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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 computationFri, 23 Dec 2011 09:14:36 -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/Dec/23/t1324649686ry8pt8o7zj60qjg.htm/, Retrieved Thu, 31 Oct 2024 23:09:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160432, Retrieved Thu, 31 Oct 2024 23:09:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [ WS 9 : ACF - d=0...] [2010-12-08 10:48:57] [2c786c21adba4dd4c8af44dce5258f06]
-   P             [(Partial) Autocorrelation Function] [ws 9 : ACF d=0 D=1 ] [2010-12-08 11:00:09] [2c786c21adba4dd4c8af44dce5258f06]
-   P               [(Partial) Autocorrelation Function] [ws 9 : ACF d=0 D=...] [2010-12-08 14:54:21] [2c786c21adba4dd4c8af44dce5258f06]
- R PD                  [(Partial) Autocorrelation Function] [] [2011-12-23 14:14:36] [c80accbb627afb8a1e74b91ef6a0d2c4] [Current]
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Dataseries X:
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
707
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160432&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160432&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160432&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'AstonUniversity' @ aston.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.221431.32860.096174
20.0391960.23520.407702
30.3295981.97760.027835
40.0027110.01630.493555
50.2211071.32660.09649
60.2706961.62420.056532
7-0.050656-0.30390.381462
80.1156870.69410.24603
90.0943950.56640.287329
100.0805030.4830.316005
110.1597280.95840.172135
12-0.09256-0.55540.291041
13-0.169438-1.01660.158058
140.1357860.81470.210295
150.0359960.2160.415113
16-0.190588-1.14350.130183
17-0.064353-0.38610.350842
18-0.14891-0.89350.188773
19-0.187577-1.12550.133921
200.1120640.67240.252815
21-0.057505-0.3450.36604
22-0.202523-1.21510.116111
23-0.148336-0.890.189683
24-0.233816-1.40290.084607
25-0.066322-0.39790.346515
26-0.061257-0.36750.357684
27-0.296744-1.78050.041721
28-0.064508-0.3870.3505
29-0.056173-0.3370.369022
30-0.155206-0.93120.178967
310.0154480.09270.463332
32-0.065708-0.39430.347861
33-0.089092-0.53460.298122
340.0399540.23970.405952
350.0269710.16180.436174
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.22143 & 1.3286 & 0.096174 \tabularnewline
2 & 0.039196 & 0.2352 & 0.407702 \tabularnewline
3 & 0.329598 & 1.9776 & 0.027835 \tabularnewline
4 & 0.002711 & 0.0163 & 0.493555 \tabularnewline
5 & 0.221107 & 1.3266 & 0.09649 \tabularnewline
6 & 0.270696 & 1.6242 & 0.056532 \tabularnewline
7 & -0.050656 & -0.3039 & 0.381462 \tabularnewline
8 & 0.115687 & 0.6941 & 0.24603 \tabularnewline
9 & 0.094395 & 0.5664 & 0.287329 \tabularnewline
10 & 0.080503 & 0.483 & 0.316005 \tabularnewline
11 & 0.159728 & 0.9584 & 0.172135 \tabularnewline
12 & -0.09256 & -0.5554 & 0.291041 \tabularnewline
13 & -0.169438 & -1.0166 & 0.158058 \tabularnewline
14 & 0.135786 & 0.8147 & 0.210295 \tabularnewline
15 & 0.035996 & 0.216 & 0.415113 \tabularnewline
16 & -0.190588 & -1.1435 & 0.130183 \tabularnewline
17 & -0.064353 & -0.3861 & 0.350842 \tabularnewline
18 & -0.14891 & -0.8935 & 0.188773 \tabularnewline
19 & -0.187577 & -1.1255 & 0.133921 \tabularnewline
20 & 0.112064 & 0.6724 & 0.252815 \tabularnewline
21 & -0.057505 & -0.345 & 0.36604 \tabularnewline
22 & -0.202523 & -1.2151 & 0.116111 \tabularnewline
23 & -0.148336 & -0.89 & 0.189683 \tabularnewline
24 & -0.233816 & -1.4029 & 0.084607 \tabularnewline
25 & -0.066322 & -0.3979 & 0.346515 \tabularnewline
26 & -0.061257 & -0.3675 & 0.357684 \tabularnewline
27 & -0.296744 & -1.7805 & 0.041721 \tabularnewline
28 & -0.064508 & -0.387 & 0.3505 \tabularnewline
29 & -0.056173 & -0.337 & 0.369022 \tabularnewline
30 & -0.155206 & -0.9312 & 0.178967 \tabularnewline
31 & 0.015448 & 0.0927 & 0.463332 \tabularnewline
32 & -0.065708 & -0.3943 & 0.347861 \tabularnewline
33 & -0.089092 & -0.5346 & 0.298122 \tabularnewline
34 & 0.039954 & 0.2397 & 0.405952 \tabularnewline
35 & 0.026971 & 0.1618 & 0.436174 \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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160432&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]0.22143[/C][C]1.3286[/C][C]0.096174[/C][/ROW]
[ROW][C]2[/C][C]0.039196[/C][C]0.2352[/C][C]0.407702[/C][/ROW]
[ROW][C]3[/C][C]0.329598[/C][C]1.9776[/C][C]0.027835[/C][/ROW]
[ROW][C]4[/C][C]0.002711[/C][C]0.0163[/C][C]0.493555[/C][/ROW]
[ROW][C]5[/C][C]0.221107[/C][C]1.3266[/C][C]0.09649[/C][/ROW]
[ROW][C]6[/C][C]0.270696[/C][C]1.6242[/C][C]0.056532[/C][/ROW]
[ROW][C]7[/C][C]-0.050656[/C][C]-0.3039[/C][C]0.381462[/C][/ROW]
[ROW][C]8[/C][C]0.115687[/C][C]0.6941[/C][C]0.24603[/C][/ROW]
[ROW][C]9[/C][C]0.094395[/C][C]0.5664[/C][C]0.287329[/C][/ROW]
[ROW][C]10[/C][C]0.080503[/C][C]0.483[/C][C]0.316005[/C][/ROW]
[ROW][C]11[/C][C]0.159728[/C][C]0.9584[/C][C]0.172135[/C][/ROW]
[ROW][C]12[/C][C]-0.09256[/C][C]-0.5554[/C][C]0.291041[/C][/ROW]
[ROW][C]13[/C][C]-0.169438[/C][C]-1.0166[/C][C]0.158058[/C][/ROW]
[ROW][C]14[/C][C]0.135786[/C][C]0.8147[/C][C]0.210295[/C][/ROW]
[ROW][C]15[/C][C]0.035996[/C][C]0.216[/C][C]0.415113[/C][/ROW]
[ROW][C]16[/C][C]-0.190588[/C][C]-1.1435[/C][C]0.130183[/C][/ROW]
[ROW][C]17[/C][C]-0.064353[/C][C]-0.3861[/C][C]0.350842[/C][/ROW]
[ROW][C]18[/C][C]-0.14891[/C][C]-0.8935[/C][C]0.188773[/C][/ROW]
[ROW][C]19[/C][C]-0.187577[/C][C]-1.1255[/C][C]0.133921[/C][/ROW]
[ROW][C]20[/C][C]0.112064[/C][C]0.6724[/C][C]0.252815[/C][/ROW]
[ROW][C]21[/C][C]-0.057505[/C][C]-0.345[/C][C]0.36604[/C][/ROW]
[ROW][C]22[/C][C]-0.202523[/C][C]-1.2151[/C][C]0.116111[/C][/ROW]
[ROW][C]23[/C][C]-0.148336[/C][C]-0.89[/C][C]0.189683[/C][/ROW]
[ROW][C]24[/C][C]-0.233816[/C][C]-1.4029[/C][C]0.084607[/C][/ROW]
[ROW][C]25[/C][C]-0.066322[/C][C]-0.3979[/C][C]0.346515[/C][/ROW]
[ROW][C]26[/C][C]-0.061257[/C][C]-0.3675[/C][C]0.357684[/C][/ROW]
[ROW][C]27[/C][C]-0.296744[/C][C]-1.7805[/C][C]0.041721[/C][/ROW]
[ROW][C]28[/C][C]-0.064508[/C][C]-0.387[/C][C]0.3505[/C][/ROW]
[ROW][C]29[/C][C]-0.056173[/C][C]-0.337[/C][C]0.369022[/C][/ROW]
[ROW][C]30[/C][C]-0.155206[/C][C]-0.9312[/C][C]0.178967[/C][/ROW]
[ROW][C]31[/C][C]0.015448[/C][C]0.0927[/C][C]0.463332[/C][/ROW]
[ROW][C]32[/C][C]-0.065708[/C][C]-0.3943[/C][C]0.347861[/C][/ROW]
[ROW][C]33[/C][C]-0.089092[/C][C]-0.5346[/C][C]0.298122[/C][/ROW]
[ROW][C]34[/C][C]0.039954[/C][C]0.2397[/C][C]0.405952[/C][/ROW]
[ROW][C]35[/C][C]0.026971[/C][C]0.1618[/C][C]0.436174[/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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160432&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160432&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
10.221431.32860.096174
20.0391960.23520.407702
30.3295981.97760.027835
40.0027110.01630.493555
50.2211071.32660.09649
60.2706961.62420.056532
7-0.050656-0.30390.381462
80.1156870.69410.24603
90.0943950.56640.287329
100.0805030.4830.316005
110.1597280.95840.172135
12-0.09256-0.55540.291041
13-0.169438-1.01660.158058
140.1357860.81470.210295
150.0359960.2160.415113
16-0.190588-1.14350.130183
17-0.064353-0.38610.350842
18-0.14891-0.89350.188773
19-0.187577-1.12550.133921
200.1120640.67240.252815
21-0.057505-0.3450.36604
22-0.202523-1.21510.116111
23-0.148336-0.890.189683
24-0.233816-1.40290.084607
25-0.066322-0.39790.346515
26-0.061257-0.36750.357684
27-0.296744-1.78050.041721
28-0.064508-0.3870.3505
29-0.056173-0.3370.369022
30-0.155206-0.93120.178967
310.0154480.09270.463332
32-0.065708-0.39430.347861
33-0.089092-0.53460.298122
340.0399540.23970.405952
350.0269710.16180.436174
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.221431.32860.096174
2-0.010342-0.06210.475433
30.3398152.03890.024428
4-0.171264-1.02760.1555
50.3389932.0340.024688
6-0.007361-0.04420.482509
7-0.023681-0.14210.443901
8-0.002407-0.01440.494279
9-0.013885-0.08330.467034
100.140710.84430.20205
11-0.048753-0.29250.385786
12-0.128277-0.76970.223262
13-0.20733-1.2440.110773
140.2192951.31580.098284
15-0.053434-0.32060.375182
16-0.217929-1.30760.099653
17-0.054044-0.32430.373809
18-0.044012-0.26410.396615
19-0.033426-0.20060.421087
200.0998760.59930.276378
21-0.016768-0.10060.46021
22-0.034054-0.20430.419626
23-0.169863-1.01920.157459
24-0.084332-0.5060.307974
25-0.010708-0.06420.474563
260.0011660.0070.497228
27-0.090088-0.54050.296081
280.0589960.3540.36271
29-0.0356-0.21360.416033
300.0182440.10950.456721
31-0.028403-0.17040.432817
320.0749540.44970.327802
330.1423550.85410.19934
34-0.057391-0.34430.366295
350.0135370.08120.467857
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.22143 & 1.3286 & 0.096174 \tabularnewline
2 & -0.010342 & -0.0621 & 0.475433 \tabularnewline
3 & 0.339815 & 2.0389 & 0.024428 \tabularnewline
4 & -0.171264 & -1.0276 & 0.1555 \tabularnewline
5 & 0.338993 & 2.034 & 0.024688 \tabularnewline
6 & -0.007361 & -0.0442 & 0.482509 \tabularnewline
7 & -0.023681 & -0.1421 & 0.443901 \tabularnewline
8 & -0.002407 & -0.0144 & 0.494279 \tabularnewline
9 & -0.013885 & -0.0833 & 0.467034 \tabularnewline
10 & 0.14071 & 0.8443 & 0.20205 \tabularnewline
11 & -0.048753 & -0.2925 & 0.385786 \tabularnewline
12 & -0.128277 & -0.7697 & 0.223262 \tabularnewline
13 & -0.20733 & -1.244 & 0.110773 \tabularnewline
14 & 0.219295 & 1.3158 & 0.098284 \tabularnewline
15 & -0.053434 & -0.3206 & 0.375182 \tabularnewline
16 & -0.217929 & -1.3076 & 0.099653 \tabularnewline
17 & -0.054044 & -0.3243 & 0.373809 \tabularnewline
18 & -0.044012 & -0.2641 & 0.396615 \tabularnewline
19 & -0.033426 & -0.2006 & 0.421087 \tabularnewline
20 & 0.099876 & 0.5993 & 0.276378 \tabularnewline
21 & -0.016768 & -0.1006 & 0.46021 \tabularnewline
22 & -0.034054 & -0.2043 & 0.419626 \tabularnewline
23 & -0.169863 & -1.0192 & 0.157459 \tabularnewline
24 & -0.084332 & -0.506 & 0.307974 \tabularnewline
25 & -0.010708 & -0.0642 & 0.474563 \tabularnewline
26 & 0.001166 & 0.007 & 0.497228 \tabularnewline
27 & -0.090088 & -0.5405 & 0.296081 \tabularnewline
28 & 0.058996 & 0.354 & 0.36271 \tabularnewline
29 & -0.0356 & -0.2136 & 0.416033 \tabularnewline
30 & 0.018244 & 0.1095 & 0.456721 \tabularnewline
31 & -0.028403 & -0.1704 & 0.432817 \tabularnewline
32 & 0.074954 & 0.4497 & 0.327802 \tabularnewline
33 & 0.142355 & 0.8541 & 0.19934 \tabularnewline
34 & -0.057391 & -0.3443 & 0.366295 \tabularnewline
35 & 0.013537 & 0.0812 & 0.467857 \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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160432&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]0.22143[/C][C]1.3286[/C][C]0.096174[/C][/ROW]
[ROW][C]2[/C][C]-0.010342[/C][C]-0.0621[/C][C]0.475433[/C][/ROW]
[ROW][C]3[/C][C]0.339815[/C][C]2.0389[/C][C]0.024428[/C][/ROW]
[ROW][C]4[/C][C]-0.171264[/C][C]-1.0276[/C][C]0.1555[/C][/ROW]
[ROW][C]5[/C][C]0.338993[/C][C]2.034[/C][C]0.024688[/C][/ROW]
[ROW][C]6[/C][C]-0.007361[/C][C]-0.0442[/C][C]0.482509[/C][/ROW]
[ROW][C]7[/C][C]-0.023681[/C][C]-0.1421[/C][C]0.443901[/C][/ROW]
[ROW][C]8[/C][C]-0.002407[/C][C]-0.0144[/C][C]0.494279[/C][/ROW]
[ROW][C]9[/C][C]-0.013885[/C][C]-0.0833[/C][C]0.467034[/C][/ROW]
[ROW][C]10[/C][C]0.14071[/C][C]0.8443[/C][C]0.20205[/C][/ROW]
[ROW][C]11[/C][C]-0.048753[/C][C]-0.2925[/C][C]0.385786[/C][/ROW]
[ROW][C]12[/C][C]-0.128277[/C][C]-0.7697[/C][C]0.223262[/C][/ROW]
[ROW][C]13[/C][C]-0.20733[/C][C]-1.244[/C][C]0.110773[/C][/ROW]
[ROW][C]14[/C][C]0.219295[/C][C]1.3158[/C][C]0.098284[/C][/ROW]
[ROW][C]15[/C][C]-0.053434[/C][C]-0.3206[/C][C]0.375182[/C][/ROW]
[ROW][C]16[/C][C]-0.217929[/C][C]-1.3076[/C][C]0.099653[/C][/ROW]
[ROW][C]17[/C][C]-0.054044[/C][C]-0.3243[/C][C]0.373809[/C][/ROW]
[ROW][C]18[/C][C]-0.044012[/C][C]-0.2641[/C][C]0.396615[/C][/ROW]
[ROW][C]19[/C][C]-0.033426[/C][C]-0.2006[/C][C]0.421087[/C][/ROW]
[ROW][C]20[/C][C]0.099876[/C][C]0.5993[/C][C]0.276378[/C][/ROW]
[ROW][C]21[/C][C]-0.016768[/C][C]-0.1006[/C][C]0.46021[/C][/ROW]
[ROW][C]22[/C][C]-0.034054[/C][C]-0.2043[/C][C]0.419626[/C][/ROW]
[ROW][C]23[/C][C]-0.169863[/C][C]-1.0192[/C][C]0.157459[/C][/ROW]
[ROW][C]24[/C][C]-0.084332[/C][C]-0.506[/C][C]0.307974[/C][/ROW]
[ROW][C]25[/C][C]-0.010708[/C][C]-0.0642[/C][C]0.474563[/C][/ROW]
[ROW][C]26[/C][C]0.001166[/C][C]0.007[/C][C]0.497228[/C][/ROW]
[ROW][C]27[/C][C]-0.090088[/C][C]-0.5405[/C][C]0.296081[/C][/ROW]
[ROW][C]28[/C][C]0.058996[/C][C]0.354[/C][C]0.36271[/C][/ROW]
[ROW][C]29[/C][C]-0.0356[/C][C]-0.2136[/C][C]0.416033[/C][/ROW]
[ROW][C]30[/C][C]0.018244[/C][C]0.1095[/C][C]0.456721[/C][/ROW]
[ROW][C]31[/C][C]-0.028403[/C][C]-0.1704[/C][C]0.432817[/C][/ROW]
[ROW][C]32[/C][C]0.074954[/C][C]0.4497[/C][C]0.327802[/C][/ROW]
[ROW][C]33[/C][C]0.142355[/C][C]0.8541[/C][C]0.19934[/C][/ROW]
[ROW][C]34[/C][C]-0.057391[/C][C]-0.3443[/C][C]0.366295[/C][/ROW]
[ROW][C]35[/C][C]0.013537[/C][C]0.0812[/C][C]0.467857[/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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160432&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160432&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
10.221431.32860.096174
2-0.010342-0.06210.475433
30.3398152.03890.024428
4-0.171264-1.02760.1555
50.3389932.0340.024688
6-0.007361-0.04420.482509
7-0.023681-0.14210.443901
8-0.002407-0.01440.494279
9-0.013885-0.08330.467034
100.140710.84430.20205
11-0.048753-0.29250.385786
12-0.128277-0.76970.223262
13-0.20733-1.2440.110773
140.2192951.31580.098284
15-0.053434-0.32060.375182
16-0.217929-1.30760.099653
17-0.054044-0.32430.373809
18-0.044012-0.26410.396615
19-0.033426-0.20060.421087
200.0998760.59930.276378
21-0.016768-0.10060.46021
22-0.034054-0.20430.419626
23-0.169863-1.01920.157459
24-0.084332-0.5060.307974
25-0.010708-0.06420.474563
260.0011660.0070.497228
27-0.090088-0.54050.296081
280.0589960.3540.36271
29-0.0356-0.21360.416033
300.0182440.10950.456721
31-0.028403-0.17040.432817
320.0749540.44970.327802
330.1423550.85410.19934
34-0.057391-0.34430.366295
350.0135370.08120.467857
36NANANA
37NANANA
38NANANA
39NANANA
40NANANA
41NANANA
42NANANA
43NANANA
44NANANA
45NANANA
46NANANA
47NANANA
48NANANA



Parameters (Session):
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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 (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')