularnewline
33 & -0.333163 & -2.827 & 0.00304 \tabularnewline
34 & -0.332509 & -2.8214 & 0.003087 \tabularnewline
35 & -0.321828 & -2.7308 & 0.00397 \tabularnewline
36 & -0.303332 & -2.5739 & 0.006058 \tabularnewline
37 & -0.332448 & -2.8209 & 0.003092 \tabularnewline
38 & -0.337375 & -2.8627 & 0.002749 \tabularnewline
39 & -0.343274 & -2.9128 & 0.002384 \tabularnewline
40 & -0.273911 & -2.3242 & 0.01147 \tabularnewline
41 & -0.267716 & -2.2716 & 0.013049 \tabularnewline
42 & -0.2728 & -2.3148 & 0.01174 \tabularnewline
43 & -0.229294 & -1.9456 & 0.027802 \tabularnewline
44 & -0.217816 & -1.8482 & 0.034338 \tabularnewline
45 & -0.168173 & -1.427 & 0.078952 \tabularnewline
46 & -0.106296 & -0.902 & 0.185044 \tabularnewline
47 & -0.103332 & -0.8768 & 0.191757 \tabularnewline
48 & -0.046409 & -0.3938 & 0.347449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75228&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]0.696554[/C][C]5.9105[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.655606[/C][C]5.563[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.686259[/C][C]5.8231[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.561276[/C][C]4.7626[/C][C]5e-06[/C][/ROW]
[ROW][C]5[/C][C]0.591035[/C][C]5.0151[/C][C]2e-06[/C][/ROW]
[ROW][C]6[/C][C]0.478006[/C][C]4.056[/C][C]6.2e-05[/C][/ROW]
[ROW][C]7[/C][C]0.408436[/C][C]3.4657[/C][C]0.000448[/C][/ROW]
[ROW][C]8[/C][C]0.422523[/C][C]3.5852[/C][C]0.000305[/C][/ROW]
[ROW][C]9[/C][C]0.307892[/C][C]2.6126[/C][C]0.005466[/C][/ROW]
[ROW][C]10[/C][C]0.222103[/C][C]1.8846[/C][C]0.03176[/C][/ROW]
[ROW][C]11[/C][C]0.248807[/C][C]2.1112[/C][C]0.019114[/C][/ROW]
[ROW][C]12[/C][C]0.235888[/C][C]2.0016[/C][C]0.02455[/C][/ROW]
[ROW][C]13[/C][C]0.070903[/C][C]0.6016[/C][C]0.274655[/C][/ROW]
[ROW][C]14[/C][C]0.077726[/C][C]0.6595[/C][C]0.25583[/C][/ROW]
[ROW][C]15[/C][C]-0.028068[/C][C]-0.2382[/C][C]0.406214[/C][/ROW]
[ROW][C]16[/C][C]-0.034759[/C][C]-0.2949[/C][C]0.384444[/C][/ROW]
[ROW][C]17[/C][C]-0.018256[/C][C]-0.1549[/C][C]0.438665[/C][/ROW]
[ROW][C]18[/C][C]-0.144582[/C][C]-1.2268[/C][C]0.111944[/C][/ROW]
[ROW][C]19[/C][C]-0.136668[/C][C]-1.1597[/C][C]0.125007[/C][/ROW]
[ROW][C]20[/C][C]-0.157899[/C][C]-1.3398[/C][C]0.092258[/C][/ROW]
[ROW][C]21[/C][C]-0.216689[/C][C]-1.8387[/C][C]0.035044[/C][/ROW]
[ROW][C]22[/C][C]-0.237008[/C][C]-2.0111[/C][C]0.024031[/C][/ROW]
[ROW][C]23[/C][C]-0.238089[/C][C]-2.0203[/C][C]0.023539[/C][/ROW]
[ROW][C]24[/C][C]-0.216453[/C][C]-1.8367[/C][C]0.035194[/C][/ROW]
[ROW][C]25[/C][C]-0.252484[/C][C]-2.1424[/C][C]0.017772[/C][/ROW]
[ROW][C]26[/C][C]-0.270379[/C][C]-2.2942[/C][C]0.012348[/C][/ROW]
[ROW][C]27[/C][C]-0.314006[/C][C]-2.6644[/C][C]0.004756[/C][/ROW]
[ROW][C]28[/C][C]-0.23038[/C][C]-1.9548[/C][C]0.027242[/C][/ROW]
[ROW][C]29[/C][C]-0.225481[/C][C]-1.9133[/C][C]0.029845[/C][/ROW]
[ROW][C]30[/C][C]-0.312731[/C][C]-2.6536[/C][C]0.004897[/C][/ROW]
[ROW][C]31[/C][C]-0.295523[/C][C]-2.5076[/C][C]0.007206[/C][/ROW]
[ROW][C]32[/C][C]-0.308801[/C][C]-2.6203[/C][C]0.005355[/C][/ROW]
[ROW][C]33[/C][C]-0.333163[/C][C]-2.827[/C][C]0.00304[/C][/ROW]
[ROW][C]34[/C][C]-0.332509[/C][C]-2.8214[/C][C]0.003087[/C][/ROW]
[ROW][C]35[/C][C]-0.321828[/C][C]-2.7308[/C][C]0.00397[/C][/ROW]
[ROW][C]36[/C][C]-0.303332[/C][C]-2.5739[/C][C]0.006058[/C][/ROW]
[ROW][C]37[/C][C]-0.332448[/C][C]-2.8209[/C][C]0.003092[/C][/ROW]
[ROW][C]38[/C][C]-0.337375[/C][C]-2.8627[/C][C]0.002749[/C][/ROW]
[ROW][C]39[/C][C]-0.343274[/C][C]-2.9128[/C][C]0.002384[/C][/ROW]
[ROW][C]40[/C][C]-0.273911[/C][C]-2.3242[/C][C]0.01147[/C][/ROW]
[ROW][C]41[/C][C]-0.267716[/C][C]-2.2716[/C][C]0.013049[/C][/ROW]
[ROW][C]42[/C][C]-0.2728[/C][C]-2.3148[/C][C]0.01174[/C][/ROW]
[ROW][C]43[/C][C]-0.229294[/C][C]-1.9456[/C][C]0.027802[/C][/ROW]
[ROW][C]44[/C][C]-0.217816[/C][C]-1.8482[/C][C]0.034338[/C][/ROW]
[ROW][C]45[/C][C]-0.168173[/C][C]-1.427[/C][C]0.078952[/C][/ROW]
[ROW][C]46[/C][C]-0.106296[/C][C]-0.902[/C][C]0.185044[/C][/ROW]
[ROW][C]47[/C][C]-0.103332[/C][C]-0.8768[/C][C]0.191757[/C][/ROW]
[ROW][C]48[/C][C]-0.046409[/C][C]-0.3938[/C][C]0.347449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75228&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75228&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
10.6965545.91050
20.6556065.5630
30.6862595.82310
40.5612764.76265e-06
50.5910355.01512e-06
60.4780064.0566.2e-05
70.4084363.46570.000448
80.4225233.58520.000305
90.3078922.61260.005466
100.2221031.88460.03176
110.2488072.11120.019114
120.2358882.00160.02455
130.0709030.60160.274655
140.0777260.65950.25583
15-0.028068-0.23820.406214
16-0.034759-0.29490.384444
17-0.018256-0.15490.438665
18-0.144582-1.22680.111944
19-0.136668-1.15970.125007
20-0.157899-1.33980.092258
21-0.216689-1.83870.035044
22-0.237008-2.01110.024031
23-0.238089-2.02030.023539
24-0.216453-1.83670.035194
25-0.252484-2.14240.017772
26-0.270379-2.29420.012348
27-0.314006-2.66440.004756
28-0.23038-1.95480.027242
29-0.225481-1.91330.029845
30-0.312731-2.65360.004897
31-0.295523-2.50760.007206
32-0.308801-2.62030.005355
33-0.333163-2.8270.00304
34-0.332509-2.82140.003087
35-0.321828-2.73080.00397
36-0.303332-2.57390.006058
37-0.332448-2.82090.003092
38-0.337375-2.86270.002749
39-0.343274-2.91280.002384
40-0.273911-2.32420.01147
41-0.267716-2.27160.013049
42-0.2728-2.31480.01174
43-0.229294-1.94560.027802
44-0.217816-1.84820.034338
45-0.168173-1.4270.078952
46-0.106296-0.9020.185044
47-0.103332-0.87680.191757
48-0.046409-0.39380.347449







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6965545.91050
20.3310292.80890.003198
30.3276272.780.003465
4-0.071414-0.6060.273222
50.1579461.34020.092194
6-0.189313-1.60640.056284
7-0.057032-0.48390.314951
80.0092730.07870.46875
9-0.083809-0.71110.239645
10-0.179345-1.52180.06622
110.1204121.02170.155165
120.1595131.35350.090064
13-0.32568-2.76350.003628
140.0265520.22530.41119
15-0.214963-1.8240.036149
160.1225251.03970.150989
17-0.014407-0.12220.451521
180.0596470.50610.307158
19-0.144592-1.22690.111928
200.0049640.04210.483258
210.0281830.23910.405839
22-0.13165-1.11710.133836
230.0626280.53140.298384
240.0407060.34540.3654
250.0321580.27290.392866
26-0.123943-1.05170.14823
270.0125540.10650.457731
280.0363710.30860.379252
290.0116640.0990.460718
30-0.154324-1.30950.097268
31-0.139734-1.18570.119822
32-0.032861-0.27880.390586
33-0.108088-0.91720.181061
340.0392820.33330.36993
350.0278790.23660.406834
36-0.012306-0.10440.458563
37-0.147426-1.25090.107502
380.0762380.64690.259876
39-0.046317-0.3930.347735
40-0.009291-0.07880.468689
410.0320860.27230.3931
420.0741550.62920.265597
430.003810.03230.487149
440.0311560.26440.396127
450.0807460.68520.247723
460.0345930.29350.384981
47-0.051617-0.4380.331354
480.0154110.13080.448161

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.696554 & 5.9105 & 0 \tabularnewline
2 & 0.331029 & 2.8089 & 0.003198 \tabularnewline
3 & 0.327627 & 2.78 & 0.003465 \tabularnewline
4 & -0.071414 & -0.606 & 0.273222 \tabularnewline
5 & 0.157946 & 1.3402 & 0.092194 \tabularnewline
6 & -0.189313 & -1.6064 & 0.056284 \tabularnewline
7 & -0.057032 & -0.4839 & 0.314951 \tabularnewline
8 & 0.009273 & 0.0787 & 0.46875 \tabularnewline
9 & -0.083809 & -0.7111 & 0.239645 \tabularnewline
10 & -0.179345 & -1.5218 & 0.06622 \tabularnewline
11 & 0.120412 & 1.0217 & 0.155165 \tabularnewline
12 & 0.159513 & 1.3535 & 0.090064 \tabularnewline
13 & -0.32568 & -2.7635 & 0.003628 \tabularnewline
14 & 0.026552 & 0.2253 & 0.41119 \tabularnewline
15 & -0.214963 & -1.824 & 0.036149 \tabularnewline
16 & 0.122525 & 1.0397 & 0.150989 \tabularnewline
17 & -0.014407 & -0.1222 & 0.451521 \tabularnewline
18 & 0.059647 & 0.5061 & 0.307158 \tabularnewline
19 & -0.144592 & -1.2269 & 0.111928 \tabularnewline
20 & 0.004964 & 0.0421 & 0.483258 \tabularnewline
21 & 0.028183 & 0.2391 & 0.405839 \tabularnewline
22 & -0.13165 & -1.1171 & 0.133836 \tabularnewline
23 & 0.062628 & 0.5314 & 0.298384 \tabularnewline
24 & 0.040706 & 0.3454 & 0.3654 \tabularnewline
25 & 0.032158 & 0.2729 & 0.392866 \tabularnewline
26 & -0.123943 & -1.0517 & 0.14823 \tabularnewline
27 & 0.012554 & 0.1065 & 0.457731 \tabularnewline
28 & 0.036371 & 0.3086 & 0.379252 \tabularnewline
29 & 0.011664 & 0.099 & 0.460718 \tabularnewline
30 & -0.154324 & -1.3095 & 0.097268 \tabularnewline
31 & -0.139734 & -1.1857 & 0.119822 \tabularnewline
32 & -0.032861 & -0.2788 & 0.390586 \tabularnewline
33 & -0.108088 & -0.9172 & 0.181061 \tabularnewline
34 & 0.039282 & 0.3333 & 0.36993 \tabularnewline
35 & 0.027879 & 0.2366 & 0.406834 \tabularnewline
36 & -0.012306 & -0.1044 & 0.458563 \tabularnewline
37 & -0.147426 & -1.2509 & 0.107502 \tabularnewline
38 & 0.076238 & 0.6469 & 0.259876 \tabularnewline
39 & -0.046317 & -0.393 & 0.347735 \tabularnewline
40 & -0.009291 & -0.0788 & 0.468689 \tabularnewline
41 & 0.032086 & 0.2723 & 0.3931 \tabularnewline
42 & 0.074155 & 0.6292 & 0.265597 \tabularnewline
43 & 0.00381 & 0.0323 & 0.487149 \tabularnewline
44 & 0.031156 & 0.2644 & 0.396127 \tabularnewline
45 & 0.080746 & 0.6852 & 0.247723 \tabularnewline
46 & 0.034593 & 0.2935 & 0.384981 \tabularnewline
47 & -0.051617 & -0.438 & 0.331354 \tabularnewline
48 & 0.015411 & 0.1308 & 0.448161 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75228&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]0.696554[/C][C]5.9105[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.331029[/C][C]2.8089[/C][C]0.003198[/C][/ROW]
[ROW][C]3[/C][C]0.327627[/C][C]2.78[/C][C]0.003465[/C][/ROW]
[ROW][C]4[/C][C]-0.071414[/C][C]-0.606[/C][C]0.273222[/C][/ROW]
[ROW][C]5[/C][C]0.157946[/C][C]1.3402[/C][C]0.092194[/C][/ROW]
[ROW][C]6[/C][C]-0.189313[/C][C]-1.6064[/C][C]0.056284[/C][/ROW]
[ROW][C]7[/C][C]-0.057032[/C][C]-0.4839[/C][C]0.314951[/C][/ROW]
[ROW][C]8[/C][C]0.009273[/C][C]0.0787[/C][C]0.46875[/C][/ROW]
[ROW][C]9[/C][C]-0.083809[/C][C]-0.7111[/C][C]0.239645[/C][/ROW]
[ROW][C]10[/C][C]-0.179345[/C][C]-1.5218[/C][C]0.06622[/C][/ROW]
[ROW][C]11[/C][C]0.120412[/C][C]1.0217[/C][C]0.155165[/C][/ROW]
[ROW][C]12[/C][C]0.159513[/C][C]1.3535[/C][C]0.090064[/C][/ROW]
[ROW][C]13[/C][C]-0.32568[/C][C]-2.7635[/C][C]0.003628[/C][/ROW]
[ROW][C]14[/C][C]0.026552[/C][C]0.2253[/C][C]0.41119[/C][/ROW]
[ROW][C]15[/C][C]-0.214963[/C][C]-1.824[/C][C]0.036149[/C][/ROW]
[ROW][C]16[/C][C]0.122525[/C][C]1.0397[/C][C]0.150989[/C][/ROW]
[ROW][C]17[/C][C]-0.014407[/C][C]-0.1222[/C][C]0.451521[/C][/ROW]
[ROW][C]18[/C][C]0.059647[/C][C]0.5061[/C][C]0.307158[/C][/ROW]
[ROW][C]19[/C][C]-0.144592[/C][C]-1.2269[/C][C]0.111928[/C][/ROW]
[ROW][C]20[/C][C]0.004964[/C][C]0.0421[/C][C]0.483258[/C][/ROW]
[ROW][C]21[/C][C]0.028183[/C][C]0.2391[/C][C]0.405839[/C][/ROW]
[ROW][C]22[/C][C]-0.13165[/C][C]-1.1171[/C][C]0.133836[/C][/ROW]
[ROW][C]23[/C][C]0.062628[/C][C]0.5314[/C][C]0.298384[/C][/ROW]
[ROW][C]24[/C][C]0.040706[/C][C]0.3454[/C][C]0.3654[/C][/ROW]
[ROW][C]25[/C][C]0.032158[/C][C]0.2729[/C][C]0.392866[/C][/ROW]
[ROW][C]26[/C][C]-0.123943[/C][C]-1.0517[/C][C]0.14823[/C][/ROW]
[ROW][C]27[/C][C]0.012554[/C][C]0.1065[/C][C]0.457731[/C][/ROW]
[ROW][C]28[/C][C]0.036371[/C][C]0.3086[/C][C]0.379252[/C][/ROW]
[ROW][C]29[/C][C]0.011664[/C][C]0.099[/C][C]0.460718[/C][/ROW]
[ROW][C]30[/C][C]-0.154324[/C][C]-1.3095[/C][C]0.097268[/C][/ROW]
[ROW][C]31[/C][C]-0.139734[/C][C]-1.1857[/C][C]0.119822[/C][/ROW]
[ROW][C]32[/C][C]-0.032861[/C][C]-0.2788[/C][C]0.390586[/C][/ROW]
[ROW][C]33[/C][C]-0.108088[/C][C]-0.9172[/C][C]0.181061[/C][/ROW]
[ROW][C]34[/C][C]0.039282[/C][C]0.3333[/C][C]0.36993[/C][/ROW]
[ROW][C]35[/C][C]0.027879[/C][C]0.2366[/C][C]0.406834[/C][/ROW]
[ROW][C]36[/C][C]-0.012306[/C][C]-0.1044[/C][C]0.458563[/C][/ROW]
[ROW][C]37[/C][C]-0.147426[/C][C]-1.2509[/C][C]0.107502[/C][/ROW]
[ROW][C]38[/C][C]0.076238[/C][C]0.6469[/C][C]0.259876[/C][/ROW]
[ROW][C]39[/C][C]-0.046317[/C][C]-0.393[/C][C]0.347735[/C][/ROW]
[ROW][C]40[/C][C]-0.009291[/C][C]-0.0788[/C][C]0.468689[/C][/ROW]
[ROW][C]41[/C][C]0.032086[/C][C]0.2723[/C][C]0.3931[/C][/ROW]
[ROW][C]42[/C][C]0.074155[/C][C]0.6292[/C][C]0.265597[/C][/ROW]
[ROW][C]43[/C][C]0.00381[/C][C]0.0323[/C][C]0.487149[/C][/ROW]
[ROW][C]44[/C][C]0.031156[/C][C]0.2644[/C][C]0.396127[/C][/ROW]
[ROW][C]45[/C][C]0.080746[/C][C]0.6852[/C][C]0.247723[/C][/ROW]
[ROW][C]46[/C][C]0.034593[/C][C]0.2935[/C][C]0.384981[/C][/ROW]
[ROW][C]47[/C][C]-0.051617[/C][C]-0.438[/C][C]0.331354[/C][/ROW]
[ROW][C]48[/C][C]0.015411[/C][C]0.1308[/C][C]0.448161[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75228&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75228&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
10.6965545.91050
20.3310292.80890.003198
30.3276272.780.003465
4-0.071414-0.6060.273222
50.1579461.34020.092194
6-0.189313-1.60640.056284
7-0.057032-0.48390.314951
80.0092730.07870.46875
9-0.083809-0.71110.239645
10-0.179345-1.52180.06622
110.1204121.02170.155165
120.1595131.35350.090064
13-0.32568-2.76350.003628
140.0265520.22530.41119
15-0.214963-1.8240.036149
160.1225251.03970.150989
17-0.014407-0.12220.451521
180.0596470.50610.307158
19-0.144592-1.22690.111928
200.0049640.04210.483258
210.0281830.23910.405839
22-0.13165-1.11710.133836
230.0626280.53140.298384
240.0407060.34540.3654
250.0321580.27290.392866
26-0.123943-1.05170.14823
270.0125540.10650.457731
280.0363710.30860.379252
290.0116640.0990.460718
30-0.154324-1.30950.097268
31-0.139734-1.18570.119822
32-0.032861-0.27880.390586
33-0.108088-0.91720.181061
340.0392820.33330.36993
350.0278790.23660.406834
36-0.012306-0.10440.458563
37-0.147426-1.25090.107502
380.0762380.64690.259876
39-0.046317-0.3930.347735
40-0.009291-0.07880.468689
410.0320860.27230.3931
420.0741550.62920.265597
430.003810.03230.487149
440.0311560.26440.396127
450.0807460.68520.247723
460.0345930.29350.384981
47-0.051617-0.4380.331354
480.0154110.13080.448161



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 ;
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')