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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 11 Dec 2010 11:26:57 +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/Dec/11/t1292066716ljf9x5yvakfgrzr.htm/, Retrieved Mon, 06 May 2024 15:18:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108066, Retrieved Mon, 06 May 2024 15:18:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [ACF interventie D=0] [2010-12-11 11:19:23] [04d4386fa51dbd2ef12d0f1f80644886]
-   PD  [(Partial) Autocorrelation Function] [ACF interventie D=1] [2010-12-11 11:23:05] [04d4386fa51dbd2ef12d0f1f80644886]
-   PD    [(Partial) Autocorrelation Function] [ACF aanvoer D=0] [2010-12-11 11:25:10] [04d4386fa51dbd2ef12d0f1f80644886]
-   PD        [(Partial) Autocorrelation Function] [ACF aanvoer D=1] [2010-12-11 11:26:57] [de8ccb310fbbdc3d90ae577a3e011cf9] [Current]
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Dataseries X:
1606
1634
2013
1654
1003
1029
1052
1653
1918
1926
1862
1816
1712
1646
1555
1402
1047
891
940
1372
2012
1879
1667
1856
1771
1721
1773
1507
1033
1011
1111
1736
1865
2078
1947
1428
1500
1950
1591
1613
1077
880
1128
1320
1692
1575
1478
1500
1368
1563
1424
1274
1047
1049
1069
981
1540
1559
1459
1559




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108066&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]1 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=108066&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108066&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1983191.3740.087913
24.9e-053e-040.499865
30.3004822.08180.021358
40.073110.50650.307404
50.1758021.2180.114591
60.1413320.97920.166202
70.0284650.19720.422248
80.0897330.62170.268543
9-0.109662-0.75980.225557
100.0574350.39790.346226
11-0.00789-0.05470.478318
12-0.362284-2.510.00775
130.0223530.15490.438787
14-0.052983-0.36710.357589
15-0.289621-2.00660.025224
16-0.147321-1.02070.156264
17-0.155069-1.07430.144019
18-0.215861-1.49550.070662
19-0.132786-0.920.181096
20-0.153285-1.0620.146778
210.0128480.0890.464722
22-0.060465-0.41890.338575
23-0.138427-0.9590.17117
24-0.035994-0.24940.402069
25-0.132133-0.91540.182267
26-0.005918-0.0410.483733
270.09580.66370.255022
280.0392320.27180.393468
290.0484380.33560.369322
300.0450350.3120.37819
310.0656860.45510.325549
320.0782730.54230.295064
33-0.028844-0.19980.421226
340.007940.0550.478181
350.0398280.27590.391891
360.0426560.29550.384432
370.0391760.27140.393615
38-0.034581-0.23960.405837
39-0.072155-0.49990.309714
400.0137830.09550.462162
410.0744570.51590.304161
42-0.000189-0.00130.49948
43-0.032144-0.22270.412358
44-0.024671-0.17090.432501
45-0.01702-0.11790.453314
460.0087450.06060.475971
470.0103210.07150.471645
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.198319 & 1.374 & 0.087913 \tabularnewline
2 & 4.9e-05 & 3e-04 & 0.499865 \tabularnewline
3 & 0.300482 & 2.0818 & 0.021358 \tabularnewline
4 & 0.07311 & 0.5065 & 0.307404 \tabularnewline
5 & 0.175802 & 1.218 & 0.114591 \tabularnewline
6 & 0.141332 & 0.9792 & 0.166202 \tabularnewline
7 & 0.028465 & 0.1972 & 0.422248 \tabularnewline
8 & 0.089733 & 0.6217 & 0.268543 \tabularnewline
9 & -0.109662 & -0.7598 & 0.225557 \tabularnewline
10 & 0.057435 & 0.3979 & 0.346226 \tabularnewline
11 & -0.00789 & -0.0547 & 0.478318 \tabularnewline
12 & -0.362284 & -2.51 & 0.00775 \tabularnewline
13 & 0.022353 & 0.1549 & 0.438787 \tabularnewline
14 & -0.052983 & -0.3671 & 0.357589 \tabularnewline
15 & -0.289621 & -2.0066 & 0.025224 \tabularnewline
16 & -0.147321 & -1.0207 & 0.156264 \tabularnewline
17 & -0.155069 & -1.0743 & 0.144019 \tabularnewline
18 & -0.215861 & -1.4955 & 0.070662 \tabularnewline
19 & -0.132786 & -0.92 & 0.181096 \tabularnewline
20 & -0.153285 & -1.062 & 0.146778 \tabularnewline
21 & 0.012848 & 0.089 & 0.464722 \tabularnewline
22 & -0.060465 & -0.4189 & 0.338575 \tabularnewline
23 & -0.138427 & -0.959 & 0.17117 \tabularnewline
24 & -0.035994 & -0.2494 & 0.402069 \tabularnewline
25 & -0.132133 & -0.9154 & 0.182267 \tabularnewline
26 & -0.005918 & -0.041 & 0.483733 \tabularnewline
27 & 0.0958 & 0.6637 & 0.255022 \tabularnewline
28 & 0.039232 & 0.2718 & 0.393468 \tabularnewline
29 & 0.048438 & 0.3356 & 0.369322 \tabularnewline
30 & 0.045035 & 0.312 & 0.37819 \tabularnewline
31 & 0.065686 & 0.4551 & 0.325549 \tabularnewline
32 & 0.078273 & 0.5423 & 0.295064 \tabularnewline
33 & -0.028844 & -0.1998 & 0.421226 \tabularnewline
34 & 0.00794 & 0.055 & 0.478181 \tabularnewline
35 & 0.039828 & 0.2759 & 0.391891 \tabularnewline
36 & 0.042656 & 0.2955 & 0.384432 \tabularnewline
37 & 0.039176 & 0.2714 & 0.393615 \tabularnewline
38 & -0.034581 & -0.2396 & 0.405837 \tabularnewline
39 & -0.072155 & -0.4999 & 0.309714 \tabularnewline
40 & 0.013783 & 0.0955 & 0.462162 \tabularnewline
41 & 0.074457 & 0.5159 & 0.304161 \tabularnewline
42 & -0.000189 & -0.0013 & 0.49948 \tabularnewline
43 & -0.032144 & -0.2227 & 0.412358 \tabularnewline
44 & -0.024671 & -0.1709 & 0.432501 \tabularnewline
45 & -0.01702 & -0.1179 & 0.453314 \tabularnewline
46 & 0.008745 & 0.0606 & 0.475971 \tabularnewline
47 & 0.010321 & 0.0715 & 0.471645 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108066&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]0.198319[/C][C]1.374[/C][C]0.087913[/C][/ROW]
[ROW][C]2[/C][C]4.9e-05[/C][C]3e-04[/C][C]0.499865[/C][/ROW]
[ROW][C]3[/C][C]0.300482[/C][C]2.0818[/C][C]0.021358[/C][/ROW]
[ROW][C]4[/C][C]0.07311[/C][C]0.5065[/C][C]0.307404[/C][/ROW]
[ROW][C]5[/C][C]0.175802[/C][C]1.218[/C][C]0.114591[/C][/ROW]
[ROW][C]6[/C][C]0.141332[/C][C]0.9792[/C][C]0.166202[/C][/ROW]
[ROW][C]7[/C][C]0.028465[/C][C]0.1972[/C][C]0.422248[/C][/ROW]
[ROW][C]8[/C][C]0.089733[/C][C]0.6217[/C][C]0.268543[/C][/ROW]
[ROW][C]9[/C][C]-0.109662[/C][C]-0.7598[/C][C]0.225557[/C][/ROW]
[ROW][C]10[/C][C]0.057435[/C][C]0.3979[/C][C]0.346226[/C][/ROW]
[ROW][C]11[/C][C]-0.00789[/C][C]-0.0547[/C][C]0.478318[/C][/ROW]
[ROW][C]12[/C][C]-0.362284[/C][C]-2.51[/C][C]0.00775[/C][/ROW]
[ROW][C]13[/C][C]0.022353[/C][C]0.1549[/C][C]0.438787[/C][/ROW]
[ROW][C]14[/C][C]-0.052983[/C][C]-0.3671[/C][C]0.357589[/C][/ROW]
[ROW][C]15[/C][C]-0.289621[/C][C]-2.0066[/C][C]0.025224[/C][/ROW]
[ROW][C]16[/C][C]-0.147321[/C][C]-1.0207[/C][C]0.156264[/C][/ROW]
[ROW][C]17[/C][C]-0.155069[/C][C]-1.0743[/C][C]0.144019[/C][/ROW]
[ROW][C]18[/C][C]-0.215861[/C][C]-1.4955[/C][C]0.070662[/C][/ROW]
[ROW][C]19[/C][C]-0.132786[/C][C]-0.92[/C][C]0.181096[/C][/ROW]
[ROW][C]20[/C][C]-0.153285[/C][C]-1.062[/C][C]0.146778[/C][/ROW]
[ROW][C]21[/C][C]0.012848[/C][C]0.089[/C][C]0.464722[/C][/ROW]
[ROW][C]22[/C][C]-0.060465[/C][C]-0.4189[/C][C]0.338575[/C][/ROW]
[ROW][C]23[/C][C]-0.138427[/C][C]-0.959[/C][C]0.17117[/C][/ROW]
[ROW][C]24[/C][C]-0.035994[/C][C]-0.2494[/C][C]0.402069[/C][/ROW]
[ROW][C]25[/C][C]-0.132133[/C][C]-0.9154[/C][C]0.182267[/C][/ROW]
[ROW][C]26[/C][C]-0.005918[/C][C]-0.041[/C][C]0.483733[/C][/ROW]
[ROW][C]27[/C][C]0.0958[/C][C]0.6637[/C][C]0.255022[/C][/ROW]
[ROW][C]28[/C][C]0.039232[/C][C]0.2718[/C][C]0.393468[/C][/ROW]
[ROW][C]29[/C][C]0.048438[/C][C]0.3356[/C][C]0.369322[/C][/ROW]
[ROW][C]30[/C][C]0.045035[/C][C]0.312[/C][C]0.37819[/C][/ROW]
[ROW][C]31[/C][C]0.065686[/C][C]0.4551[/C][C]0.325549[/C][/ROW]
[ROW][C]32[/C][C]0.078273[/C][C]0.5423[/C][C]0.295064[/C][/ROW]
[ROW][C]33[/C][C]-0.028844[/C][C]-0.1998[/C][C]0.421226[/C][/ROW]
[ROW][C]34[/C][C]0.00794[/C][C]0.055[/C][C]0.478181[/C][/ROW]
[ROW][C]35[/C][C]0.039828[/C][C]0.2759[/C][C]0.391891[/C][/ROW]
[ROW][C]36[/C][C]0.042656[/C][C]0.2955[/C][C]0.384432[/C][/ROW]
[ROW][C]37[/C][C]0.039176[/C][C]0.2714[/C][C]0.393615[/C][/ROW]
[ROW][C]38[/C][C]-0.034581[/C][C]-0.2396[/C][C]0.405837[/C][/ROW]
[ROW][C]39[/C][C]-0.072155[/C][C]-0.4999[/C][C]0.309714[/C][/ROW]
[ROW][C]40[/C][C]0.013783[/C][C]0.0955[/C][C]0.462162[/C][/ROW]
[ROW][C]41[/C][C]0.074457[/C][C]0.5159[/C][C]0.304161[/C][/ROW]
[ROW][C]42[/C][C]-0.000189[/C][C]-0.0013[/C][C]0.49948[/C][/ROW]
[ROW][C]43[/C][C]-0.032144[/C][C]-0.2227[/C][C]0.412358[/C][/ROW]
[ROW][C]44[/C][C]-0.024671[/C][C]-0.1709[/C][C]0.432501[/C][/ROW]
[ROW][C]45[/C][C]-0.01702[/C][C]-0.1179[/C][C]0.453314[/C][/ROW]
[ROW][C]46[/C][C]0.008745[/C][C]0.0606[/C][C]0.475971[/C][/ROW]
[ROW][C]47[/C][C]0.010321[/C][C]0.0715[/C][C]0.471645[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108066&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108066&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
10.1983191.3740.087913
24.9e-053e-040.499865
30.3004822.08180.021358
40.073110.50650.307404
50.1758021.2180.114591
60.1413320.97920.166202
70.0284650.19720.422248
80.0897330.62170.268543
9-0.109662-0.75980.225557
100.0574350.39790.346226
11-0.00789-0.05470.478318
12-0.362284-2.510.00775
130.0223530.15490.438787
14-0.052983-0.36710.357589
15-0.289621-2.00660.025224
16-0.147321-1.02070.156264
17-0.155069-1.07430.144019
18-0.215861-1.49550.070662
19-0.132786-0.920.181096
20-0.153285-1.0620.146778
210.0128480.0890.464722
22-0.060465-0.41890.338575
23-0.138427-0.9590.17117
24-0.035994-0.24940.402069
25-0.132133-0.91540.182267
26-0.005918-0.0410.483733
270.09580.66370.255022
280.0392320.27180.393468
290.0484380.33560.369322
300.0450350.3120.37819
310.0656860.45510.325549
320.0782730.54230.295064
33-0.028844-0.19980.421226
340.007940.0550.478181
350.0398280.27590.391891
360.0426560.29550.384432
370.0391760.27140.393615
38-0.034581-0.23960.405837
39-0.072155-0.49990.309714
400.0137830.09550.462162
410.0744570.51590.304161
42-0.000189-0.00130.49948
43-0.032144-0.22270.412358
44-0.024671-0.17090.432501
45-0.01702-0.11790.453314
460.0087450.06060.475971
470.0103210.07150.471645
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1983191.3740.087913
2-0.040889-0.28330.389086
30.3217532.22920.015259
4-0.065919-0.45670.324974
50.2402031.66420.051297
6-0.057563-0.39880.345901
70.0617490.42780.335351
8-0.046628-0.3230.374032
9-0.178408-1.2360.111228
100.1181870.81880.208468
11-0.185921-1.28810.101944
12-0.264487-1.83240.036548
130.1187630.82280.207342
14-0.134614-0.93260.177838
15-0.05515-0.38210.352041
16-0.173424-1.20150.117723
170.0653210.45260.326453
18-0.179887-1.24630.109353
190.0588490.40770.342646
20-0.073517-0.50930.306424
210.1800471.24740.10915
220.0170660.11820.453186
23-0.034939-0.24210.404881
24-0.149561-1.03620.152654
25-0.008595-0.05950.476383
260.0021730.01510.494026
27-0.032291-0.22370.411962
280.0773320.53580.297296
290.0095850.06640.473665
30-0.052443-0.36330.358975
310.0329690.22840.410146
32-0.124087-0.85970.197114
33-0.001889-0.01310.494806
34-0.195068-1.35150.09144
350.0189140.1310.448145
36-0.068262-0.47290.319203
370.0505320.35010.363898
38-0.080137-0.55520.290666
39-0.089014-0.61670.27017
400.0845880.5860.280297
410.0376620.26090.397632
42-0.027535-0.19080.424756
430.0046370.03210.487253
44-0.002235-0.01550.493855
450.0257230.17820.429652
46-0.005256-0.03640.485551
470.035230.24410.404104
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.198319 & 1.374 & 0.087913 \tabularnewline
2 & -0.040889 & -0.2833 & 0.389086 \tabularnewline
3 & 0.321753 & 2.2292 & 0.015259 \tabularnewline
4 & -0.065919 & -0.4567 & 0.324974 \tabularnewline
5 & 0.240203 & 1.6642 & 0.051297 \tabularnewline
6 & -0.057563 & -0.3988 & 0.345901 \tabularnewline
7 & 0.061749 & 0.4278 & 0.335351 \tabularnewline
8 & -0.046628 & -0.323 & 0.374032 \tabularnewline
9 & -0.178408 & -1.236 & 0.111228 \tabularnewline
10 & 0.118187 & 0.8188 & 0.208468 \tabularnewline
11 & -0.185921 & -1.2881 & 0.101944 \tabularnewline
12 & -0.264487 & -1.8324 & 0.036548 \tabularnewline
13 & 0.118763 & 0.8228 & 0.207342 \tabularnewline
14 & -0.134614 & -0.9326 & 0.177838 \tabularnewline
15 & -0.05515 & -0.3821 & 0.352041 \tabularnewline
16 & -0.173424 & -1.2015 & 0.117723 \tabularnewline
17 & 0.065321 & 0.4526 & 0.326453 \tabularnewline
18 & -0.179887 & -1.2463 & 0.109353 \tabularnewline
19 & 0.058849 & 0.4077 & 0.342646 \tabularnewline
20 & -0.073517 & -0.5093 & 0.306424 \tabularnewline
21 & 0.180047 & 1.2474 & 0.10915 \tabularnewline
22 & 0.017066 & 0.1182 & 0.453186 \tabularnewline
23 & -0.034939 & -0.2421 & 0.404881 \tabularnewline
24 & -0.149561 & -1.0362 & 0.152654 \tabularnewline
25 & -0.008595 & -0.0595 & 0.476383 \tabularnewline
26 & 0.002173 & 0.0151 & 0.494026 \tabularnewline
27 & -0.032291 & -0.2237 & 0.411962 \tabularnewline
28 & 0.077332 & 0.5358 & 0.297296 \tabularnewline
29 & 0.009585 & 0.0664 & 0.473665 \tabularnewline
30 & -0.052443 & -0.3633 & 0.358975 \tabularnewline
31 & 0.032969 & 0.2284 & 0.410146 \tabularnewline
32 & -0.124087 & -0.8597 & 0.197114 \tabularnewline
33 & -0.001889 & -0.0131 & 0.494806 \tabularnewline
34 & -0.195068 & -1.3515 & 0.09144 \tabularnewline
35 & 0.018914 & 0.131 & 0.448145 \tabularnewline
36 & -0.068262 & -0.4729 & 0.319203 \tabularnewline
37 & 0.050532 & 0.3501 & 0.363898 \tabularnewline
38 & -0.080137 & -0.5552 & 0.290666 \tabularnewline
39 & -0.089014 & -0.6167 & 0.27017 \tabularnewline
40 & 0.084588 & 0.586 & 0.280297 \tabularnewline
41 & 0.037662 & 0.2609 & 0.397632 \tabularnewline
42 & -0.027535 & -0.1908 & 0.424756 \tabularnewline
43 & 0.004637 & 0.0321 & 0.487253 \tabularnewline
44 & -0.002235 & -0.0155 & 0.493855 \tabularnewline
45 & 0.025723 & 0.1782 & 0.429652 \tabularnewline
46 & -0.005256 & -0.0364 & 0.485551 \tabularnewline
47 & 0.03523 & 0.2441 & 0.404104 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108066&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]0.198319[/C][C]1.374[/C][C]0.087913[/C][/ROW]
[ROW][C]2[/C][C]-0.040889[/C][C]-0.2833[/C][C]0.389086[/C][/ROW]
[ROW][C]3[/C][C]0.321753[/C][C]2.2292[/C][C]0.015259[/C][/ROW]
[ROW][C]4[/C][C]-0.065919[/C][C]-0.4567[/C][C]0.324974[/C][/ROW]
[ROW][C]5[/C][C]0.240203[/C][C]1.6642[/C][C]0.051297[/C][/ROW]
[ROW][C]6[/C][C]-0.057563[/C][C]-0.3988[/C][C]0.345901[/C][/ROW]
[ROW][C]7[/C][C]0.061749[/C][C]0.4278[/C][C]0.335351[/C][/ROW]
[ROW][C]8[/C][C]-0.046628[/C][C]-0.323[/C][C]0.374032[/C][/ROW]
[ROW][C]9[/C][C]-0.178408[/C][C]-1.236[/C][C]0.111228[/C][/ROW]
[ROW][C]10[/C][C]0.118187[/C][C]0.8188[/C][C]0.208468[/C][/ROW]
[ROW][C]11[/C][C]-0.185921[/C][C]-1.2881[/C][C]0.101944[/C][/ROW]
[ROW][C]12[/C][C]-0.264487[/C][C]-1.8324[/C][C]0.036548[/C][/ROW]
[ROW][C]13[/C][C]0.118763[/C][C]0.8228[/C][C]0.207342[/C][/ROW]
[ROW][C]14[/C][C]-0.134614[/C][C]-0.9326[/C][C]0.177838[/C][/ROW]
[ROW][C]15[/C][C]-0.05515[/C][C]-0.3821[/C][C]0.352041[/C][/ROW]
[ROW][C]16[/C][C]-0.173424[/C][C]-1.2015[/C][C]0.117723[/C][/ROW]
[ROW][C]17[/C][C]0.065321[/C][C]0.4526[/C][C]0.326453[/C][/ROW]
[ROW][C]18[/C][C]-0.179887[/C][C]-1.2463[/C][C]0.109353[/C][/ROW]
[ROW][C]19[/C][C]0.058849[/C][C]0.4077[/C][C]0.342646[/C][/ROW]
[ROW][C]20[/C][C]-0.073517[/C][C]-0.5093[/C][C]0.306424[/C][/ROW]
[ROW][C]21[/C][C]0.180047[/C][C]1.2474[/C][C]0.10915[/C][/ROW]
[ROW][C]22[/C][C]0.017066[/C][C]0.1182[/C][C]0.453186[/C][/ROW]
[ROW][C]23[/C][C]-0.034939[/C][C]-0.2421[/C][C]0.404881[/C][/ROW]
[ROW][C]24[/C][C]-0.149561[/C][C]-1.0362[/C][C]0.152654[/C][/ROW]
[ROW][C]25[/C][C]-0.008595[/C][C]-0.0595[/C][C]0.476383[/C][/ROW]
[ROW][C]26[/C][C]0.002173[/C][C]0.0151[/C][C]0.494026[/C][/ROW]
[ROW][C]27[/C][C]-0.032291[/C][C]-0.2237[/C][C]0.411962[/C][/ROW]
[ROW][C]28[/C][C]0.077332[/C][C]0.5358[/C][C]0.297296[/C][/ROW]
[ROW][C]29[/C][C]0.009585[/C][C]0.0664[/C][C]0.473665[/C][/ROW]
[ROW][C]30[/C][C]-0.052443[/C][C]-0.3633[/C][C]0.358975[/C][/ROW]
[ROW][C]31[/C][C]0.032969[/C][C]0.2284[/C][C]0.410146[/C][/ROW]
[ROW][C]32[/C][C]-0.124087[/C][C]-0.8597[/C][C]0.197114[/C][/ROW]
[ROW][C]33[/C][C]-0.001889[/C][C]-0.0131[/C][C]0.494806[/C][/ROW]
[ROW][C]34[/C][C]-0.195068[/C][C]-1.3515[/C][C]0.09144[/C][/ROW]
[ROW][C]35[/C][C]0.018914[/C][C]0.131[/C][C]0.448145[/C][/ROW]
[ROW][C]36[/C][C]-0.068262[/C][C]-0.4729[/C][C]0.319203[/C][/ROW]
[ROW][C]37[/C][C]0.050532[/C][C]0.3501[/C][C]0.363898[/C][/ROW]
[ROW][C]38[/C][C]-0.080137[/C][C]-0.5552[/C][C]0.290666[/C][/ROW]
[ROW][C]39[/C][C]-0.089014[/C][C]-0.6167[/C][C]0.27017[/C][/ROW]
[ROW][C]40[/C][C]0.084588[/C][C]0.586[/C][C]0.280297[/C][/ROW]
[ROW][C]41[/C][C]0.037662[/C][C]0.2609[/C][C]0.397632[/C][/ROW]
[ROW][C]42[/C][C]-0.027535[/C][C]-0.1908[/C][C]0.424756[/C][/ROW]
[ROW][C]43[/C][C]0.004637[/C][C]0.0321[/C][C]0.487253[/C][/ROW]
[ROW][C]44[/C][C]-0.002235[/C][C]-0.0155[/C][C]0.493855[/C][/ROW]
[ROW][C]45[/C][C]0.025723[/C][C]0.1782[/C][C]0.429652[/C][/ROW]
[ROW][C]46[/C][C]-0.005256[/C][C]-0.0364[/C][C]0.485551[/C][/ROW]
[ROW][C]47[/C][C]0.03523[/C][C]0.2441[/C][C]0.404104[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108066&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108066&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
10.1983191.3740.087913
2-0.040889-0.28330.389086
30.3217532.22920.015259
4-0.065919-0.45670.324974
50.2402031.66420.051297
6-0.057563-0.39880.345901
70.0617490.42780.335351
8-0.046628-0.3230.374032
9-0.178408-1.2360.111228
100.1181870.81880.208468
11-0.185921-1.28810.101944
12-0.264487-1.83240.036548
130.1187630.82280.207342
14-0.134614-0.93260.177838
15-0.05515-0.38210.352041
16-0.173424-1.20150.117723
170.0653210.45260.326453
18-0.179887-1.24630.109353
190.0588490.40770.342646
20-0.073517-0.50930.306424
210.1800471.24740.10915
220.0170660.11820.453186
23-0.034939-0.24210.404881
24-0.149561-1.03620.152654
25-0.008595-0.05950.476383
260.0021730.01510.494026
27-0.032291-0.22370.411962
280.0773320.53580.297296
290.0095850.06640.473665
30-0.052443-0.36330.358975
310.0329690.22840.410146
32-0.124087-0.85970.197114
33-0.001889-0.01310.494806
34-0.195068-1.35150.09144
350.0189140.1310.448145
36-0.068262-0.47290.319203
370.0505320.35010.363898
38-0.080137-0.55520.290666
39-0.089014-0.61670.27017
400.0845880.5860.280297
410.0376620.26090.397632
42-0.027535-0.19080.424756
430.0046370.03210.487253
44-0.002235-0.01550.493855
450.0257230.17820.429652
46-0.005256-0.03640.485551
470.035230.24410.404104
48NANANA



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