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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 26 Jan 2010 12:04:20 -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/2010/Jan/26/t1264532889afyuzomx1bz6fhu.htm/, Retrieved Thu, 02 May 2024 19:01:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72649, Retrieved Thu, 02 May 2024 19:01:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact137
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [KDGP2W21] [2009-12-16 10:44:20] [8c77cc01643940e7a8195154a75bb218]
-   P     [(Partial) Autocorrelation Function] [KDGP2W21] [2010-01-26 19:04:20] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1
4
-3
-3
0
6
-1
0
-1
1
-4
-1
-1
0
3
0
8
8
8
8
11
13
5
12
13
9
11
7
12
11
10
13
14
10
13
12
13
17
15
6
9
6
11
12
13
11
16
16
19
14
15
12
14
16
13
13
15
12
13
12
15
10
8
11
8
13
9
8
8
6
8
6
12
16




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=72649&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=72649&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72649&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
1-0.404297-3.45430.000461
20.0296810.25360.400262
3-0.043191-0.3690.356588
40.0291670.24920.401951
50.0453750.38770.34969
6-0.095516-0.81610.208552
70.009710.0830.467053
80.0524010.44770.327842
9-0.098494-0.84150.201399
100.0520830.4450.328819
11-0.123162-1.05230.148067
120.2118971.81050.03717
13-0.115834-0.98970.162798
14-0.015835-0.13530.446375
15-0.034328-0.29330.385062
160.0608640.520.302312
17-0.006751-0.05770.477081
18-0.05679-0.48520.31449
190.0407610.34830.364324
200.051680.44160.330058
21-0.115243-0.98460.164027
22-0.016852-0.1440.442957
230.0519920.44420.329099
24-0.037524-0.32060.374713
25-0.008894-0.0760.469818
26-0.044001-0.37590.354025
270.0844490.72150.236443
28-0.006554-0.0560.477748
290.0464570.39690.34629
300.0376380.32160.374347
31-0.028399-0.24260.404481
320.0748890.63990.262136
33-0.008979-0.07670.46953
34-0.151326-1.29290.100056
350.0031860.02720.489177
36-0.016824-0.14370.44305
370.1636771.39850.083105
38-0.217112-1.8550.033817
390.1808441.54510.063319
40-0.125992-1.07650.14263
41-0.006991-0.05970.476268
420.0875250.74780.228487
43-0.064046-0.54720.292952
440.0466630.39870.345642
45-0.031917-0.27270.392928
46-0.086732-0.7410.230522
470.0855810.73120.233497
48-0.095372-0.81490.208901

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.404297 & -3.4543 & 0.000461 \tabularnewline
2 & 0.029681 & 0.2536 & 0.400262 \tabularnewline
3 & -0.043191 & -0.369 & 0.356588 \tabularnewline
4 & 0.029167 & 0.2492 & 0.401951 \tabularnewline
5 & 0.045375 & 0.3877 & 0.34969 \tabularnewline
6 & -0.095516 & -0.8161 & 0.208552 \tabularnewline
7 & 0.00971 & 0.083 & 0.467053 \tabularnewline
8 & 0.052401 & 0.4477 & 0.327842 \tabularnewline
9 & -0.098494 & -0.8415 & 0.201399 \tabularnewline
10 & 0.052083 & 0.445 & 0.328819 \tabularnewline
11 & -0.123162 & -1.0523 & 0.148067 \tabularnewline
12 & 0.211897 & 1.8105 & 0.03717 \tabularnewline
13 & -0.115834 & -0.9897 & 0.162798 \tabularnewline
14 & -0.015835 & -0.1353 & 0.446375 \tabularnewline
15 & -0.034328 & -0.2933 & 0.385062 \tabularnewline
16 & 0.060864 & 0.52 & 0.302312 \tabularnewline
17 & -0.006751 & -0.0577 & 0.477081 \tabularnewline
18 & -0.05679 & -0.4852 & 0.31449 \tabularnewline
19 & 0.040761 & 0.3483 & 0.364324 \tabularnewline
20 & 0.05168 & 0.4416 & 0.330058 \tabularnewline
21 & -0.115243 & -0.9846 & 0.164027 \tabularnewline
22 & -0.016852 & -0.144 & 0.442957 \tabularnewline
23 & 0.051992 & 0.4442 & 0.329099 \tabularnewline
24 & -0.037524 & -0.3206 & 0.374713 \tabularnewline
25 & -0.008894 & -0.076 & 0.469818 \tabularnewline
26 & -0.044001 & -0.3759 & 0.354025 \tabularnewline
27 & 0.084449 & 0.7215 & 0.236443 \tabularnewline
28 & -0.006554 & -0.056 & 0.477748 \tabularnewline
29 & 0.046457 & 0.3969 & 0.34629 \tabularnewline
30 & 0.037638 & 0.3216 & 0.374347 \tabularnewline
31 & -0.028399 & -0.2426 & 0.404481 \tabularnewline
32 & 0.074889 & 0.6399 & 0.262136 \tabularnewline
33 & -0.008979 & -0.0767 & 0.46953 \tabularnewline
34 & -0.151326 & -1.2929 & 0.100056 \tabularnewline
35 & 0.003186 & 0.0272 & 0.489177 \tabularnewline
36 & -0.016824 & -0.1437 & 0.44305 \tabularnewline
37 & 0.163677 & 1.3985 & 0.083105 \tabularnewline
38 & -0.217112 & -1.855 & 0.033817 \tabularnewline
39 & 0.180844 & 1.5451 & 0.063319 \tabularnewline
40 & -0.125992 & -1.0765 & 0.14263 \tabularnewline
41 & -0.006991 & -0.0597 & 0.476268 \tabularnewline
42 & 0.087525 & 0.7478 & 0.228487 \tabularnewline
43 & -0.064046 & -0.5472 & 0.292952 \tabularnewline
44 & 0.046663 & 0.3987 & 0.345642 \tabularnewline
45 & -0.031917 & -0.2727 & 0.392928 \tabularnewline
46 & -0.086732 & -0.741 & 0.230522 \tabularnewline
47 & 0.085581 & 0.7312 & 0.233497 \tabularnewline
48 & -0.095372 & -0.8149 & 0.208901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72649&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]-0.404297[/C][C]-3.4543[/C][C]0.000461[/C][/ROW]
[ROW][C]2[/C][C]0.029681[/C][C]0.2536[/C][C]0.400262[/C][/ROW]
[ROW][C]3[/C][C]-0.043191[/C][C]-0.369[/C][C]0.356588[/C][/ROW]
[ROW][C]4[/C][C]0.029167[/C][C]0.2492[/C][C]0.401951[/C][/ROW]
[ROW][C]5[/C][C]0.045375[/C][C]0.3877[/C][C]0.34969[/C][/ROW]
[ROW][C]6[/C][C]-0.095516[/C][C]-0.8161[/C][C]0.208552[/C][/ROW]
[ROW][C]7[/C][C]0.00971[/C][C]0.083[/C][C]0.467053[/C][/ROW]
[ROW][C]8[/C][C]0.052401[/C][C]0.4477[/C][C]0.327842[/C][/ROW]
[ROW][C]9[/C][C]-0.098494[/C][C]-0.8415[/C][C]0.201399[/C][/ROW]
[ROW][C]10[/C][C]0.052083[/C][C]0.445[/C][C]0.328819[/C][/ROW]
[ROW][C]11[/C][C]-0.123162[/C][C]-1.0523[/C][C]0.148067[/C][/ROW]
[ROW][C]12[/C][C]0.211897[/C][C]1.8105[/C][C]0.03717[/C][/ROW]
[ROW][C]13[/C][C]-0.115834[/C][C]-0.9897[/C][C]0.162798[/C][/ROW]
[ROW][C]14[/C][C]-0.015835[/C][C]-0.1353[/C][C]0.446375[/C][/ROW]
[ROW][C]15[/C][C]-0.034328[/C][C]-0.2933[/C][C]0.385062[/C][/ROW]
[ROW][C]16[/C][C]0.060864[/C][C]0.52[/C][C]0.302312[/C][/ROW]
[ROW][C]17[/C][C]-0.006751[/C][C]-0.0577[/C][C]0.477081[/C][/ROW]
[ROW][C]18[/C][C]-0.05679[/C][C]-0.4852[/C][C]0.31449[/C][/ROW]
[ROW][C]19[/C][C]0.040761[/C][C]0.3483[/C][C]0.364324[/C][/ROW]
[ROW][C]20[/C][C]0.05168[/C][C]0.4416[/C][C]0.330058[/C][/ROW]
[ROW][C]21[/C][C]-0.115243[/C][C]-0.9846[/C][C]0.164027[/C][/ROW]
[ROW][C]22[/C][C]-0.016852[/C][C]-0.144[/C][C]0.442957[/C][/ROW]
[ROW][C]23[/C][C]0.051992[/C][C]0.4442[/C][C]0.329099[/C][/ROW]
[ROW][C]24[/C][C]-0.037524[/C][C]-0.3206[/C][C]0.374713[/C][/ROW]
[ROW][C]25[/C][C]-0.008894[/C][C]-0.076[/C][C]0.469818[/C][/ROW]
[ROW][C]26[/C][C]-0.044001[/C][C]-0.3759[/C][C]0.354025[/C][/ROW]
[ROW][C]27[/C][C]0.084449[/C][C]0.7215[/C][C]0.236443[/C][/ROW]
[ROW][C]28[/C][C]-0.006554[/C][C]-0.056[/C][C]0.477748[/C][/ROW]
[ROW][C]29[/C][C]0.046457[/C][C]0.3969[/C][C]0.34629[/C][/ROW]
[ROW][C]30[/C][C]0.037638[/C][C]0.3216[/C][C]0.374347[/C][/ROW]
[ROW][C]31[/C][C]-0.028399[/C][C]-0.2426[/C][C]0.404481[/C][/ROW]
[ROW][C]32[/C][C]0.074889[/C][C]0.6399[/C][C]0.262136[/C][/ROW]
[ROW][C]33[/C][C]-0.008979[/C][C]-0.0767[/C][C]0.46953[/C][/ROW]
[ROW][C]34[/C][C]-0.151326[/C][C]-1.2929[/C][C]0.100056[/C][/ROW]
[ROW][C]35[/C][C]0.003186[/C][C]0.0272[/C][C]0.489177[/C][/ROW]
[ROW][C]36[/C][C]-0.016824[/C][C]-0.1437[/C][C]0.44305[/C][/ROW]
[ROW][C]37[/C][C]0.163677[/C][C]1.3985[/C][C]0.083105[/C][/ROW]
[ROW][C]38[/C][C]-0.217112[/C][C]-1.855[/C][C]0.033817[/C][/ROW]
[ROW][C]39[/C][C]0.180844[/C][C]1.5451[/C][C]0.063319[/C][/ROW]
[ROW][C]40[/C][C]-0.125992[/C][C]-1.0765[/C][C]0.14263[/C][/ROW]
[ROW][C]41[/C][C]-0.006991[/C][C]-0.0597[/C][C]0.476268[/C][/ROW]
[ROW][C]42[/C][C]0.087525[/C][C]0.7478[/C][C]0.228487[/C][/ROW]
[ROW][C]43[/C][C]-0.064046[/C][C]-0.5472[/C][C]0.292952[/C][/ROW]
[ROW][C]44[/C][C]0.046663[/C][C]0.3987[/C][C]0.345642[/C][/ROW]
[ROW][C]45[/C][C]-0.031917[/C][C]-0.2727[/C][C]0.392928[/C][/ROW]
[ROW][C]46[/C][C]-0.086732[/C][C]-0.741[/C][C]0.230522[/C][/ROW]
[ROW][C]47[/C][C]0.085581[/C][C]0.7312[/C][C]0.233497[/C][/ROW]
[ROW][C]48[/C][C]-0.095372[/C][C]-0.8149[/C][C]0.208901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72649&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72649&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
1-0.404297-3.45430.000461
20.0296810.25360.400262
3-0.043191-0.3690.356588
40.0291670.24920.401951
50.0453750.38770.34969
6-0.095516-0.81610.208552
70.009710.0830.467053
80.0524010.44770.327842
9-0.098494-0.84150.201399
100.0520830.4450.328819
11-0.123162-1.05230.148067
120.2118971.81050.03717
13-0.115834-0.98970.162798
14-0.015835-0.13530.446375
15-0.034328-0.29330.385062
160.0608640.520.302312
17-0.006751-0.05770.477081
18-0.05679-0.48520.31449
190.0407610.34830.364324
200.051680.44160.330058
21-0.115243-0.98460.164027
22-0.016852-0.1440.442957
230.0519920.44420.329099
24-0.037524-0.32060.374713
25-0.008894-0.0760.469818
26-0.044001-0.37590.354025
270.0844490.72150.236443
28-0.006554-0.0560.477748
290.0464570.39690.34629
300.0376380.32160.374347
31-0.028399-0.24260.404481
320.0748890.63990.262136
33-0.008979-0.07670.46953
34-0.151326-1.29290.100056
350.0031860.02720.489177
36-0.016824-0.14370.44305
370.1636771.39850.083105
38-0.217112-1.8550.033817
390.1808441.54510.063319
40-0.125992-1.07650.14263
41-0.006991-0.05970.476268
420.0875250.74780.228487
43-0.064046-0.54720.292952
440.0466630.39870.345642
45-0.031917-0.27270.392928
46-0.086732-0.7410.230522
470.0855810.73120.233497
48-0.095372-0.81490.208901







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.404297-3.45430.000461
2-0.159915-1.36630.088017
3-0.115225-0.98450.164065
4-0.039932-0.34120.366975
50.047280.4040.343712
6-0.065806-0.56230.287834
7-0.06452-0.55130.291568
80.0259360.22160.412624
9-0.093109-0.79550.214444
10-0.030299-0.25890.398229
11-0.145393-1.24220.109062
120.1100530.94030.175084
130.0042450.03630.485582
14-0.045388-0.38780.349649
15-0.088459-0.75580.226102
16-0.004197-0.03590.485746
17-0.015067-0.12870.44896
18-0.058411-0.49910.309618
190.0033210.02840.488721
200.0413720.35350.362372
21-0.078367-0.66960.252622
22-0.132716-1.13390.130268
230.0020910.01790.492898
24-0.109422-0.93490.176461
25-0.073932-0.63170.264785
26-0.087036-0.74360.229742
270.0263550.22520.411235
28-0.010099-0.08630.465738
290.0695340.59410.277142
300.1231431.05210.148104
310.0334640.28590.387877
320.0752150.64260.261237
330.1083880.92610.178731
34-0.111653-0.9540.171624
35-0.21006-1.79480.038416
36-0.152849-1.30590.097836
370.1176441.00520.159072
38-0.101297-0.86550.194805
390.0807710.69010.246158
40-0.031213-0.26670.395233
41-0.107443-0.9180.180823
420.0049760.04250.483101
43-0.018701-0.15980.436747
44-0.013754-0.11750.453387
45-0.064851-0.55410.290607
46-0.117651-1.00520.159058
47-0.047637-0.4070.342595
48-0.112829-0.9640.169111

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.404297 & -3.4543 & 0.000461 \tabularnewline
2 & -0.159915 & -1.3663 & 0.088017 \tabularnewline
3 & -0.115225 & -0.9845 & 0.164065 \tabularnewline
4 & -0.039932 & -0.3412 & 0.366975 \tabularnewline
5 & 0.04728 & 0.404 & 0.343712 \tabularnewline
6 & -0.065806 & -0.5623 & 0.287834 \tabularnewline
7 & -0.06452 & -0.5513 & 0.291568 \tabularnewline
8 & 0.025936 & 0.2216 & 0.412624 \tabularnewline
9 & -0.093109 & -0.7955 & 0.214444 \tabularnewline
10 & -0.030299 & -0.2589 & 0.398229 \tabularnewline
11 & -0.145393 & -1.2422 & 0.109062 \tabularnewline
12 & 0.110053 & 0.9403 & 0.175084 \tabularnewline
13 & 0.004245 & 0.0363 & 0.485582 \tabularnewline
14 & -0.045388 & -0.3878 & 0.349649 \tabularnewline
15 & -0.088459 & -0.7558 & 0.226102 \tabularnewline
16 & -0.004197 & -0.0359 & 0.485746 \tabularnewline
17 & -0.015067 & -0.1287 & 0.44896 \tabularnewline
18 & -0.058411 & -0.4991 & 0.309618 \tabularnewline
19 & 0.003321 & 0.0284 & 0.488721 \tabularnewline
20 & 0.041372 & 0.3535 & 0.362372 \tabularnewline
21 & -0.078367 & -0.6696 & 0.252622 \tabularnewline
22 & -0.132716 & -1.1339 & 0.130268 \tabularnewline
23 & 0.002091 & 0.0179 & 0.492898 \tabularnewline
24 & -0.109422 & -0.9349 & 0.176461 \tabularnewline
25 & -0.073932 & -0.6317 & 0.264785 \tabularnewline
26 & -0.087036 & -0.7436 & 0.229742 \tabularnewline
27 & 0.026355 & 0.2252 & 0.411235 \tabularnewline
28 & -0.010099 & -0.0863 & 0.465738 \tabularnewline
29 & 0.069534 & 0.5941 & 0.277142 \tabularnewline
30 & 0.123143 & 1.0521 & 0.148104 \tabularnewline
31 & 0.033464 & 0.2859 & 0.387877 \tabularnewline
32 & 0.075215 & 0.6426 & 0.261237 \tabularnewline
33 & 0.108388 & 0.9261 & 0.178731 \tabularnewline
34 & -0.111653 & -0.954 & 0.171624 \tabularnewline
35 & -0.21006 & -1.7948 & 0.038416 \tabularnewline
36 & -0.152849 & -1.3059 & 0.097836 \tabularnewline
37 & 0.117644 & 1.0052 & 0.159072 \tabularnewline
38 & -0.101297 & -0.8655 & 0.194805 \tabularnewline
39 & 0.080771 & 0.6901 & 0.246158 \tabularnewline
40 & -0.031213 & -0.2667 & 0.395233 \tabularnewline
41 & -0.107443 & -0.918 & 0.180823 \tabularnewline
42 & 0.004976 & 0.0425 & 0.483101 \tabularnewline
43 & -0.018701 & -0.1598 & 0.436747 \tabularnewline
44 & -0.013754 & -0.1175 & 0.453387 \tabularnewline
45 & -0.064851 & -0.5541 & 0.290607 \tabularnewline
46 & -0.117651 & -1.0052 & 0.159058 \tabularnewline
47 & -0.047637 & -0.407 & 0.342595 \tabularnewline
48 & -0.112829 & -0.964 & 0.169111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72649&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]-0.404297[/C][C]-3.4543[/C][C]0.000461[/C][/ROW]
[ROW][C]2[/C][C]-0.159915[/C][C]-1.3663[/C][C]0.088017[/C][/ROW]
[ROW][C]3[/C][C]-0.115225[/C][C]-0.9845[/C][C]0.164065[/C][/ROW]
[ROW][C]4[/C][C]-0.039932[/C][C]-0.3412[/C][C]0.366975[/C][/ROW]
[ROW][C]5[/C][C]0.04728[/C][C]0.404[/C][C]0.343712[/C][/ROW]
[ROW][C]6[/C][C]-0.065806[/C][C]-0.5623[/C][C]0.287834[/C][/ROW]
[ROW][C]7[/C][C]-0.06452[/C][C]-0.5513[/C][C]0.291568[/C][/ROW]
[ROW][C]8[/C][C]0.025936[/C][C]0.2216[/C][C]0.412624[/C][/ROW]
[ROW][C]9[/C][C]-0.093109[/C][C]-0.7955[/C][C]0.214444[/C][/ROW]
[ROW][C]10[/C][C]-0.030299[/C][C]-0.2589[/C][C]0.398229[/C][/ROW]
[ROW][C]11[/C][C]-0.145393[/C][C]-1.2422[/C][C]0.109062[/C][/ROW]
[ROW][C]12[/C][C]0.110053[/C][C]0.9403[/C][C]0.175084[/C][/ROW]
[ROW][C]13[/C][C]0.004245[/C][C]0.0363[/C][C]0.485582[/C][/ROW]
[ROW][C]14[/C][C]-0.045388[/C][C]-0.3878[/C][C]0.349649[/C][/ROW]
[ROW][C]15[/C][C]-0.088459[/C][C]-0.7558[/C][C]0.226102[/C][/ROW]
[ROW][C]16[/C][C]-0.004197[/C][C]-0.0359[/C][C]0.485746[/C][/ROW]
[ROW][C]17[/C][C]-0.015067[/C][C]-0.1287[/C][C]0.44896[/C][/ROW]
[ROW][C]18[/C][C]-0.058411[/C][C]-0.4991[/C][C]0.309618[/C][/ROW]
[ROW][C]19[/C][C]0.003321[/C][C]0.0284[/C][C]0.488721[/C][/ROW]
[ROW][C]20[/C][C]0.041372[/C][C]0.3535[/C][C]0.362372[/C][/ROW]
[ROW][C]21[/C][C]-0.078367[/C][C]-0.6696[/C][C]0.252622[/C][/ROW]
[ROW][C]22[/C][C]-0.132716[/C][C]-1.1339[/C][C]0.130268[/C][/ROW]
[ROW][C]23[/C][C]0.002091[/C][C]0.0179[/C][C]0.492898[/C][/ROW]
[ROW][C]24[/C][C]-0.109422[/C][C]-0.9349[/C][C]0.176461[/C][/ROW]
[ROW][C]25[/C][C]-0.073932[/C][C]-0.6317[/C][C]0.264785[/C][/ROW]
[ROW][C]26[/C][C]-0.087036[/C][C]-0.7436[/C][C]0.229742[/C][/ROW]
[ROW][C]27[/C][C]0.026355[/C][C]0.2252[/C][C]0.411235[/C][/ROW]
[ROW][C]28[/C][C]-0.010099[/C][C]-0.0863[/C][C]0.465738[/C][/ROW]
[ROW][C]29[/C][C]0.069534[/C][C]0.5941[/C][C]0.277142[/C][/ROW]
[ROW][C]30[/C][C]0.123143[/C][C]1.0521[/C][C]0.148104[/C][/ROW]
[ROW][C]31[/C][C]0.033464[/C][C]0.2859[/C][C]0.387877[/C][/ROW]
[ROW][C]32[/C][C]0.075215[/C][C]0.6426[/C][C]0.261237[/C][/ROW]
[ROW][C]33[/C][C]0.108388[/C][C]0.9261[/C][C]0.178731[/C][/ROW]
[ROW][C]34[/C][C]-0.111653[/C][C]-0.954[/C][C]0.171624[/C][/ROW]
[ROW][C]35[/C][C]-0.21006[/C][C]-1.7948[/C][C]0.038416[/C][/ROW]
[ROW][C]36[/C][C]-0.152849[/C][C]-1.3059[/C][C]0.097836[/C][/ROW]
[ROW][C]37[/C][C]0.117644[/C][C]1.0052[/C][C]0.159072[/C][/ROW]
[ROW][C]38[/C][C]-0.101297[/C][C]-0.8655[/C][C]0.194805[/C][/ROW]
[ROW][C]39[/C][C]0.080771[/C][C]0.6901[/C][C]0.246158[/C][/ROW]
[ROW][C]40[/C][C]-0.031213[/C][C]-0.2667[/C][C]0.395233[/C][/ROW]
[ROW][C]41[/C][C]-0.107443[/C][C]-0.918[/C][C]0.180823[/C][/ROW]
[ROW][C]42[/C][C]0.004976[/C][C]0.0425[/C][C]0.483101[/C][/ROW]
[ROW][C]43[/C][C]-0.018701[/C][C]-0.1598[/C][C]0.436747[/C][/ROW]
[ROW][C]44[/C][C]-0.013754[/C][C]-0.1175[/C][C]0.453387[/C][/ROW]
[ROW][C]45[/C][C]-0.064851[/C][C]-0.5541[/C][C]0.290607[/C][/ROW]
[ROW][C]46[/C][C]-0.117651[/C][C]-1.0052[/C][C]0.159058[/C][/ROW]
[ROW][C]47[/C][C]-0.047637[/C][C]-0.407[/C][C]0.342595[/C][/ROW]
[ROW][C]48[/C][C]-0.112829[/C][C]-0.964[/C][C]0.169111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72649&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72649&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
1-0.404297-3.45430.000461
2-0.159915-1.36630.088017
3-0.115225-0.98450.164065
4-0.039932-0.34120.366975
50.047280.4040.343712
6-0.065806-0.56230.287834
7-0.06452-0.55130.291568
80.0259360.22160.412624
9-0.093109-0.79550.214444
10-0.030299-0.25890.398229
11-0.145393-1.24220.109062
120.1100530.94030.175084
130.0042450.03630.485582
14-0.045388-0.38780.349649
15-0.088459-0.75580.226102
16-0.004197-0.03590.485746
17-0.015067-0.12870.44896
18-0.058411-0.49910.309618
190.0033210.02840.488721
200.0413720.35350.362372
21-0.078367-0.66960.252622
22-0.132716-1.13390.130268
230.0020910.01790.492898
24-0.109422-0.93490.176461
25-0.073932-0.63170.264785
26-0.087036-0.74360.229742
270.0263550.22520.411235
28-0.010099-0.08630.465738
290.0695340.59410.277142
300.1231431.05210.148104
310.0334640.28590.387877
320.0752150.64260.261237
330.1083880.92610.178731
34-0.111653-0.9540.171624
35-0.21006-1.79480.038416
36-0.152849-1.30590.097836
370.1176441.00520.159072
38-0.101297-0.86550.194805
390.0807710.69010.246158
40-0.031213-0.26670.395233
41-0.107443-0.9180.180823
420.0049760.04250.483101
43-0.018701-0.15980.436747
44-0.013754-0.11750.453387
45-0.064851-0.55410.290607
46-0.117651-1.00520.159058
47-0.047637-0.4070.342595
48-0.112829-0.9640.169111



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