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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 15 Nov 2011 07:01:36 -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/15/t1321358616vpuojzd1vf7ln2b.htm/, Retrieved Thu, 28 Mar 2024 13:48:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=142792, Retrieved Thu, 28 Mar 2024 13:48:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [gemiddelde consum...] [2011-11-15 12:01:36] [bd8cebb9d7961275d2f6ed94788b7e5f] [Current]
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Dataseries X:
20,98		
20,1		
20,61		
20,27		
20,08		
23,58		
22,31		
22,89		
21,78		
22,19		
22,58		
22,78		
25,06		
25,16		
25,47		
25,34		
24,2		
25,32		
25,57		
25,76		
24,79		
23,14		
22,66		
22,06		
24,26		
23,15		
22,92		
21,43		
21,56		
23,48		
24,35		
24,83		
24,19		
23,58		
23,58		
24,35		
27,18		
25,69		
24,81		
23,26		
23,49		
26,86		
27,12		
27,66		
26,26		
25,51		
24,63		
23,57		
27,63		
25,85		
26,09		
24,47		
24,19		
25,09		
25,26		
25,58		
24,76		
25,02		
24,24		
24,14		
28,69		
26,74		
26,48		
24,45		
23,88		
26,58		
26,23		
28,63		
26,81		
26,56		
26,64		
26,8		
28,37		
27,13		
28,44		
28,62		
27,28		
31,32		
31,26		
31,41		
31,76		
32,72		
32,15		
33,62		
35,97		
33,78		
33,77		
32,75		
32,55		
33,22		
32,88		
31,56		
30,27		
28,65		
27,89		
27,07		
30,8		
28,38		
27,5		
28		
28,02		
29,2		
27,59		
27,22		
27,16		
26,31		
25,67		
26,41		
28,34		
25,43		
23,72		
23,33		
23,8		
27,7		
26,28		
27,51		
27,93		
28,76		
28,65		
29,52		
31,23		
27,9		
27,87		
27,52		
27,59		
31,2		
30,22		
30,62		
31,52		
30,59		
31,42		
31,95		




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142792&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142792&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142792&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'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.209024-2.39240.009079
2-0.026332-0.30140.381801
3-0.14128-1.6170.054139
4-0.265785-3.0420.00142
50.3394693.88548.1e-05
6-0.019464-0.22280.412027
70.3204623.66790.000177
8-0.226195-2.58890.005358
9-0.189836-2.17280.015798
10-0.036271-0.41510.339359
11-0.181543-2.07790.019838
120.6211517.10940
13-0.175821-2.01240.023116
14-0.102393-1.17190.121674
15-0.145067-1.66040.049616
16-0.244882-2.80280.002918
170.3663564.19312.5e-05
18-0.060003-0.68680.246722
190.2976433.40670.000437
20-0.26617-3.04650.0014
21-0.151037-1.72870.04311
22-0.077567-0.88780.18814
23-0.108621-1.24320.108003
240.5086415.82170
25-0.213226-2.44050.008002
26-0.037022-0.42370.336228
27-0.133713-1.53040.064162
28-0.265407-3.03770.001439
290.3403363.89537.8e-05
30-0.029949-0.34280.366155
310.2090292.39240.009078
32-0.200856-2.29890.011547
33-0.174131-1.9930.024169
340.0061280.07010.472097
35-0.114992-1.31610.095211
360.4941375.65570
37-0.210105-2.40480.008791
38-0.038998-0.44630.328041
39-0.051586-0.59040.277962
40-0.177913-2.03630.021867
410.2597172.97260.001758
42-0.019675-0.22520.41109
430.1798112.0580.020785
44-0.209028-2.39240.009078
45-0.098045-1.12220.13192
460.0422310.48340.314824
47-0.045528-0.52110.301593
480.4256974.87232e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.209024 & -2.3924 & 0.009079 \tabularnewline
2 & -0.026332 & -0.3014 & 0.381801 \tabularnewline
3 & -0.14128 & -1.617 & 0.054139 \tabularnewline
4 & -0.265785 & -3.042 & 0.00142 \tabularnewline
5 & 0.339469 & 3.8854 & 8.1e-05 \tabularnewline
6 & -0.019464 & -0.2228 & 0.412027 \tabularnewline
7 & 0.320462 & 3.6679 & 0.000177 \tabularnewline
8 & -0.226195 & -2.5889 & 0.005358 \tabularnewline
9 & -0.189836 & -2.1728 & 0.015798 \tabularnewline
10 & -0.036271 & -0.4151 & 0.339359 \tabularnewline
11 & -0.181543 & -2.0779 & 0.019838 \tabularnewline
12 & 0.621151 & 7.1094 & 0 \tabularnewline
13 & -0.175821 & -2.0124 & 0.023116 \tabularnewline
14 & -0.102393 & -1.1719 & 0.121674 \tabularnewline
15 & -0.145067 & -1.6604 & 0.049616 \tabularnewline
16 & -0.244882 & -2.8028 & 0.002918 \tabularnewline
17 & 0.366356 & 4.1931 & 2.5e-05 \tabularnewline
18 & -0.060003 & -0.6868 & 0.246722 \tabularnewline
19 & 0.297643 & 3.4067 & 0.000437 \tabularnewline
20 & -0.26617 & -3.0465 & 0.0014 \tabularnewline
21 & -0.151037 & -1.7287 & 0.04311 \tabularnewline
22 & -0.077567 & -0.8878 & 0.18814 \tabularnewline
23 & -0.108621 & -1.2432 & 0.108003 \tabularnewline
24 & 0.508641 & 5.8217 & 0 \tabularnewline
25 & -0.213226 & -2.4405 & 0.008002 \tabularnewline
26 & -0.037022 & -0.4237 & 0.336228 \tabularnewline
27 & -0.133713 & -1.5304 & 0.064162 \tabularnewline
28 & -0.265407 & -3.0377 & 0.001439 \tabularnewline
29 & 0.340336 & 3.8953 & 7.8e-05 \tabularnewline
30 & -0.029949 & -0.3428 & 0.366155 \tabularnewline
31 & 0.209029 & 2.3924 & 0.009078 \tabularnewline
32 & -0.200856 & -2.2989 & 0.011547 \tabularnewline
33 & -0.174131 & -1.993 & 0.024169 \tabularnewline
34 & 0.006128 & 0.0701 & 0.472097 \tabularnewline
35 & -0.114992 & -1.3161 & 0.095211 \tabularnewline
36 & 0.494137 & 5.6557 & 0 \tabularnewline
37 & -0.210105 & -2.4048 & 0.008791 \tabularnewline
38 & -0.038998 & -0.4463 & 0.328041 \tabularnewline
39 & -0.051586 & -0.5904 & 0.277962 \tabularnewline
40 & -0.177913 & -2.0363 & 0.021867 \tabularnewline
41 & 0.259717 & 2.9726 & 0.001758 \tabularnewline
42 & -0.019675 & -0.2252 & 0.41109 \tabularnewline
43 & 0.179811 & 2.058 & 0.020785 \tabularnewline
44 & -0.209028 & -2.3924 & 0.009078 \tabularnewline
45 & -0.098045 & -1.1222 & 0.13192 \tabularnewline
46 & 0.042231 & 0.4834 & 0.314824 \tabularnewline
47 & -0.045528 & -0.5211 & 0.301593 \tabularnewline
48 & 0.425697 & 4.8723 & 2e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142792&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]-0.209024[/C][C]-2.3924[/C][C]0.009079[/C][/ROW]
[ROW][C]2[/C][C]-0.026332[/C][C]-0.3014[/C][C]0.381801[/C][/ROW]
[ROW][C]3[/C][C]-0.14128[/C][C]-1.617[/C][C]0.054139[/C][/ROW]
[ROW][C]4[/C][C]-0.265785[/C][C]-3.042[/C][C]0.00142[/C][/ROW]
[ROW][C]5[/C][C]0.339469[/C][C]3.8854[/C][C]8.1e-05[/C][/ROW]
[ROW][C]6[/C][C]-0.019464[/C][C]-0.2228[/C][C]0.412027[/C][/ROW]
[ROW][C]7[/C][C]0.320462[/C][C]3.6679[/C][C]0.000177[/C][/ROW]
[ROW][C]8[/C][C]-0.226195[/C][C]-2.5889[/C][C]0.005358[/C][/ROW]
[ROW][C]9[/C][C]-0.189836[/C][C]-2.1728[/C][C]0.015798[/C][/ROW]
[ROW][C]10[/C][C]-0.036271[/C][C]-0.4151[/C][C]0.339359[/C][/ROW]
[ROW][C]11[/C][C]-0.181543[/C][C]-2.0779[/C][C]0.019838[/C][/ROW]
[ROW][C]12[/C][C]0.621151[/C][C]7.1094[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.175821[/C][C]-2.0124[/C][C]0.023116[/C][/ROW]
[ROW][C]14[/C][C]-0.102393[/C][C]-1.1719[/C][C]0.121674[/C][/ROW]
[ROW][C]15[/C][C]-0.145067[/C][C]-1.6604[/C][C]0.049616[/C][/ROW]
[ROW][C]16[/C][C]-0.244882[/C][C]-2.8028[/C][C]0.002918[/C][/ROW]
[ROW][C]17[/C][C]0.366356[/C][C]4.1931[/C][C]2.5e-05[/C][/ROW]
[ROW][C]18[/C][C]-0.060003[/C][C]-0.6868[/C][C]0.246722[/C][/ROW]
[ROW][C]19[/C][C]0.297643[/C][C]3.4067[/C][C]0.000437[/C][/ROW]
[ROW][C]20[/C][C]-0.26617[/C][C]-3.0465[/C][C]0.0014[/C][/ROW]
[ROW][C]21[/C][C]-0.151037[/C][C]-1.7287[/C][C]0.04311[/C][/ROW]
[ROW][C]22[/C][C]-0.077567[/C][C]-0.8878[/C][C]0.18814[/C][/ROW]
[ROW][C]23[/C][C]-0.108621[/C][C]-1.2432[/C][C]0.108003[/C][/ROW]
[ROW][C]24[/C][C]0.508641[/C][C]5.8217[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.213226[/C][C]-2.4405[/C][C]0.008002[/C][/ROW]
[ROW][C]26[/C][C]-0.037022[/C][C]-0.4237[/C][C]0.336228[/C][/ROW]
[ROW][C]27[/C][C]-0.133713[/C][C]-1.5304[/C][C]0.064162[/C][/ROW]
[ROW][C]28[/C][C]-0.265407[/C][C]-3.0377[/C][C]0.001439[/C][/ROW]
[ROW][C]29[/C][C]0.340336[/C][C]3.8953[/C][C]7.8e-05[/C][/ROW]
[ROW][C]30[/C][C]-0.029949[/C][C]-0.3428[/C][C]0.366155[/C][/ROW]
[ROW][C]31[/C][C]0.209029[/C][C]2.3924[/C][C]0.009078[/C][/ROW]
[ROW][C]32[/C][C]-0.200856[/C][C]-2.2989[/C][C]0.011547[/C][/ROW]
[ROW][C]33[/C][C]-0.174131[/C][C]-1.993[/C][C]0.024169[/C][/ROW]
[ROW][C]34[/C][C]0.006128[/C][C]0.0701[/C][C]0.472097[/C][/ROW]
[ROW][C]35[/C][C]-0.114992[/C][C]-1.3161[/C][C]0.095211[/C][/ROW]
[ROW][C]36[/C][C]0.494137[/C][C]5.6557[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.210105[/C][C]-2.4048[/C][C]0.008791[/C][/ROW]
[ROW][C]38[/C][C]-0.038998[/C][C]-0.4463[/C][C]0.328041[/C][/ROW]
[ROW][C]39[/C][C]-0.051586[/C][C]-0.5904[/C][C]0.277962[/C][/ROW]
[ROW][C]40[/C][C]-0.177913[/C][C]-2.0363[/C][C]0.021867[/C][/ROW]
[ROW][C]41[/C][C]0.259717[/C][C]2.9726[/C][C]0.001758[/C][/ROW]
[ROW][C]42[/C][C]-0.019675[/C][C]-0.2252[/C][C]0.41109[/C][/ROW]
[ROW][C]43[/C][C]0.179811[/C][C]2.058[/C][C]0.020785[/C][/ROW]
[ROW][C]44[/C][C]-0.209028[/C][C]-2.3924[/C][C]0.009078[/C][/ROW]
[ROW][C]45[/C][C]-0.098045[/C][C]-1.1222[/C][C]0.13192[/C][/ROW]
[ROW][C]46[/C][C]0.042231[/C][C]0.4834[/C][C]0.314824[/C][/ROW]
[ROW][C]47[/C][C]-0.045528[/C][C]-0.5211[/C][C]0.301593[/C][/ROW]
[ROW][C]48[/C][C]0.425697[/C][C]4.8723[/C][C]2e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142792&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142792&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
1-0.209024-2.39240.009079
2-0.026332-0.30140.381801
3-0.14128-1.6170.054139
4-0.265785-3.0420.00142
50.3394693.88548.1e-05
6-0.019464-0.22280.412027
70.3204623.66790.000177
8-0.226195-2.58890.005358
9-0.189836-2.17280.015798
10-0.036271-0.41510.339359
11-0.181543-2.07790.019838
120.6211517.10940
13-0.175821-2.01240.023116
14-0.102393-1.17190.121674
15-0.145067-1.66040.049616
16-0.244882-2.80280.002918
170.3663564.19312.5e-05
18-0.060003-0.68680.246722
190.2976433.40670.000437
20-0.26617-3.04650.0014
21-0.151037-1.72870.04311
22-0.077567-0.88780.18814
23-0.108621-1.24320.108003
240.5086415.82170
25-0.213226-2.44050.008002
26-0.037022-0.42370.336228
27-0.133713-1.53040.064162
28-0.265407-3.03770.001439
290.3403363.89537.8e-05
30-0.029949-0.34280.366155
310.2090292.39240.009078
32-0.200856-2.29890.011547
33-0.174131-1.9930.024169
340.0061280.07010.472097
35-0.114992-1.31610.095211
360.4941375.65570
37-0.210105-2.40480.008791
38-0.038998-0.44630.328041
39-0.051586-0.59040.277962
40-0.177913-2.03630.021867
410.2597172.97260.001758
42-0.019675-0.22520.41109
430.1798112.0580.020785
44-0.209028-2.39240.009078
45-0.098045-1.12220.13192
460.0422310.48340.314824
47-0.045528-0.52110.301593
480.4256974.87232e-06







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.209024-2.39240.009079
2-0.073222-0.83810.201761
3-0.170832-1.95530.026341
4-0.365911-4.1882.6e-05
50.193952.21990.014074
60.0403690.4620.322409
70.3372453.85998.9e-05
8-0.094281-1.07910.141265
9-0.067923-0.77740.219157
10-0.151377-1.73260.042761
11-0.224466-2.56910.005658
120.4013464.59365e-06
13-0.049558-0.56720.285768
14-0.193143-2.21060.014399
15-0.115746-1.32480.093777
16-0.023798-0.27240.39288
170.1515641.73470.04257
18-0.044496-0.50930.305708
190.079460.90950.182387
20-0.149142-1.7070.045095
210.0808950.92590.178103
22-0.20549-2.35190.010083
23-0.019329-0.22120.412631
24-0.017081-0.19550.422654
25-0.146191-1.67320.048334
26-0.022264-0.25480.39963
270.0306170.35040.363292
28-0.128342-1.46890.072123
29-0.034663-0.39670.346105
300.0641610.73440.232023
31-0.049111-0.56210.287504
32-0.008749-0.10010.460194
33-0.081967-0.93820.174946
34-0.019526-0.22350.411753
35-0.100517-1.15050.126023
360.0294710.33730.368213
37-0.083373-0.95420.170858
38-0.107217-1.22720.110982
390.1008341.15410.125281
400.1075291.23070.110316
41-0.064699-0.74050.230158
42-0.101802-1.16520.123031
430.009590.10980.456381
44-0.10945-1.25270.106272
450.0644450.73760.231037
46-0.042301-0.48420.314541
470.0147490.16880.433102
480.0346280.39630.34625

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.209024 & -2.3924 & 0.009079 \tabularnewline
2 & -0.073222 & -0.8381 & 0.201761 \tabularnewline
3 & -0.170832 & -1.9553 & 0.026341 \tabularnewline
4 & -0.365911 & -4.188 & 2.6e-05 \tabularnewline
5 & 0.19395 & 2.2199 & 0.014074 \tabularnewline
6 & 0.040369 & 0.462 & 0.322409 \tabularnewline
7 & 0.337245 & 3.8599 & 8.9e-05 \tabularnewline
8 & -0.094281 & -1.0791 & 0.141265 \tabularnewline
9 & -0.067923 & -0.7774 & 0.219157 \tabularnewline
10 & -0.151377 & -1.7326 & 0.042761 \tabularnewline
11 & -0.224466 & -2.5691 & 0.005658 \tabularnewline
12 & 0.401346 & 4.5936 & 5e-06 \tabularnewline
13 & -0.049558 & -0.5672 & 0.285768 \tabularnewline
14 & -0.193143 & -2.2106 & 0.014399 \tabularnewline
15 & -0.115746 & -1.3248 & 0.093777 \tabularnewline
16 & -0.023798 & -0.2724 & 0.39288 \tabularnewline
17 & 0.151564 & 1.7347 & 0.04257 \tabularnewline
18 & -0.044496 & -0.5093 & 0.305708 \tabularnewline
19 & 0.07946 & 0.9095 & 0.182387 \tabularnewline
20 & -0.149142 & -1.707 & 0.045095 \tabularnewline
21 & 0.080895 & 0.9259 & 0.178103 \tabularnewline
22 & -0.20549 & -2.3519 & 0.010083 \tabularnewline
23 & -0.019329 & -0.2212 & 0.412631 \tabularnewline
24 & -0.017081 & -0.1955 & 0.422654 \tabularnewline
25 & -0.146191 & -1.6732 & 0.048334 \tabularnewline
26 & -0.022264 & -0.2548 & 0.39963 \tabularnewline
27 & 0.030617 & 0.3504 & 0.363292 \tabularnewline
28 & -0.128342 & -1.4689 & 0.072123 \tabularnewline
29 & -0.034663 & -0.3967 & 0.346105 \tabularnewline
30 & 0.064161 & 0.7344 & 0.232023 \tabularnewline
31 & -0.049111 & -0.5621 & 0.287504 \tabularnewline
32 & -0.008749 & -0.1001 & 0.460194 \tabularnewline
33 & -0.081967 & -0.9382 & 0.174946 \tabularnewline
34 & -0.019526 & -0.2235 & 0.411753 \tabularnewline
35 & -0.100517 & -1.1505 & 0.126023 \tabularnewline
36 & 0.029471 & 0.3373 & 0.368213 \tabularnewline
37 & -0.083373 & -0.9542 & 0.170858 \tabularnewline
38 & -0.107217 & -1.2272 & 0.110982 \tabularnewline
39 & 0.100834 & 1.1541 & 0.125281 \tabularnewline
40 & 0.107529 & 1.2307 & 0.110316 \tabularnewline
41 & -0.064699 & -0.7405 & 0.230158 \tabularnewline
42 & -0.101802 & -1.1652 & 0.123031 \tabularnewline
43 & 0.00959 & 0.1098 & 0.456381 \tabularnewline
44 & -0.10945 & -1.2527 & 0.106272 \tabularnewline
45 & 0.064445 & 0.7376 & 0.231037 \tabularnewline
46 & -0.042301 & -0.4842 & 0.314541 \tabularnewline
47 & 0.014749 & 0.1688 & 0.433102 \tabularnewline
48 & 0.034628 & 0.3963 & 0.34625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142792&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]-0.209024[/C][C]-2.3924[/C][C]0.009079[/C][/ROW]
[ROW][C]2[/C][C]-0.073222[/C][C]-0.8381[/C][C]0.201761[/C][/ROW]
[ROW][C]3[/C][C]-0.170832[/C][C]-1.9553[/C][C]0.026341[/C][/ROW]
[ROW][C]4[/C][C]-0.365911[/C][C]-4.188[/C][C]2.6e-05[/C][/ROW]
[ROW][C]5[/C][C]0.19395[/C][C]2.2199[/C][C]0.014074[/C][/ROW]
[ROW][C]6[/C][C]0.040369[/C][C]0.462[/C][C]0.322409[/C][/ROW]
[ROW][C]7[/C][C]0.337245[/C][C]3.8599[/C][C]8.9e-05[/C][/ROW]
[ROW][C]8[/C][C]-0.094281[/C][C]-1.0791[/C][C]0.141265[/C][/ROW]
[ROW][C]9[/C][C]-0.067923[/C][C]-0.7774[/C][C]0.219157[/C][/ROW]
[ROW][C]10[/C][C]-0.151377[/C][C]-1.7326[/C][C]0.042761[/C][/ROW]
[ROW][C]11[/C][C]-0.224466[/C][C]-2.5691[/C][C]0.005658[/C][/ROW]
[ROW][C]12[/C][C]0.401346[/C][C]4.5936[/C][C]5e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.049558[/C][C]-0.5672[/C][C]0.285768[/C][/ROW]
[ROW][C]14[/C][C]-0.193143[/C][C]-2.2106[/C][C]0.014399[/C][/ROW]
[ROW][C]15[/C][C]-0.115746[/C][C]-1.3248[/C][C]0.093777[/C][/ROW]
[ROW][C]16[/C][C]-0.023798[/C][C]-0.2724[/C][C]0.39288[/C][/ROW]
[ROW][C]17[/C][C]0.151564[/C][C]1.7347[/C][C]0.04257[/C][/ROW]
[ROW][C]18[/C][C]-0.044496[/C][C]-0.5093[/C][C]0.305708[/C][/ROW]
[ROW][C]19[/C][C]0.07946[/C][C]0.9095[/C][C]0.182387[/C][/ROW]
[ROW][C]20[/C][C]-0.149142[/C][C]-1.707[/C][C]0.045095[/C][/ROW]
[ROW][C]21[/C][C]0.080895[/C][C]0.9259[/C][C]0.178103[/C][/ROW]
[ROW][C]22[/C][C]-0.20549[/C][C]-2.3519[/C][C]0.010083[/C][/ROW]
[ROW][C]23[/C][C]-0.019329[/C][C]-0.2212[/C][C]0.412631[/C][/ROW]
[ROW][C]24[/C][C]-0.017081[/C][C]-0.1955[/C][C]0.422654[/C][/ROW]
[ROW][C]25[/C][C]-0.146191[/C][C]-1.6732[/C][C]0.048334[/C][/ROW]
[ROW][C]26[/C][C]-0.022264[/C][C]-0.2548[/C][C]0.39963[/C][/ROW]
[ROW][C]27[/C][C]0.030617[/C][C]0.3504[/C][C]0.363292[/C][/ROW]
[ROW][C]28[/C][C]-0.128342[/C][C]-1.4689[/C][C]0.072123[/C][/ROW]
[ROW][C]29[/C][C]-0.034663[/C][C]-0.3967[/C][C]0.346105[/C][/ROW]
[ROW][C]30[/C][C]0.064161[/C][C]0.7344[/C][C]0.232023[/C][/ROW]
[ROW][C]31[/C][C]-0.049111[/C][C]-0.5621[/C][C]0.287504[/C][/ROW]
[ROW][C]32[/C][C]-0.008749[/C][C]-0.1001[/C][C]0.460194[/C][/ROW]
[ROW][C]33[/C][C]-0.081967[/C][C]-0.9382[/C][C]0.174946[/C][/ROW]
[ROW][C]34[/C][C]-0.019526[/C][C]-0.2235[/C][C]0.411753[/C][/ROW]
[ROW][C]35[/C][C]-0.100517[/C][C]-1.1505[/C][C]0.126023[/C][/ROW]
[ROW][C]36[/C][C]0.029471[/C][C]0.3373[/C][C]0.368213[/C][/ROW]
[ROW][C]37[/C][C]-0.083373[/C][C]-0.9542[/C][C]0.170858[/C][/ROW]
[ROW][C]38[/C][C]-0.107217[/C][C]-1.2272[/C][C]0.110982[/C][/ROW]
[ROW][C]39[/C][C]0.100834[/C][C]1.1541[/C][C]0.125281[/C][/ROW]
[ROW][C]40[/C][C]0.107529[/C][C]1.2307[/C][C]0.110316[/C][/ROW]
[ROW][C]41[/C][C]-0.064699[/C][C]-0.7405[/C][C]0.230158[/C][/ROW]
[ROW][C]42[/C][C]-0.101802[/C][C]-1.1652[/C][C]0.123031[/C][/ROW]
[ROW][C]43[/C][C]0.00959[/C][C]0.1098[/C][C]0.456381[/C][/ROW]
[ROW][C]44[/C][C]-0.10945[/C][C]-1.2527[/C][C]0.106272[/C][/ROW]
[ROW][C]45[/C][C]0.064445[/C][C]0.7376[/C][C]0.231037[/C][/ROW]
[ROW][C]46[/C][C]-0.042301[/C][C]-0.4842[/C][C]0.314541[/C][/ROW]
[ROW][C]47[/C][C]0.014749[/C][C]0.1688[/C][C]0.433102[/C][/ROW]
[ROW][C]48[/C][C]0.034628[/C][C]0.3963[/C][C]0.34625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142792&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142792&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
1-0.209024-2.39240.009079
2-0.073222-0.83810.201761
3-0.170832-1.95530.026341
4-0.365911-4.1882.6e-05
50.193952.21990.014074
60.0403690.4620.322409
70.3372453.85998.9e-05
8-0.094281-1.07910.141265
9-0.067923-0.77740.219157
10-0.151377-1.73260.042761
11-0.224466-2.56910.005658
120.4013464.59365e-06
13-0.049558-0.56720.285768
14-0.193143-2.21060.014399
15-0.115746-1.32480.093777
16-0.023798-0.27240.39288
170.1515641.73470.04257
18-0.044496-0.50930.305708
190.079460.90950.182387
20-0.149142-1.7070.045095
210.0808950.92590.178103
22-0.20549-2.35190.010083
23-0.019329-0.22120.412631
24-0.017081-0.19550.422654
25-0.146191-1.67320.048334
26-0.022264-0.25480.39963
270.0306170.35040.363292
28-0.128342-1.46890.072123
29-0.034663-0.39670.346105
300.0641610.73440.232023
31-0.049111-0.56210.287504
32-0.008749-0.10010.460194
33-0.081967-0.93820.174946
34-0.019526-0.22350.411753
35-0.100517-1.15050.126023
360.0294710.33730.368213
37-0.083373-0.95420.170858
38-0.107217-1.22720.110982
390.1008341.15410.125281
400.1075291.23070.110316
41-0.064699-0.74050.230158
42-0.101802-1.16520.123031
430.009590.10980.456381
44-0.10945-1.25270.106272
450.0644450.73760.231037
46-0.042301-0.48420.314541
470.0147490.16880.433102
480.0346280.39630.34625



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')