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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 09:31:45 -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/t1259857964trm7u5zkz5cm2yn.htm/, Retrieved Tue, 16 Apr 2024 20:52:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62886, Retrieved Tue, 16 Apr 2024 20:52:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsRW8(14)
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [] [2009-11-26 18:47:15] [023d83ebdf42a2acf423907b4076e8a1]
-   PD    [(Partial) Autocorrelation Function] [Workshop 8: Review] [2009-12-03 16:31:45] [af31b947d6acaef3c71f428c4bb503e9] [Current]
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Dataseries X:
12.610
10.862
52.929
56.902
81.776
87.876
82.103
72.846
60.632
33.521
15.342
7.758
8.668
13.082
38.157
58.263
81.153
88.476
72.329
75.845
61.108
37.665
12.755
2.793
12.935
19.533
33.404
52.074
70.735
69.702
61.656
82.993
53.990
32.283
15.686
2.713
12.842
19.244
48.488
54.464
84.192
84.458
85.793
75.163
68.212
49.233
24.302
5.402
15.058
33.559
70.358
85.934
94.452
129.305
113.882
107.256
94.274
57.842
26.611
14.521




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=62886&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=62886&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62886&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
10.5703663.95160.000127
20.5610083.88680.000156
30.4586373.17750.001299
40.4523533.1340.00147
50.2715091.88110.033018
60.2606891.80610.038587
70.1685851.1680.12429
80.1364770.94550.17456
90.2116541.46640.074533
100.1352820.93730.176658
110.2184061.51320.068398
120.0785930.54450.294306
130.1240440.85940.197196
140.1386570.96060.170772
150.1341430.92940.178675
16-0.006753-0.04680.481438
17-0.026896-0.18630.426482
18-0.073382-0.50840.30675
19-0.100282-0.69480.245272
20-0.144205-0.99910.161383
21-0.195782-1.35640.090656
22-0.236324-1.63730.054054
23-0.262243-1.81690.037742
24-0.326846-2.26450.01405
25-0.226503-1.56930.061578
26-0.29932-2.07370.021746
27-0.292364-2.02560.024195
28-0.22857-1.58360.059929
29-0.105499-0.73090.23419
30-0.148196-1.02670.154846
31-0.13069-0.90540.184876
32-0.135062-0.93570.177046
33-0.161632-1.11980.134182
34-0.09153-0.63410.2645
35-0.150833-1.0450.150628
36-0.148841-1.03120.153807
37-0.191601-1.32750.095319
38-0.135054-0.93570.17706
39-0.184024-1.2750.10423
40-0.105455-0.73060.234284
41-0.140898-0.97620.166937
42-0.090878-0.62960.265965
43-0.048659-0.33710.368749
44-0.019105-0.13240.447625
45-0.011178-0.07740.469295
460.0023980.01660.493408
47-0.004192-0.0290.488476
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.570366 & 3.9516 & 0.000127 \tabularnewline
2 & 0.561008 & 3.8868 & 0.000156 \tabularnewline
3 & 0.458637 & 3.1775 & 0.001299 \tabularnewline
4 & 0.452353 & 3.134 & 0.00147 \tabularnewline
5 & 0.271509 & 1.8811 & 0.033018 \tabularnewline
6 & 0.260689 & 1.8061 & 0.038587 \tabularnewline
7 & 0.168585 & 1.168 & 0.12429 \tabularnewline
8 & 0.136477 & 0.9455 & 0.17456 \tabularnewline
9 & 0.211654 & 1.4664 & 0.074533 \tabularnewline
10 & 0.135282 & 0.9373 & 0.176658 \tabularnewline
11 & 0.218406 & 1.5132 & 0.068398 \tabularnewline
12 & 0.078593 & 0.5445 & 0.294306 \tabularnewline
13 & 0.124044 & 0.8594 & 0.197196 \tabularnewline
14 & 0.138657 & 0.9606 & 0.170772 \tabularnewline
15 & 0.134143 & 0.9294 & 0.178675 \tabularnewline
16 & -0.006753 & -0.0468 & 0.481438 \tabularnewline
17 & -0.026896 & -0.1863 & 0.426482 \tabularnewline
18 & -0.073382 & -0.5084 & 0.30675 \tabularnewline
19 & -0.100282 & -0.6948 & 0.245272 \tabularnewline
20 & -0.144205 & -0.9991 & 0.161383 \tabularnewline
21 & -0.195782 & -1.3564 & 0.090656 \tabularnewline
22 & -0.236324 & -1.6373 & 0.054054 \tabularnewline
23 & -0.262243 & -1.8169 & 0.037742 \tabularnewline
24 & -0.326846 & -2.2645 & 0.01405 \tabularnewline
25 & -0.226503 & -1.5693 & 0.061578 \tabularnewline
26 & -0.29932 & -2.0737 & 0.021746 \tabularnewline
27 & -0.292364 & -2.0256 & 0.024195 \tabularnewline
28 & -0.22857 & -1.5836 & 0.059929 \tabularnewline
29 & -0.105499 & -0.7309 & 0.23419 \tabularnewline
30 & -0.148196 & -1.0267 & 0.154846 \tabularnewline
31 & -0.13069 & -0.9054 & 0.184876 \tabularnewline
32 & -0.135062 & -0.9357 & 0.177046 \tabularnewline
33 & -0.161632 & -1.1198 & 0.134182 \tabularnewline
34 & -0.09153 & -0.6341 & 0.2645 \tabularnewline
35 & -0.150833 & -1.045 & 0.150628 \tabularnewline
36 & -0.148841 & -1.0312 & 0.153807 \tabularnewline
37 & -0.191601 & -1.3275 & 0.095319 \tabularnewline
38 & -0.135054 & -0.9357 & 0.17706 \tabularnewline
39 & -0.184024 & -1.275 & 0.10423 \tabularnewline
40 & -0.105455 & -0.7306 & 0.234284 \tabularnewline
41 & -0.140898 & -0.9762 & 0.166937 \tabularnewline
42 & -0.090878 & -0.6296 & 0.265965 \tabularnewline
43 & -0.048659 & -0.3371 & 0.368749 \tabularnewline
44 & -0.019105 & -0.1324 & 0.447625 \tabularnewline
45 & -0.011178 & -0.0774 & 0.469295 \tabularnewline
46 & 0.002398 & 0.0166 & 0.493408 \tabularnewline
47 & -0.004192 & -0.029 & 0.488476 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62886&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]0.570366[/C][C]3.9516[/C][C]0.000127[/C][/ROW]
[ROW][C]2[/C][C]0.561008[/C][C]3.8868[/C][C]0.000156[/C][/ROW]
[ROW][C]3[/C][C]0.458637[/C][C]3.1775[/C][C]0.001299[/C][/ROW]
[ROW][C]4[/C][C]0.452353[/C][C]3.134[/C][C]0.00147[/C][/ROW]
[ROW][C]5[/C][C]0.271509[/C][C]1.8811[/C][C]0.033018[/C][/ROW]
[ROW][C]6[/C][C]0.260689[/C][C]1.8061[/C][C]0.038587[/C][/ROW]
[ROW][C]7[/C][C]0.168585[/C][C]1.168[/C][C]0.12429[/C][/ROW]
[ROW][C]8[/C][C]0.136477[/C][C]0.9455[/C][C]0.17456[/C][/ROW]
[ROW][C]9[/C][C]0.211654[/C][C]1.4664[/C][C]0.074533[/C][/ROW]
[ROW][C]10[/C][C]0.135282[/C][C]0.9373[/C][C]0.176658[/C][/ROW]
[ROW][C]11[/C][C]0.218406[/C][C]1.5132[/C][C]0.068398[/C][/ROW]
[ROW][C]12[/C][C]0.078593[/C][C]0.5445[/C][C]0.294306[/C][/ROW]
[ROW][C]13[/C][C]0.124044[/C][C]0.8594[/C][C]0.197196[/C][/ROW]
[ROW][C]14[/C][C]0.138657[/C][C]0.9606[/C][C]0.170772[/C][/ROW]
[ROW][C]15[/C][C]0.134143[/C][C]0.9294[/C][C]0.178675[/C][/ROW]
[ROW][C]16[/C][C]-0.006753[/C][C]-0.0468[/C][C]0.481438[/C][/ROW]
[ROW][C]17[/C][C]-0.026896[/C][C]-0.1863[/C][C]0.426482[/C][/ROW]
[ROW][C]18[/C][C]-0.073382[/C][C]-0.5084[/C][C]0.30675[/C][/ROW]
[ROW][C]19[/C][C]-0.100282[/C][C]-0.6948[/C][C]0.245272[/C][/ROW]
[ROW][C]20[/C][C]-0.144205[/C][C]-0.9991[/C][C]0.161383[/C][/ROW]
[ROW][C]21[/C][C]-0.195782[/C][C]-1.3564[/C][C]0.090656[/C][/ROW]
[ROW][C]22[/C][C]-0.236324[/C][C]-1.6373[/C][C]0.054054[/C][/ROW]
[ROW][C]23[/C][C]-0.262243[/C][C]-1.8169[/C][C]0.037742[/C][/ROW]
[ROW][C]24[/C][C]-0.326846[/C][C]-2.2645[/C][C]0.01405[/C][/ROW]
[ROW][C]25[/C][C]-0.226503[/C][C]-1.5693[/C][C]0.061578[/C][/ROW]
[ROW][C]26[/C][C]-0.29932[/C][C]-2.0737[/C][C]0.021746[/C][/ROW]
[ROW][C]27[/C][C]-0.292364[/C][C]-2.0256[/C][C]0.024195[/C][/ROW]
[ROW][C]28[/C][C]-0.22857[/C][C]-1.5836[/C][C]0.059929[/C][/ROW]
[ROW][C]29[/C][C]-0.105499[/C][C]-0.7309[/C][C]0.23419[/C][/ROW]
[ROW][C]30[/C][C]-0.148196[/C][C]-1.0267[/C][C]0.154846[/C][/ROW]
[ROW][C]31[/C][C]-0.13069[/C][C]-0.9054[/C][C]0.184876[/C][/ROW]
[ROW][C]32[/C][C]-0.135062[/C][C]-0.9357[/C][C]0.177046[/C][/ROW]
[ROW][C]33[/C][C]-0.161632[/C][C]-1.1198[/C][C]0.134182[/C][/ROW]
[ROW][C]34[/C][C]-0.09153[/C][C]-0.6341[/C][C]0.2645[/C][/ROW]
[ROW][C]35[/C][C]-0.150833[/C][C]-1.045[/C][C]0.150628[/C][/ROW]
[ROW][C]36[/C][C]-0.148841[/C][C]-1.0312[/C][C]0.153807[/C][/ROW]
[ROW][C]37[/C][C]-0.191601[/C][C]-1.3275[/C][C]0.095319[/C][/ROW]
[ROW][C]38[/C][C]-0.135054[/C][C]-0.9357[/C][C]0.17706[/C][/ROW]
[ROW][C]39[/C][C]-0.184024[/C][C]-1.275[/C][C]0.10423[/C][/ROW]
[ROW][C]40[/C][C]-0.105455[/C][C]-0.7306[/C][C]0.234284[/C][/ROW]
[ROW][C]41[/C][C]-0.140898[/C][C]-0.9762[/C][C]0.166937[/C][/ROW]
[ROW][C]42[/C][C]-0.090878[/C][C]-0.6296[/C][C]0.265965[/C][/ROW]
[ROW][C]43[/C][C]-0.048659[/C][C]-0.3371[/C][C]0.368749[/C][/ROW]
[ROW][C]44[/C][C]-0.019105[/C][C]-0.1324[/C][C]0.447625[/C][/ROW]
[ROW][C]45[/C][C]-0.011178[/C][C]-0.0774[/C][C]0.469295[/C][/ROW]
[ROW][C]46[/C][C]0.002398[/C][C]0.0166[/C][C]0.493408[/C][/ROW]
[ROW][C]47[/C][C]-0.004192[/C][C]-0.029[/C][C]0.488476[/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=62886&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62886&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
10.5703663.95160.000127
20.5610083.88680.000156
30.4586373.17750.001299
40.4523533.1340.00147
50.2715091.88110.033018
60.2606891.80610.038587
70.1685851.1680.12429
80.1364770.94550.17456
90.2116541.46640.074533
100.1352820.93730.176658
110.2184061.51320.068398
120.0785930.54450.294306
130.1240440.85940.197196
140.1386570.96060.170772
150.1341430.92940.178675
16-0.006753-0.04680.481438
17-0.026896-0.18630.426482
18-0.073382-0.50840.30675
19-0.100282-0.69480.245272
20-0.144205-0.99910.161383
21-0.195782-1.35640.090656
22-0.236324-1.63730.054054
23-0.262243-1.81690.037742
24-0.326846-2.26450.01405
25-0.226503-1.56930.061578
26-0.29932-2.07370.021746
27-0.292364-2.02560.024195
28-0.22857-1.58360.059929
29-0.105499-0.73090.23419
30-0.148196-1.02670.154846
31-0.13069-0.90540.184876
32-0.135062-0.93570.177046
33-0.161632-1.11980.134182
34-0.09153-0.63410.2645
35-0.150833-1.0450.150628
36-0.148841-1.03120.153807
37-0.191601-1.32750.095319
38-0.135054-0.93570.17706
39-0.184024-1.2750.10423
40-0.105455-0.73060.234284
41-0.140898-0.97620.166937
42-0.090878-0.62960.265965
43-0.048659-0.33710.368749
44-0.019105-0.13240.447625
45-0.011178-0.07740.469295
460.0023980.01660.493408
47-0.004192-0.0290.488476
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5703663.95160.000127
20.3493362.42030.009672
30.0864160.59870.276091
40.1168740.80970.211047
5-0.171467-1.1880.120347
6-0.014063-0.09740.461396
7-0.043696-0.30270.3817
8-0.020685-0.14330.443323
90.2451041.69810.047979
10-0.045934-0.31820.375841
110.1552981.07590.143666
12-0.210522-1.45850.075602
13-0.061573-0.42660.335791
140.1621161.12320.133475
15-0.054669-0.37880.353268
16-0.089663-0.62120.268703
17-0.141745-0.9820.165502
18-0.104044-0.72080.237252
190.0411960.28540.388277
20-0.100627-0.69720.244531
210.0161050.11160.45581
22-0.114061-0.79020.216639
23-0.107114-0.74210.230819
24-0.186523-1.29230.101225
250.1361250.94310.175176
26-0.021421-0.14840.44132
270.0167950.11640.453926
280.0932880.64630.260577
290.1022260.70820.24111
300.0076190.05280.479061
31-0.067621-0.46850.320778
32-0.058898-0.40810.342524
33-0.042663-0.29560.384413
340.0944650.65450.257965
350.0432650.29980.382831
36-0.082852-0.5740.284318
37-0.006268-0.04340.48277
38-0.036347-0.25180.401128
39-0.110721-0.76710.22339
40-0.004263-0.02950.48828
410.0357550.24770.402706
420.0395090.27370.392735
43-0.042516-0.29460.3848
44-0.080964-0.56090.288725
45-0.030744-0.2130.416114
460.0400060.27720.391421
47-0.021539-0.14920.441001
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.570366 & 3.9516 & 0.000127 \tabularnewline
2 & 0.349336 & 2.4203 & 0.009672 \tabularnewline
3 & 0.086416 & 0.5987 & 0.276091 \tabularnewline
4 & 0.116874 & 0.8097 & 0.211047 \tabularnewline
5 & -0.171467 & -1.188 & 0.120347 \tabularnewline
6 & -0.014063 & -0.0974 & 0.461396 \tabularnewline
7 & -0.043696 & -0.3027 & 0.3817 \tabularnewline
8 & -0.020685 & -0.1433 & 0.443323 \tabularnewline
9 & 0.245104 & 1.6981 & 0.047979 \tabularnewline
10 & -0.045934 & -0.3182 & 0.375841 \tabularnewline
11 & 0.155298 & 1.0759 & 0.143666 \tabularnewline
12 & -0.210522 & -1.4585 & 0.075602 \tabularnewline
13 & -0.061573 & -0.4266 & 0.335791 \tabularnewline
14 & 0.162116 & 1.1232 & 0.133475 \tabularnewline
15 & -0.054669 & -0.3788 & 0.353268 \tabularnewline
16 & -0.089663 & -0.6212 & 0.268703 \tabularnewline
17 & -0.141745 & -0.982 & 0.165502 \tabularnewline
18 & -0.104044 & -0.7208 & 0.237252 \tabularnewline
19 & 0.041196 & 0.2854 & 0.388277 \tabularnewline
20 & -0.100627 & -0.6972 & 0.244531 \tabularnewline
21 & 0.016105 & 0.1116 & 0.45581 \tabularnewline
22 & -0.114061 & -0.7902 & 0.216639 \tabularnewline
23 & -0.107114 & -0.7421 & 0.230819 \tabularnewline
24 & -0.186523 & -1.2923 & 0.101225 \tabularnewline
25 & 0.136125 & 0.9431 & 0.175176 \tabularnewline
26 & -0.021421 & -0.1484 & 0.44132 \tabularnewline
27 & 0.016795 & 0.1164 & 0.453926 \tabularnewline
28 & 0.093288 & 0.6463 & 0.260577 \tabularnewline
29 & 0.102226 & 0.7082 & 0.24111 \tabularnewline
30 & 0.007619 & 0.0528 & 0.479061 \tabularnewline
31 & -0.067621 & -0.4685 & 0.320778 \tabularnewline
32 & -0.058898 & -0.4081 & 0.342524 \tabularnewline
33 & -0.042663 & -0.2956 & 0.384413 \tabularnewline
34 & 0.094465 & 0.6545 & 0.257965 \tabularnewline
35 & 0.043265 & 0.2998 & 0.382831 \tabularnewline
36 & -0.082852 & -0.574 & 0.284318 \tabularnewline
37 & -0.006268 & -0.0434 & 0.48277 \tabularnewline
38 & -0.036347 & -0.2518 & 0.401128 \tabularnewline
39 & -0.110721 & -0.7671 & 0.22339 \tabularnewline
40 & -0.004263 & -0.0295 & 0.48828 \tabularnewline
41 & 0.035755 & 0.2477 & 0.402706 \tabularnewline
42 & 0.039509 & 0.2737 & 0.392735 \tabularnewline
43 & -0.042516 & -0.2946 & 0.3848 \tabularnewline
44 & -0.080964 & -0.5609 & 0.288725 \tabularnewline
45 & -0.030744 & -0.213 & 0.416114 \tabularnewline
46 & 0.040006 & 0.2772 & 0.391421 \tabularnewline
47 & -0.021539 & -0.1492 & 0.441001 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62886&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]0.570366[/C][C]3.9516[/C][C]0.000127[/C][/ROW]
[ROW][C]2[/C][C]0.349336[/C][C]2.4203[/C][C]0.009672[/C][/ROW]
[ROW][C]3[/C][C]0.086416[/C][C]0.5987[/C][C]0.276091[/C][/ROW]
[ROW][C]4[/C][C]0.116874[/C][C]0.8097[/C][C]0.211047[/C][/ROW]
[ROW][C]5[/C][C]-0.171467[/C][C]-1.188[/C][C]0.120347[/C][/ROW]
[ROW][C]6[/C][C]-0.014063[/C][C]-0.0974[/C][C]0.461396[/C][/ROW]
[ROW][C]7[/C][C]-0.043696[/C][C]-0.3027[/C][C]0.3817[/C][/ROW]
[ROW][C]8[/C][C]-0.020685[/C][C]-0.1433[/C][C]0.443323[/C][/ROW]
[ROW][C]9[/C][C]0.245104[/C][C]1.6981[/C][C]0.047979[/C][/ROW]
[ROW][C]10[/C][C]-0.045934[/C][C]-0.3182[/C][C]0.375841[/C][/ROW]
[ROW][C]11[/C][C]0.155298[/C][C]1.0759[/C][C]0.143666[/C][/ROW]
[ROW][C]12[/C][C]-0.210522[/C][C]-1.4585[/C][C]0.075602[/C][/ROW]
[ROW][C]13[/C][C]-0.061573[/C][C]-0.4266[/C][C]0.335791[/C][/ROW]
[ROW][C]14[/C][C]0.162116[/C][C]1.1232[/C][C]0.133475[/C][/ROW]
[ROW][C]15[/C][C]-0.054669[/C][C]-0.3788[/C][C]0.353268[/C][/ROW]
[ROW][C]16[/C][C]-0.089663[/C][C]-0.6212[/C][C]0.268703[/C][/ROW]
[ROW][C]17[/C][C]-0.141745[/C][C]-0.982[/C][C]0.165502[/C][/ROW]
[ROW][C]18[/C][C]-0.104044[/C][C]-0.7208[/C][C]0.237252[/C][/ROW]
[ROW][C]19[/C][C]0.041196[/C][C]0.2854[/C][C]0.388277[/C][/ROW]
[ROW][C]20[/C][C]-0.100627[/C][C]-0.6972[/C][C]0.244531[/C][/ROW]
[ROW][C]21[/C][C]0.016105[/C][C]0.1116[/C][C]0.45581[/C][/ROW]
[ROW][C]22[/C][C]-0.114061[/C][C]-0.7902[/C][C]0.216639[/C][/ROW]
[ROW][C]23[/C][C]-0.107114[/C][C]-0.7421[/C][C]0.230819[/C][/ROW]
[ROW][C]24[/C][C]-0.186523[/C][C]-1.2923[/C][C]0.101225[/C][/ROW]
[ROW][C]25[/C][C]0.136125[/C][C]0.9431[/C][C]0.175176[/C][/ROW]
[ROW][C]26[/C][C]-0.021421[/C][C]-0.1484[/C][C]0.44132[/C][/ROW]
[ROW][C]27[/C][C]0.016795[/C][C]0.1164[/C][C]0.453926[/C][/ROW]
[ROW][C]28[/C][C]0.093288[/C][C]0.6463[/C][C]0.260577[/C][/ROW]
[ROW][C]29[/C][C]0.102226[/C][C]0.7082[/C][C]0.24111[/C][/ROW]
[ROW][C]30[/C][C]0.007619[/C][C]0.0528[/C][C]0.479061[/C][/ROW]
[ROW][C]31[/C][C]-0.067621[/C][C]-0.4685[/C][C]0.320778[/C][/ROW]
[ROW][C]32[/C][C]-0.058898[/C][C]-0.4081[/C][C]0.342524[/C][/ROW]
[ROW][C]33[/C][C]-0.042663[/C][C]-0.2956[/C][C]0.384413[/C][/ROW]
[ROW][C]34[/C][C]0.094465[/C][C]0.6545[/C][C]0.257965[/C][/ROW]
[ROW][C]35[/C][C]0.043265[/C][C]0.2998[/C][C]0.382831[/C][/ROW]
[ROW][C]36[/C][C]-0.082852[/C][C]-0.574[/C][C]0.284318[/C][/ROW]
[ROW][C]37[/C][C]-0.006268[/C][C]-0.0434[/C][C]0.48277[/C][/ROW]
[ROW][C]38[/C][C]-0.036347[/C][C]-0.2518[/C][C]0.401128[/C][/ROW]
[ROW][C]39[/C][C]-0.110721[/C][C]-0.7671[/C][C]0.22339[/C][/ROW]
[ROW][C]40[/C][C]-0.004263[/C][C]-0.0295[/C][C]0.48828[/C][/ROW]
[ROW][C]41[/C][C]0.035755[/C][C]0.2477[/C][C]0.402706[/C][/ROW]
[ROW][C]42[/C][C]0.039509[/C][C]0.2737[/C][C]0.392735[/C][/ROW]
[ROW][C]43[/C][C]-0.042516[/C][C]-0.2946[/C][C]0.3848[/C][/ROW]
[ROW][C]44[/C][C]-0.080964[/C][C]-0.5609[/C][C]0.288725[/C][/ROW]
[ROW][C]45[/C][C]-0.030744[/C][C]-0.213[/C][C]0.416114[/C][/ROW]
[ROW][C]46[/C][C]0.040006[/C][C]0.2772[/C][C]0.391421[/C][/ROW]
[ROW][C]47[/C][C]-0.021539[/C][C]-0.1492[/C][C]0.441001[/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=62886&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62886&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
10.5703663.95160.000127
20.3493362.42030.009672
30.0864160.59870.276091
40.1168740.80970.211047
5-0.171467-1.1880.120347
6-0.014063-0.09740.461396
7-0.043696-0.30270.3817
8-0.020685-0.14330.443323
90.2451041.69810.047979
10-0.045934-0.31820.375841
110.1552981.07590.143666
12-0.210522-1.45850.075602
13-0.061573-0.42660.335791
140.1621161.12320.133475
15-0.054669-0.37880.353268
16-0.089663-0.62120.268703
17-0.141745-0.9820.165502
18-0.104044-0.72080.237252
190.0411960.28540.388277
20-0.100627-0.69720.244531
210.0161050.11160.45581
22-0.114061-0.79020.216639
23-0.107114-0.74210.230819
24-0.186523-1.29230.101225
250.1361250.94310.175176
26-0.021421-0.14840.44132
270.0167950.11640.453926
280.0932880.64630.260577
290.1022260.70820.24111
300.0076190.05280.479061
31-0.067621-0.46850.320778
32-0.058898-0.40810.342524
33-0.042663-0.29560.384413
340.0944650.65450.257965
350.0432650.29980.382831
36-0.082852-0.5740.284318
37-0.006268-0.04340.48277
38-0.036347-0.25180.401128
39-0.110721-0.76710.22339
40-0.004263-0.02950.48828
410.0357550.24770.402706
420.0395090.27370.392735
43-0.042516-0.29460.3848
44-0.080964-0.56090.288725
45-0.030744-0.2130.416114
460.0400060.27720.391421
47-0.021539-0.14920.441001
48NANANA



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