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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 computationThu, 03 Dec 2009 08:49:35 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t1259855865p38h02seubi8lz8.htm/, Retrieved Thu, 28 Mar 2024 12:03:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62861, Retrieved Thu, 28 Mar 2024 12:03:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:47:30] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [] [2009-12-03 15:49:35] [bcaf453a09027aa0f995cb78bdc3c98a] [Current]
-   PD        [(Partial) Autocorrelation Function] [autocorrelatie] [2009-12-04 19:35:20] [3dd791303389e75e672968b227170a72]
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Dataseries X:
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8
8.1
8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62861&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62861&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62861&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8489756.63070
20.608984.75636e-06
30.4222273.29770.000815
40.3756062.93360.002358
50.4233643.30660.000793
60.4459433.48290.000462
70.3592062.80550.003366
80.2150751.67980.049057
90.1061310.82890.205194
100.1085670.84790.199893
110.1758521.37340.08732
120.2300931.79710.038636
130.1814961.41750.080708
140.0852470.66580.254025
15-0.014365-0.11220.455518
16-0.079779-0.62310.267773
17-0.116701-0.91150.182819
18-0.144341-1.12730.132006
19-0.177061-1.38290.08587
20-0.225148-1.75850.041842
21-0.27119-2.11810.019126
22-0.308821-2.4120.009445
23-0.325246-2.54030.00682
24-0.318818-2.490.007756
25-0.306422-2.39320.009897
26-0.269955-2.10840.019555
27-0.241171-1.88360.032194
28-0.236938-1.85050.03454
29-0.275806-2.15410.017595
30-0.325721-2.5440.006755
31-0.350458-2.73720.004054
32-0.356762-2.78640.003547
33-0.323198-2.52430.007106
34-0.259805-2.02910.023407
35-0.211302-1.65030.052009
36-0.180143-1.4070.082256
37-0.15675-1.22430.112782
38-0.110503-0.86310.195743
39-0.048429-0.37820.353283
400.0129190.10090.459981
410.0358960.28040.390077
420.021560.16840.433419
43-0.016848-0.13160.447871
44-0.053211-0.41560.339584
45-0.049176-0.38410.351128
46-0.009544-0.07450.470411
470.0080240.06270.475117
480.0043060.03360.486641

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.848975 & 6.6307 & 0 \tabularnewline
2 & 0.60898 & 4.7563 & 6e-06 \tabularnewline
3 & 0.422227 & 3.2977 & 0.000815 \tabularnewline
4 & 0.375606 & 2.9336 & 0.002358 \tabularnewline
5 & 0.423364 & 3.3066 & 0.000793 \tabularnewline
6 & 0.445943 & 3.4829 & 0.000462 \tabularnewline
7 & 0.359206 & 2.8055 & 0.003366 \tabularnewline
8 & 0.215075 & 1.6798 & 0.049057 \tabularnewline
9 & 0.106131 & 0.8289 & 0.205194 \tabularnewline
10 & 0.108567 & 0.8479 & 0.199893 \tabularnewline
11 & 0.175852 & 1.3734 & 0.08732 \tabularnewline
12 & 0.230093 & 1.7971 & 0.038636 \tabularnewline
13 & 0.181496 & 1.4175 & 0.080708 \tabularnewline
14 & 0.085247 & 0.6658 & 0.254025 \tabularnewline
15 & -0.014365 & -0.1122 & 0.455518 \tabularnewline
16 & -0.079779 & -0.6231 & 0.267773 \tabularnewline
17 & -0.116701 & -0.9115 & 0.182819 \tabularnewline
18 & -0.144341 & -1.1273 & 0.132006 \tabularnewline
19 & -0.177061 & -1.3829 & 0.08587 \tabularnewline
20 & -0.225148 & -1.7585 & 0.041842 \tabularnewline
21 & -0.27119 & -2.1181 & 0.019126 \tabularnewline
22 & -0.308821 & -2.412 & 0.009445 \tabularnewline
23 & -0.325246 & -2.5403 & 0.00682 \tabularnewline
24 & -0.318818 & -2.49 & 0.007756 \tabularnewline
25 & -0.306422 & -2.3932 & 0.009897 \tabularnewline
26 & -0.269955 & -2.1084 & 0.019555 \tabularnewline
27 & -0.241171 & -1.8836 & 0.032194 \tabularnewline
28 & -0.236938 & -1.8505 & 0.03454 \tabularnewline
29 & -0.275806 & -2.1541 & 0.017595 \tabularnewline
30 & -0.325721 & -2.544 & 0.006755 \tabularnewline
31 & -0.350458 & -2.7372 & 0.004054 \tabularnewline
32 & -0.356762 & -2.7864 & 0.003547 \tabularnewline
33 & -0.323198 & -2.5243 & 0.007106 \tabularnewline
34 & -0.259805 & -2.0291 & 0.023407 \tabularnewline
35 & -0.211302 & -1.6503 & 0.052009 \tabularnewline
36 & -0.180143 & -1.407 & 0.082256 \tabularnewline
37 & -0.15675 & -1.2243 & 0.112782 \tabularnewline
38 & -0.110503 & -0.8631 & 0.195743 \tabularnewline
39 & -0.048429 & -0.3782 & 0.353283 \tabularnewline
40 & 0.012919 & 0.1009 & 0.459981 \tabularnewline
41 & 0.035896 & 0.2804 & 0.390077 \tabularnewline
42 & 0.02156 & 0.1684 & 0.433419 \tabularnewline
43 & -0.016848 & -0.1316 & 0.447871 \tabularnewline
44 & -0.053211 & -0.4156 & 0.339584 \tabularnewline
45 & -0.049176 & -0.3841 & 0.351128 \tabularnewline
46 & -0.009544 & -0.0745 & 0.470411 \tabularnewline
47 & 0.008024 & 0.0627 & 0.475117 \tabularnewline
48 & 0.004306 & 0.0336 & 0.486641 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62861&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]0.848975[/C][C]6.6307[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.60898[/C][C]4.7563[/C][C]6e-06[/C][/ROW]
[ROW][C]3[/C][C]0.422227[/C][C]3.2977[/C][C]0.000815[/C][/ROW]
[ROW][C]4[/C][C]0.375606[/C][C]2.9336[/C][C]0.002358[/C][/ROW]
[ROW][C]5[/C][C]0.423364[/C][C]3.3066[/C][C]0.000793[/C][/ROW]
[ROW][C]6[/C][C]0.445943[/C][C]3.4829[/C][C]0.000462[/C][/ROW]
[ROW][C]7[/C][C]0.359206[/C][C]2.8055[/C][C]0.003366[/C][/ROW]
[ROW][C]8[/C][C]0.215075[/C][C]1.6798[/C][C]0.049057[/C][/ROW]
[ROW][C]9[/C][C]0.106131[/C][C]0.8289[/C][C]0.205194[/C][/ROW]
[ROW][C]10[/C][C]0.108567[/C][C]0.8479[/C][C]0.199893[/C][/ROW]
[ROW][C]11[/C][C]0.175852[/C][C]1.3734[/C][C]0.08732[/C][/ROW]
[ROW][C]12[/C][C]0.230093[/C][C]1.7971[/C][C]0.038636[/C][/ROW]
[ROW][C]13[/C][C]0.181496[/C][C]1.4175[/C][C]0.080708[/C][/ROW]
[ROW][C]14[/C][C]0.085247[/C][C]0.6658[/C][C]0.254025[/C][/ROW]
[ROW][C]15[/C][C]-0.014365[/C][C]-0.1122[/C][C]0.455518[/C][/ROW]
[ROW][C]16[/C][C]-0.079779[/C][C]-0.6231[/C][C]0.267773[/C][/ROW]
[ROW][C]17[/C][C]-0.116701[/C][C]-0.9115[/C][C]0.182819[/C][/ROW]
[ROW][C]18[/C][C]-0.144341[/C][C]-1.1273[/C][C]0.132006[/C][/ROW]
[ROW][C]19[/C][C]-0.177061[/C][C]-1.3829[/C][C]0.08587[/C][/ROW]
[ROW][C]20[/C][C]-0.225148[/C][C]-1.7585[/C][C]0.041842[/C][/ROW]
[ROW][C]21[/C][C]-0.27119[/C][C]-2.1181[/C][C]0.019126[/C][/ROW]
[ROW][C]22[/C][C]-0.308821[/C][C]-2.412[/C][C]0.009445[/C][/ROW]
[ROW][C]23[/C][C]-0.325246[/C][C]-2.5403[/C][C]0.00682[/C][/ROW]
[ROW][C]24[/C][C]-0.318818[/C][C]-2.49[/C][C]0.007756[/C][/ROW]
[ROW][C]25[/C][C]-0.306422[/C][C]-2.3932[/C][C]0.009897[/C][/ROW]
[ROW][C]26[/C][C]-0.269955[/C][C]-2.1084[/C][C]0.019555[/C][/ROW]
[ROW][C]27[/C][C]-0.241171[/C][C]-1.8836[/C][C]0.032194[/C][/ROW]
[ROW][C]28[/C][C]-0.236938[/C][C]-1.8505[/C][C]0.03454[/C][/ROW]
[ROW][C]29[/C][C]-0.275806[/C][C]-2.1541[/C][C]0.017595[/C][/ROW]
[ROW][C]30[/C][C]-0.325721[/C][C]-2.544[/C][C]0.006755[/C][/ROW]
[ROW][C]31[/C][C]-0.350458[/C][C]-2.7372[/C][C]0.004054[/C][/ROW]
[ROW][C]32[/C][C]-0.356762[/C][C]-2.7864[/C][C]0.003547[/C][/ROW]
[ROW][C]33[/C][C]-0.323198[/C][C]-2.5243[/C][C]0.007106[/C][/ROW]
[ROW][C]34[/C][C]-0.259805[/C][C]-2.0291[/C][C]0.023407[/C][/ROW]
[ROW][C]35[/C][C]-0.211302[/C][C]-1.6503[/C][C]0.052009[/C][/ROW]
[ROW][C]36[/C][C]-0.180143[/C][C]-1.407[/C][C]0.082256[/C][/ROW]
[ROW][C]37[/C][C]-0.15675[/C][C]-1.2243[/C][C]0.112782[/C][/ROW]
[ROW][C]38[/C][C]-0.110503[/C][C]-0.8631[/C][C]0.195743[/C][/ROW]
[ROW][C]39[/C][C]-0.048429[/C][C]-0.3782[/C][C]0.353283[/C][/ROW]
[ROW][C]40[/C][C]0.012919[/C][C]0.1009[/C][C]0.459981[/C][/ROW]
[ROW][C]41[/C][C]0.035896[/C][C]0.2804[/C][C]0.390077[/C][/ROW]
[ROW][C]42[/C][C]0.02156[/C][C]0.1684[/C][C]0.433419[/C][/ROW]
[ROW][C]43[/C][C]-0.016848[/C][C]-0.1316[/C][C]0.447871[/C][/ROW]
[ROW][C]44[/C][C]-0.053211[/C][C]-0.4156[/C][C]0.339584[/C][/ROW]
[ROW][C]45[/C][C]-0.049176[/C][C]-0.3841[/C][C]0.351128[/C][/ROW]
[ROW][C]46[/C][C]-0.009544[/C][C]-0.0745[/C][C]0.470411[/C][/ROW]
[ROW][C]47[/C][C]0.008024[/C][C]0.0627[/C][C]0.475117[/C][/ROW]
[ROW][C]48[/C][C]0.004306[/C][C]0.0336[/C][C]0.486641[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62861&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62861&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
10.8489756.63070
20.608984.75636e-06
30.4222273.29770.000815
40.3756062.93360.002358
50.4233643.30660.000793
60.4459433.48290.000462
70.3592062.80550.003366
80.2150751.67980.049057
90.1061310.82890.205194
100.1085670.84790.199893
110.1758521.37340.08732
120.2300931.79710.038636
130.1814961.41750.080708
140.0852470.66580.254025
15-0.014365-0.11220.455518
16-0.079779-0.62310.267773
17-0.116701-0.91150.182819
18-0.144341-1.12730.132006
19-0.177061-1.38290.08587
20-0.225148-1.75850.041842
21-0.27119-2.11810.019126
22-0.308821-2.4120.009445
23-0.325246-2.54030.00682
24-0.318818-2.490.007756
25-0.306422-2.39320.009897
26-0.269955-2.10840.019555
27-0.241171-1.88360.032194
28-0.236938-1.85050.03454
29-0.275806-2.15410.017595
30-0.325721-2.5440.006755
31-0.350458-2.73720.004054
32-0.356762-2.78640.003547
33-0.323198-2.52430.007106
34-0.259805-2.02910.023407
35-0.211302-1.65030.052009
36-0.180143-1.4070.082256
37-0.15675-1.22430.112782
38-0.110503-0.86310.195743
39-0.048429-0.37820.353283
400.0129190.10090.459981
410.0358960.28040.390077
420.021560.16840.433419
43-0.016848-0.13160.447871
44-0.053211-0.41560.339584
45-0.049176-0.38410.351128
46-0.009544-0.07450.470411
470.0080240.06270.475117
480.0043060.03360.486641







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8489756.63070
2-0.400289-3.12640.001355
30.1624751.2690.104636
40.3050932.38290.010155
50.0973110.760.225085
6-0.124597-0.97310.167166
7-0.196909-1.53790.064621
80.0273250.21340.415857
90.0528960.41310.34048
100.127280.99410.162054
11-0.031845-0.24870.402206
120.0165270.12910.448859
13-0.153161-1.19620.118118
140.0945310.73830.231578
15-0.136885-1.06910.144617
16-0.186517-1.45670.075158
17-0.117334-0.91640.181532
180.0059650.04660.481498
190.0625340.48840.313508
20-0.125229-0.97810.165952
21-0.033388-0.26080.397575
22-0.103056-0.80490.212004
230.0514520.40190.344599
24-0.027372-0.21380.415716
25-0.047345-0.36980.356415
260.0891430.69620.244464
27-0.012665-0.09890.460764
280.007490.05850.476771
29-0.179508-1.4020.082992
30-0.029169-0.22780.410276
31-0.041001-0.32020.374945
32-0.10649-0.83170.204407
330.1090740.85190.198802
340.146671.14550.128233
35-0.012911-0.10080.460005
360.0123610.09650.461703
370.0638840.49890.309806
380.0132960.10380.458817
39-0.047177-0.36850.3569
40-0.045704-0.3570.361178
41-0.041856-0.32690.372428
42-0.008839-0.0690.472594
43-0.052927-0.41340.340392
44-0.026061-0.20350.419694
45-0.005799-0.04530.48201
46-0.011821-0.09230.463372
47-0.163869-1.27990.10272
480.0411080.32110.374631

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.848975 & 6.6307 & 0 \tabularnewline
2 & -0.400289 & -3.1264 & 0.001355 \tabularnewline
3 & 0.162475 & 1.269 & 0.104636 \tabularnewline
4 & 0.305093 & 2.3829 & 0.010155 \tabularnewline
5 & 0.097311 & 0.76 & 0.225085 \tabularnewline
6 & -0.124597 & -0.9731 & 0.167166 \tabularnewline
7 & -0.196909 & -1.5379 & 0.064621 \tabularnewline
8 & 0.027325 & 0.2134 & 0.415857 \tabularnewline
9 & 0.052896 & 0.4131 & 0.34048 \tabularnewline
10 & 0.12728 & 0.9941 & 0.162054 \tabularnewline
11 & -0.031845 & -0.2487 & 0.402206 \tabularnewline
12 & 0.016527 & 0.1291 & 0.448859 \tabularnewline
13 & -0.153161 & -1.1962 & 0.118118 \tabularnewline
14 & 0.094531 & 0.7383 & 0.231578 \tabularnewline
15 & -0.136885 & -1.0691 & 0.144617 \tabularnewline
16 & -0.186517 & -1.4567 & 0.075158 \tabularnewline
17 & -0.117334 & -0.9164 & 0.181532 \tabularnewline
18 & 0.005965 & 0.0466 & 0.481498 \tabularnewline
19 & 0.062534 & 0.4884 & 0.313508 \tabularnewline
20 & -0.125229 & -0.9781 & 0.165952 \tabularnewline
21 & -0.033388 & -0.2608 & 0.397575 \tabularnewline
22 & -0.103056 & -0.8049 & 0.212004 \tabularnewline
23 & 0.051452 & 0.4019 & 0.344599 \tabularnewline
24 & -0.027372 & -0.2138 & 0.415716 \tabularnewline
25 & -0.047345 & -0.3698 & 0.356415 \tabularnewline
26 & 0.089143 & 0.6962 & 0.244464 \tabularnewline
27 & -0.012665 & -0.0989 & 0.460764 \tabularnewline
28 & 0.00749 & 0.0585 & 0.476771 \tabularnewline
29 & -0.179508 & -1.402 & 0.082992 \tabularnewline
30 & -0.029169 & -0.2278 & 0.410276 \tabularnewline
31 & -0.041001 & -0.3202 & 0.374945 \tabularnewline
32 & -0.10649 & -0.8317 & 0.204407 \tabularnewline
33 & 0.109074 & 0.8519 & 0.198802 \tabularnewline
34 & 0.14667 & 1.1455 & 0.128233 \tabularnewline
35 & -0.012911 & -0.1008 & 0.460005 \tabularnewline
36 & 0.012361 & 0.0965 & 0.461703 \tabularnewline
37 & 0.063884 & 0.4989 & 0.309806 \tabularnewline
38 & 0.013296 & 0.1038 & 0.458817 \tabularnewline
39 & -0.047177 & -0.3685 & 0.3569 \tabularnewline
40 & -0.045704 & -0.357 & 0.361178 \tabularnewline
41 & -0.041856 & -0.3269 & 0.372428 \tabularnewline
42 & -0.008839 & -0.069 & 0.472594 \tabularnewline
43 & -0.052927 & -0.4134 & 0.340392 \tabularnewline
44 & -0.026061 & -0.2035 & 0.419694 \tabularnewline
45 & -0.005799 & -0.0453 & 0.48201 \tabularnewline
46 & -0.011821 & -0.0923 & 0.463372 \tabularnewline
47 & -0.163869 & -1.2799 & 0.10272 \tabularnewline
48 & 0.041108 & 0.3211 & 0.374631 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62861&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]0.848975[/C][C]6.6307[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.400289[/C][C]-3.1264[/C][C]0.001355[/C][/ROW]
[ROW][C]3[/C][C]0.162475[/C][C]1.269[/C][C]0.104636[/C][/ROW]
[ROW][C]4[/C][C]0.305093[/C][C]2.3829[/C][C]0.010155[/C][/ROW]
[ROW][C]5[/C][C]0.097311[/C][C]0.76[/C][C]0.225085[/C][/ROW]
[ROW][C]6[/C][C]-0.124597[/C][C]-0.9731[/C][C]0.167166[/C][/ROW]
[ROW][C]7[/C][C]-0.196909[/C][C]-1.5379[/C][C]0.064621[/C][/ROW]
[ROW][C]8[/C][C]0.027325[/C][C]0.2134[/C][C]0.415857[/C][/ROW]
[ROW][C]9[/C][C]0.052896[/C][C]0.4131[/C][C]0.34048[/C][/ROW]
[ROW][C]10[/C][C]0.12728[/C][C]0.9941[/C][C]0.162054[/C][/ROW]
[ROW][C]11[/C][C]-0.031845[/C][C]-0.2487[/C][C]0.402206[/C][/ROW]
[ROW][C]12[/C][C]0.016527[/C][C]0.1291[/C][C]0.448859[/C][/ROW]
[ROW][C]13[/C][C]-0.153161[/C][C]-1.1962[/C][C]0.118118[/C][/ROW]
[ROW][C]14[/C][C]0.094531[/C][C]0.7383[/C][C]0.231578[/C][/ROW]
[ROW][C]15[/C][C]-0.136885[/C][C]-1.0691[/C][C]0.144617[/C][/ROW]
[ROW][C]16[/C][C]-0.186517[/C][C]-1.4567[/C][C]0.075158[/C][/ROW]
[ROW][C]17[/C][C]-0.117334[/C][C]-0.9164[/C][C]0.181532[/C][/ROW]
[ROW][C]18[/C][C]0.005965[/C][C]0.0466[/C][C]0.481498[/C][/ROW]
[ROW][C]19[/C][C]0.062534[/C][C]0.4884[/C][C]0.313508[/C][/ROW]
[ROW][C]20[/C][C]-0.125229[/C][C]-0.9781[/C][C]0.165952[/C][/ROW]
[ROW][C]21[/C][C]-0.033388[/C][C]-0.2608[/C][C]0.397575[/C][/ROW]
[ROW][C]22[/C][C]-0.103056[/C][C]-0.8049[/C][C]0.212004[/C][/ROW]
[ROW][C]23[/C][C]0.051452[/C][C]0.4019[/C][C]0.344599[/C][/ROW]
[ROW][C]24[/C][C]-0.027372[/C][C]-0.2138[/C][C]0.415716[/C][/ROW]
[ROW][C]25[/C][C]-0.047345[/C][C]-0.3698[/C][C]0.356415[/C][/ROW]
[ROW][C]26[/C][C]0.089143[/C][C]0.6962[/C][C]0.244464[/C][/ROW]
[ROW][C]27[/C][C]-0.012665[/C][C]-0.0989[/C][C]0.460764[/C][/ROW]
[ROW][C]28[/C][C]0.00749[/C][C]0.0585[/C][C]0.476771[/C][/ROW]
[ROW][C]29[/C][C]-0.179508[/C][C]-1.402[/C][C]0.082992[/C][/ROW]
[ROW][C]30[/C][C]-0.029169[/C][C]-0.2278[/C][C]0.410276[/C][/ROW]
[ROW][C]31[/C][C]-0.041001[/C][C]-0.3202[/C][C]0.374945[/C][/ROW]
[ROW][C]32[/C][C]-0.10649[/C][C]-0.8317[/C][C]0.204407[/C][/ROW]
[ROW][C]33[/C][C]0.109074[/C][C]0.8519[/C][C]0.198802[/C][/ROW]
[ROW][C]34[/C][C]0.14667[/C][C]1.1455[/C][C]0.128233[/C][/ROW]
[ROW][C]35[/C][C]-0.012911[/C][C]-0.1008[/C][C]0.460005[/C][/ROW]
[ROW][C]36[/C][C]0.012361[/C][C]0.0965[/C][C]0.461703[/C][/ROW]
[ROW][C]37[/C][C]0.063884[/C][C]0.4989[/C][C]0.309806[/C][/ROW]
[ROW][C]38[/C][C]0.013296[/C][C]0.1038[/C][C]0.458817[/C][/ROW]
[ROW][C]39[/C][C]-0.047177[/C][C]-0.3685[/C][C]0.3569[/C][/ROW]
[ROW][C]40[/C][C]-0.045704[/C][C]-0.357[/C][C]0.361178[/C][/ROW]
[ROW][C]41[/C][C]-0.041856[/C][C]-0.3269[/C][C]0.372428[/C][/ROW]
[ROW][C]42[/C][C]-0.008839[/C][C]-0.069[/C][C]0.472594[/C][/ROW]
[ROW][C]43[/C][C]-0.052927[/C][C]-0.4134[/C][C]0.340392[/C][/ROW]
[ROW][C]44[/C][C]-0.026061[/C][C]-0.2035[/C][C]0.419694[/C][/ROW]
[ROW][C]45[/C][C]-0.005799[/C][C]-0.0453[/C][C]0.48201[/C][/ROW]
[ROW][C]46[/C][C]-0.011821[/C][C]-0.0923[/C][C]0.463372[/C][/ROW]
[ROW][C]47[/C][C]-0.163869[/C][C]-1.2799[/C][C]0.10272[/C][/ROW]
[ROW][C]48[/C][C]0.041108[/C][C]0.3211[/C][C]0.374631[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62861&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62861&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
10.8489756.63070
2-0.400289-3.12640.001355
30.1624751.2690.104636
40.3050932.38290.010155
50.0973110.760.225085
6-0.124597-0.97310.167166
7-0.196909-1.53790.064621
80.0273250.21340.415857
90.0528960.41310.34048
100.127280.99410.162054
11-0.031845-0.24870.402206
120.0165270.12910.448859
13-0.153161-1.19620.118118
140.0945310.73830.231578
15-0.136885-1.06910.144617
16-0.186517-1.45670.075158
17-0.117334-0.91640.181532
180.0059650.04660.481498
190.0625340.48840.313508
20-0.125229-0.97810.165952
21-0.033388-0.26080.397575
22-0.103056-0.80490.212004
230.0514520.40190.344599
24-0.027372-0.21380.415716
25-0.047345-0.36980.356415
260.0891430.69620.244464
27-0.012665-0.09890.460764
280.007490.05850.476771
29-0.179508-1.4020.082992
30-0.029169-0.22780.410276
31-0.041001-0.32020.374945
32-0.10649-0.83170.204407
330.1090740.85190.198802
340.146671.14550.128233
35-0.012911-0.10080.460005
360.0123610.09650.461703
370.0638840.49890.309806
380.0132960.10380.458817
39-0.047177-0.36850.3569
40-0.045704-0.3570.361178
41-0.041856-0.32690.372428
42-0.008839-0.0690.472594
43-0.052927-0.41340.340392
44-0.026061-0.20350.419694
45-0.005799-0.04530.48201
46-0.011821-0.09230.463372
47-0.163869-1.27990.10272
480.0411080.32110.374631



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