Free Statistics

of Irreproducible Research!

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, 18 Dec 2010 13:07:11 +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/18/t12926776731fm94azc6l9l6jh.htm/, Retrieved Tue, 30 Apr 2024 00:41:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111940, Retrieved Tue, 30 Apr 2024 00:41:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Multiple Regressi...] [2010-12-09 13:10:55] [d6a5e6c1b0014d57cedb2bdfb4a7099f]
- RMPD  [(Partial) Autocorrelation Function] [Autocorrelation F...] [2010-12-12 20:17:05] [d6a5e6c1b0014d57cedb2bdfb4a7099f]
-   P       [(Partial) Autocorrelation Function] [Correlation Funct...] [2010-12-18 13:07:11] [039869833c16fe697975601e6b065e0f] [Current]
Feedback Forum

Post a new message
Dataseries X:
1038.00
934.00
988.00
870.00
854.00
834.00
872.00
954.00
870.00
1238.00
1082.00
1053.00
934.00
787.00
1081.00
908.00
995.00
825.00
822.00
856.00
887.00
1094.00
990.00
936.00
1097.00
918.00
926.00
907.00
899.00
971.00
1087.00
1000.00
1071.00
1190.00
1116.00
1070.00
1314.00
1068.00
1185.00
1215.00
1145.00
1251.00
1363.00
1368.00
1535.00
1853.00
1866.00
2023.00
1373.00
1968.00
1424.00
1160.00
1243.00
1375.00
1539.00
1773.00
1906.00
2076.00
2004.00




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=111940&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=111940&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111940&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
1-0.524067-3.55440.000445
20.1482661.00560.159937
30.0208860.14170.443984
4-0.108519-0.7360.232729
5-0.061546-0.41740.339155
60.0692910.470.320304
7-0.076813-0.5210.302442
80.0399160.27070.393908
90.0230380.15620.43826
100.0258980.17560.43067
110.0555280.37660.354099
12-0.130776-0.8870.189855
130.0176950.120.452497
14-0.004464-0.03030.487989
150.0392120.2660.395733
16-0.008162-0.05540.478048
170.0622120.42190.337517
18-0.05875-0.39850.346067
19-0.045023-0.30540.380735
200.1046970.71010.240617
21-0.16977-1.15140.127751
220.145520.9870.164412
23-0.073073-0.49560.311266
24-0.061007-0.41380.340483
250.167951.13910.130281
26-0.107645-0.73010.234521
270.0359920.24410.404117
28-0.106021-0.71910.237867
290.0632480.4290.334974
30-0.012949-0.08780.465198
310.0842680.57150.285211
32-0.053009-0.35950.360424
330.0942110.6390.263006
34-0.129834-0.88060.191563
350.0925750.62790.266596
36-0.060772-0.41220.341063
37-0.023001-0.1560.438359
380.0065630.04450.482343
390.0128420.08710.465486
400.0076140.05160.479521
410.0190750.12940.448814
42-0.007237-0.04910.480534
43-0.010575-0.07170.471567
44-0.005092-0.03450.4863
450.0016080.01090.495672
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.524067 & -3.5544 & 0.000445 \tabularnewline
2 & 0.148266 & 1.0056 & 0.159937 \tabularnewline
3 & 0.020886 & 0.1417 & 0.443984 \tabularnewline
4 & -0.108519 & -0.736 & 0.232729 \tabularnewline
5 & -0.061546 & -0.4174 & 0.339155 \tabularnewline
6 & 0.069291 & 0.47 & 0.320304 \tabularnewline
7 & -0.076813 & -0.521 & 0.302442 \tabularnewline
8 & 0.039916 & 0.2707 & 0.393908 \tabularnewline
9 & 0.023038 & 0.1562 & 0.43826 \tabularnewline
10 & 0.025898 & 0.1756 & 0.43067 \tabularnewline
11 & 0.055528 & 0.3766 & 0.354099 \tabularnewline
12 & -0.130776 & -0.887 & 0.189855 \tabularnewline
13 & 0.017695 & 0.12 & 0.452497 \tabularnewline
14 & -0.004464 & -0.0303 & 0.487989 \tabularnewline
15 & 0.039212 & 0.266 & 0.395733 \tabularnewline
16 & -0.008162 & -0.0554 & 0.478048 \tabularnewline
17 & 0.062212 & 0.4219 & 0.337517 \tabularnewline
18 & -0.05875 & -0.3985 & 0.346067 \tabularnewline
19 & -0.045023 & -0.3054 & 0.380735 \tabularnewline
20 & 0.104697 & 0.7101 & 0.240617 \tabularnewline
21 & -0.16977 & -1.1514 & 0.127751 \tabularnewline
22 & 0.14552 & 0.987 & 0.164412 \tabularnewline
23 & -0.073073 & -0.4956 & 0.311266 \tabularnewline
24 & -0.061007 & -0.4138 & 0.340483 \tabularnewline
25 & 0.16795 & 1.1391 & 0.130281 \tabularnewline
26 & -0.107645 & -0.7301 & 0.234521 \tabularnewline
27 & 0.035992 & 0.2441 & 0.404117 \tabularnewline
28 & -0.106021 & -0.7191 & 0.237867 \tabularnewline
29 & 0.063248 & 0.429 & 0.334974 \tabularnewline
30 & -0.012949 & -0.0878 & 0.465198 \tabularnewline
31 & 0.084268 & 0.5715 & 0.285211 \tabularnewline
32 & -0.053009 & -0.3595 & 0.360424 \tabularnewline
33 & 0.094211 & 0.639 & 0.263006 \tabularnewline
34 & -0.129834 & -0.8806 & 0.191563 \tabularnewline
35 & 0.092575 & 0.6279 & 0.266596 \tabularnewline
36 & -0.060772 & -0.4122 & 0.341063 \tabularnewline
37 & -0.023001 & -0.156 & 0.438359 \tabularnewline
38 & 0.006563 & 0.0445 & 0.482343 \tabularnewline
39 & 0.012842 & 0.0871 & 0.465486 \tabularnewline
40 & 0.007614 & 0.0516 & 0.479521 \tabularnewline
41 & 0.019075 & 0.1294 & 0.448814 \tabularnewline
42 & -0.007237 & -0.0491 & 0.480534 \tabularnewline
43 & -0.010575 & -0.0717 & 0.471567 \tabularnewline
44 & -0.005092 & -0.0345 & 0.4863 \tabularnewline
45 & 0.001608 & 0.0109 & 0.495672 \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=111940&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]-0.524067[/C][C]-3.5544[/C][C]0.000445[/C][/ROW]
[ROW][C]2[/C][C]0.148266[/C][C]1.0056[/C][C]0.159937[/C][/ROW]
[ROW][C]3[/C][C]0.020886[/C][C]0.1417[/C][C]0.443984[/C][/ROW]
[ROW][C]4[/C][C]-0.108519[/C][C]-0.736[/C][C]0.232729[/C][/ROW]
[ROW][C]5[/C][C]-0.061546[/C][C]-0.4174[/C][C]0.339155[/C][/ROW]
[ROW][C]6[/C][C]0.069291[/C][C]0.47[/C][C]0.320304[/C][/ROW]
[ROW][C]7[/C][C]-0.076813[/C][C]-0.521[/C][C]0.302442[/C][/ROW]
[ROW][C]8[/C][C]0.039916[/C][C]0.2707[/C][C]0.393908[/C][/ROW]
[ROW][C]9[/C][C]0.023038[/C][C]0.1562[/C][C]0.43826[/C][/ROW]
[ROW][C]10[/C][C]0.025898[/C][C]0.1756[/C][C]0.43067[/C][/ROW]
[ROW][C]11[/C][C]0.055528[/C][C]0.3766[/C][C]0.354099[/C][/ROW]
[ROW][C]12[/C][C]-0.130776[/C][C]-0.887[/C][C]0.189855[/C][/ROW]
[ROW][C]13[/C][C]0.017695[/C][C]0.12[/C][C]0.452497[/C][/ROW]
[ROW][C]14[/C][C]-0.004464[/C][C]-0.0303[/C][C]0.487989[/C][/ROW]
[ROW][C]15[/C][C]0.039212[/C][C]0.266[/C][C]0.395733[/C][/ROW]
[ROW][C]16[/C][C]-0.008162[/C][C]-0.0554[/C][C]0.478048[/C][/ROW]
[ROW][C]17[/C][C]0.062212[/C][C]0.4219[/C][C]0.337517[/C][/ROW]
[ROW][C]18[/C][C]-0.05875[/C][C]-0.3985[/C][C]0.346067[/C][/ROW]
[ROW][C]19[/C][C]-0.045023[/C][C]-0.3054[/C][C]0.380735[/C][/ROW]
[ROW][C]20[/C][C]0.104697[/C][C]0.7101[/C][C]0.240617[/C][/ROW]
[ROW][C]21[/C][C]-0.16977[/C][C]-1.1514[/C][C]0.127751[/C][/ROW]
[ROW][C]22[/C][C]0.14552[/C][C]0.987[/C][C]0.164412[/C][/ROW]
[ROW][C]23[/C][C]-0.073073[/C][C]-0.4956[/C][C]0.311266[/C][/ROW]
[ROW][C]24[/C][C]-0.061007[/C][C]-0.4138[/C][C]0.340483[/C][/ROW]
[ROW][C]25[/C][C]0.16795[/C][C]1.1391[/C][C]0.130281[/C][/ROW]
[ROW][C]26[/C][C]-0.107645[/C][C]-0.7301[/C][C]0.234521[/C][/ROW]
[ROW][C]27[/C][C]0.035992[/C][C]0.2441[/C][C]0.404117[/C][/ROW]
[ROW][C]28[/C][C]-0.106021[/C][C]-0.7191[/C][C]0.237867[/C][/ROW]
[ROW][C]29[/C][C]0.063248[/C][C]0.429[/C][C]0.334974[/C][/ROW]
[ROW][C]30[/C][C]-0.012949[/C][C]-0.0878[/C][C]0.465198[/C][/ROW]
[ROW][C]31[/C][C]0.084268[/C][C]0.5715[/C][C]0.285211[/C][/ROW]
[ROW][C]32[/C][C]-0.053009[/C][C]-0.3595[/C][C]0.360424[/C][/ROW]
[ROW][C]33[/C][C]0.094211[/C][C]0.639[/C][C]0.263006[/C][/ROW]
[ROW][C]34[/C][C]-0.129834[/C][C]-0.8806[/C][C]0.191563[/C][/ROW]
[ROW][C]35[/C][C]0.092575[/C][C]0.6279[/C][C]0.266596[/C][/ROW]
[ROW][C]36[/C][C]-0.060772[/C][C]-0.4122[/C][C]0.341063[/C][/ROW]
[ROW][C]37[/C][C]-0.023001[/C][C]-0.156[/C][C]0.438359[/C][/ROW]
[ROW][C]38[/C][C]0.006563[/C][C]0.0445[/C][C]0.482343[/C][/ROW]
[ROW][C]39[/C][C]0.012842[/C][C]0.0871[/C][C]0.465486[/C][/ROW]
[ROW][C]40[/C][C]0.007614[/C][C]0.0516[/C][C]0.479521[/C][/ROW]
[ROW][C]41[/C][C]0.019075[/C][C]0.1294[/C][C]0.448814[/C][/ROW]
[ROW][C]42[/C][C]-0.007237[/C][C]-0.0491[/C][C]0.480534[/C][/ROW]
[ROW][C]43[/C][C]-0.010575[/C][C]-0.0717[/C][C]0.471567[/C][/ROW]
[ROW][C]44[/C][C]-0.005092[/C][C]-0.0345[/C][C]0.4863[/C][/ROW]
[ROW][C]45[/C][C]0.001608[/C][C]0.0109[/C][C]0.495672[/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=111940&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111940&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
1-0.524067-3.55440.000445
20.1482661.00560.159937
30.0208860.14170.443984
4-0.108519-0.7360.232729
5-0.061546-0.41740.339155
60.0692910.470.320304
7-0.076813-0.5210.302442
80.0399160.27070.393908
90.0230380.15620.43826
100.0258980.17560.43067
110.0555280.37660.354099
12-0.130776-0.8870.189855
130.0176950.120.452497
14-0.004464-0.03030.487989
150.0392120.2660.395733
16-0.008162-0.05540.478048
170.0622120.42190.337517
18-0.05875-0.39850.346067
19-0.045023-0.30540.380735
200.1046970.71010.240617
21-0.16977-1.15140.127751
220.145520.9870.164412
23-0.073073-0.49560.311266
24-0.061007-0.41380.340483
250.167951.13910.130281
26-0.107645-0.73010.234521
270.0359920.24410.404117
28-0.106021-0.71910.237867
290.0632480.4290.334974
30-0.012949-0.08780.465198
310.0842680.57150.285211
32-0.053009-0.35950.360424
330.0942110.6390.263006
34-0.129834-0.88060.191563
350.0925750.62790.266596
36-0.060772-0.41220.341063
37-0.023001-0.1560.438359
380.0065630.04450.482343
390.0128420.08710.465486
400.0076140.05160.479521
410.0190750.12940.448814
42-0.007237-0.04910.480534
43-0.010575-0.07170.471567
44-0.005092-0.03450.4863
450.0016080.01090.495672
46NANANA
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.524067-3.55440.000445
2-0.174233-1.18170.121698
30.0295960.20070.420898
4-0.081301-0.55140.292012
5-0.23439-1.58970.059375
6-0.115992-0.78670.217746
7-0.093934-0.63710.263612
8-0.068375-0.46370.32251
9-0.03814-0.25870.398519
100.0250550.16990.432904
110.1182440.8020.213347
12-0.089358-0.60610.273728
13-0.161236-1.09360.139922
14-0.078957-0.53550.297437
150.0910150.61730.270043
160.0720410.48860.313722
170.0524240.35560.3619
18-0.019958-0.13540.446458
19-0.137768-0.93440.177491
200.0274010.18580.426693
21-0.094515-0.6410.26234
220.0585820.39730.346483
230.0416170.28230.389506
24-0.162196-1.10010.138514
25-0.0102-0.06920.472572
26-0.036355-0.24660.403169
270.0268390.1820.42818
28-0.190778-1.29390.101076
29-0.091455-0.62030.269067
300.0161510.10950.456625
310.0937720.6360.263968
320.0090740.06150.475596
330.0285860.19390.423563
34-0.032913-0.22320.412173
350.0105180.07130.471719
36-0.015629-0.1060.45802
37-0.029056-0.19710.422323
380.0308270.20910.417655
390.0300990.20410.419571
40-0.074151-0.50290.308712
41-0.053422-0.36230.359384
42-0.066397-0.45030.327295
430.0433670.29410.384992
440.031590.21430.415648
45-0.014907-0.10110.459954
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.524067 & -3.5544 & 0.000445 \tabularnewline
2 & -0.174233 & -1.1817 & 0.121698 \tabularnewline
3 & 0.029596 & 0.2007 & 0.420898 \tabularnewline
4 & -0.081301 & -0.5514 & 0.292012 \tabularnewline
5 & -0.23439 & -1.5897 & 0.059375 \tabularnewline
6 & -0.115992 & -0.7867 & 0.217746 \tabularnewline
7 & -0.093934 & -0.6371 & 0.263612 \tabularnewline
8 & -0.068375 & -0.4637 & 0.32251 \tabularnewline
9 & -0.03814 & -0.2587 & 0.398519 \tabularnewline
10 & 0.025055 & 0.1699 & 0.432904 \tabularnewline
11 & 0.118244 & 0.802 & 0.213347 \tabularnewline
12 & -0.089358 & -0.6061 & 0.273728 \tabularnewline
13 & -0.161236 & -1.0936 & 0.139922 \tabularnewline
14 & -0.078957 & -0.5355 & 0.297437 \tabularnewline
15 & 0.091015 & 0.6173 & 0.270043 \tabularnewline
16 & 0.072041 & 0.4886 & 0.313722 \tabularnewline
17 & 0.052424 & 0.3556 & 0.3619 \tabularnewline
18 & -0.019958 & -0.1354 & 0.446458 \tabularnewline
19 & -0.137768 & -0.9344 & 0.177491 \tabularnewline
20 & 0.027401 & 0.1858 & 0.426693 \tabularnewline
21 & -0.094515 & -0.641 & 0.26234 \tabularnewline
22 & 0.058582 & 0.3973 & 0.346483 \tabularnewline
23 & 0.041617 & 0.2823 & 0.389506 \tabularnewline
24 & -0.162196 & -1.1001 & 0.138514 \tabularnewline
25 & -0.0102 & -0.0692 & 0.472572 \tabularnewline
26 & -0.036355 & -0.2466 & 0.403169 \tabularnewline
27 & 0.026839 & 0.182 & 0.42818 \tabularnewline
28 & -0.190778 & -1.2939 & 0.101076 \tabularnewline
29 & -0.091455 & -0.6203 & 0.269067 \tabularnewline
30 & 0.016151 & 0.1095 & 0.456625 \tabularnewline
31 & 0.093772 & 0.636 & 0.263968 \tabularnewline
32 & 0.009074 & 0.0615 & 0.475596 \tabularnewline
33 & 0.028586 & 0.1939 & 0.423563 \tabularnewline
34 & -0.032913 & -0.2232 & 0.412173 \tabularnewline
35 & 0.010518 & 0.0713 & 0.471719 \tabularnewline
36 & -0.015629 & -0.106 & 0.45802 \tabularnewline
37 & -0.029056 & -0.1971 & 0.422323 \tabularnewline
38 & 0.030827 & 0.2091 & 0.417655 \tabularnewline
39 & 0.030099 & 0.2041 & 0.419571 \tabularnewline
40 & -0.074151 & -0.5029 & 0.308712 \tabularnewline
41 & -0.053422 & -0.3623 & 0.359384 \tabularnewline
42 & -0.066397 & -0.4503 & 0.327295 \tabularnewline
43 & 0.043367 & 0.2941 & 0.384992 \tabularnewline
44 & 0.03159 & 0.2143 & 0.415648 \tabularnewline
45 & -0.014907 & -0.1011 & 0.459954 \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=111940&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]-0.524067[/C][C]-3.5544[/C][C]0.000445[/C][/ROW]
[ROW][C]2[/C][C]-0.174233[/C][C]-1.1817[/C][C]0.121698[/C][/ROW]
[ROW][C]3[/C][C]0.029596[/C][C]0.2007[/C][C]0.420898[/C][/ROW]
[ROW][C]4[/C][C]-0.081301[/C][C]-0.5514[/C][C]0.292012[/C][/ROW]
[ROW][C]5[/C][C]-0.23439[/C][C]-1.5897[/C][C]0.059375[/C][/ROW]
[ROW][C]6[/C][C]-0.115992[/C][C]-0.7867[/C][C]0.217746[/C][/ROW]
[ROW][C]7[/C][C]-0.093934[/C][C]-0.6371[/C][C]0.263612[/C][/ROW]
[ROW][C]8[/C][C]-0.068375[/C][C]-0.4637[/C][C]0.32251[/C][/ROW]
[ROW][C]9[/C][C]-0.03814[/C][C]-0.2587[/C][C]0.398519[/C][/ROW]
[ROW][C]10[/C][C]0.025055[/C][C]0.1699[/C][C]0.432904[/C][/ROW]
[ROW][C]11[/C][C]0.118244[/C][C]0.802[/C][C]0.213347[/C][/ROW]
[ROW][C]12[/C][C]-0.089358[/C][C]-0.6061[/C][C]0.273728[/C][/ROW]
[ROW][C]13[/C][C]-0.161236[/C][C]-1.0936[/C][C]0.139922[/C][/ROW]
[ROW][C]14[/C][C]-0.078957[/C][C]-0.5355[/C][C]0.297437[/C][/ROW]
[ROW][C]15[/C][C]0.091015[/C][C]0.6173[/C][C]0.270043[/C][/ROW]
[ROW][C]16[/C][C]0.072041[/C][C]0.4886[/C][C]0.313722[/C][/ROW]
[ROW][C]17[/C][C]0.052424[/C][C]0.3556[/C][C]0.3619[/C][/ROW]
[ROW][C]18[/C][C]-0.019958[/C][C]-0.1354[/C][C]0.446458[/C][/ROW]
[ROW][C]19[/C][C]-0.137768[/C][C]-0.9344[/C][C]0.177491[/C][/ROW]
[ROW][C]20[/C][C]0.027401[/C][C]0.1858[/C][C]0.426693[/C][/ROW]
[ROW][C]21[/C][C]-0.094515[/C][C]-0.641[/C][C]0.26234[/C][/ROW]
[ROW][C]22[/C][C]0.058582[/C][C]0.3973[/C][C]0.346483[/C][/ROW]
[ROW][C]23[/C][C]0.041617[/C][C]0.2823[/C][C]0.389506[/C][/ROW]
[ROW][C]24[/C][C]-0.162196[/C][C]-1.1001[/C][C]0.138514[/C][/ROW]
[ROW][C]25[/C][C]-0.0102[/C][C]-0.0692[/C][C]0.472572[/C][/ROW]
[ROW][C]26[/C][C]-0.036355[/C][C]-0.2466[/C][C]0.403169[/C][/ROW]
[ROW][C]27[/C][C]0.026839[/C][C]0.182[/C][C]0.42818[/C][/ROW]
[ROW][C]28[/C][C]-0.190778[/C][C]-1.2939[/C][C]0.101076[/C][/ROW]
[ROW][C]29[/C][C]-0.091455[/C][C]-0.6203[/C][C]0.269067[/C][/ROW]
[ROW][C]30[/C][C]0.016151[/C][C]0.1095[/C][C]0.456625[/C][/ROW]
[ROW][C]31[/C][C]0.093772[/C][C]0.636[/C][C]0.263968[/C][/ROW]
[ROW][C]32[/C][C]0.009074[/C][C]0.0615[/C][C]0.475596[/C][/ROW]
[ROW][C]33[/C][C]0.028586[/C][C]0.1939[/C][C]0.423563[/C][/ROW]
[ROW][C]34[/C][C]-0.032913[/C][C]-0.2232[/C][C]0.412173[/C][/ROW]
[ROW][C]35[/C][C]0.010518[/C][C]0.0713[/C][C]0.471719[/C][/ROW]
[ROW][C]36[/C][C]-0.015629[/C][C]-0.106[/C][C]0.45802[/C][/ROW]
[ROW][C]37[/C][C]-0.029056[/C][C]-0.1971[/C][C]0.422323[/C][/ROW]
[ROW][C]38[/C][C]0.030827[/C][C]0.2091[/C][C]0.417655[/C][/ROW]
[ROW][C]39[/C][C]0.030099[/C][C]0.2041[/C][C]0.419571[/C][/ROW]
[ROW][C]40[/C][C]-0.074151[/C][C]-0.5029[/C][C]0.308712[/C][/ROW]
[ROW][C]41[/C][C]-0.053422[/C][C]-0.3623[/C][C]0.359384[/C][/ROW]
[ROW][C]42[/C][C]-0.066397[/C][C]-0.4503[/C][C]0.327295[/C][/ROW]
[ROW][C]43[/C][C]0.043367[/C][C]0.2941[/C][C]0.384992[/C][/ROW]
[ROW][C]44[/C][C]0.03159[/C][C]0.2143[/C][C]0.415648[/C][/ROW]
[ROW][C]45[/C][C]-0.014907[/C][C]-0.1011[/C][C]0.459954[/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=111940&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111940&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
1-0.524067-3.55440.000445
2-0.174233-1.18170.121698
30.0295960.20070.420898
4-0.081301-0.55140.292012
5-0.23439-1.58970.059375
6-0.115992-0.78670.217746
7-0.093934-0.63710.263612
8-0.068375-0.46370.32251
9-0.03814-0.25870.398519
100.0250550.16990.432904
110.1182440.8020.213347
12-0.089358-0.60610.273728
13-0.161236-1.09360.139922
14-0.078957-0.53550.297437
150.0910150.61730.270043
160.0720410.48860.313722
170.0524240.35560.3619
18-0.019958-0.13540.446458
19-0.137768-0.93440.177491
200.0274010.18580.426693
21-0.094515-0.6410.26234
220.0585820.39730.346483
230.0416170.28230.389506
24-0.162196-1.10010.138514
25-0.0102-0.06920.472572
26-0.036355-0.24660.403169
270.0268390.1820.42818
28-0.190778-1.29390.101076
29-0.091455-0.62030.269067
300.0161510.10950.456625
310.0937720.6360.263968
320.0090740.06150.475596
330.0285860.19390.423563
34-0.032913-0.22320.412173
350.0105180.07130.471719
36-0.015629-0.1060.45802
37-0.029056-0.19710.422323
380.0308270.20910.417655
390.0300990.20410.419571
40-0.074151-0.50290.308712
41-0.053422-0.36230.359384
42-0.066397-0.45030.327295
430.0433670.29410.384992
440.031590.21430.415648
45-0.014907-0.10110.459954
46NANANA
47NANANA
48NANANA



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