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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, 18 Aug 2009 11:26:33 -0600
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/Aug/18/t1250616421bvrf0k4kbwskhx3.htm/, Retrieved Mon, 06 May 2024 13:33:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42856, Retrieved Mon, 06 May 2024 13:33:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Opgave 6 Oefening...] [2008-12-03 17:26:25] [61fbc7ea9bd73829dc055ddb9178936d]
- RMPD    [(Partial) Autocorrelation Function] [dennis volkaerts ...] [2009-08-18 17:26:33] [0d1085ed835696cdd537ad5fa07600ec] [Current]
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Dataseries X:
17.23
17.36
17.39
17.29
17.28
17.4
17.51
17.54
17.64
17.65
17.5
17.37
17.56
17.49
17.61
17.79
17.83
17.56
17.95
18.09
18.38
18.38
18.44
18.84
19.01
19.06
19.06
18.97
18.98
19.41
19.55
19.64
19.71
19.48
19.48
19.41
19.25
19.14
19.21
19.3
19.53
19.14
19.16
19.24
19.38
19.27
19.27
19.07
19.15
19.24
19.36
19.57
19.59
19.36
19.46
19.65
19.46
19.51
19.64
19.64
19.69
19.28
19.67
19.65
19.6
19.53
19.64
19.67
19.81
19.73
19.87
19.97
20.12
19.94
20.31
20.13
20.22
20.38
20.44
20.34
20.14
19.97
19.82
19.98
20.12




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=42856&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=42856&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42856&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
1-0.109993-1.00810.15815
2-0.033361-0.30580.380274
3-0.094641-0.86740.194097
40.0688460.6310.264882
5-0.010905-0.09990.460312
60.1337541.22590.111835
7-0.105842-0.97010.167402
80.1156031.05950.1462
9-0.045295-0.41510.339551
10-0.058564-0.53670.296431
110.0746980.68460.247735
12-0.001048-0.00960.496179
13-0.24828-2.27550.01271
140.0874280.80130.212611
15-0.037997-0.34820.364264
160.0011620.01070.495763
17-0.025059-0.22970.409452
18-0.176619-1.61870.054626
190.0316860.29040.386111
200.2147491.96820.026172
21-0.174991-1.60380.056254
220.0346680.31770.375735
23-0.051981-0.47640.317508
240.0496180.45480.325228
25-0.00887-0.08130.467699
260.0815710.74760.228392
27-0.161204-1.47750.071646
280.2033411.86370.032932
29-0.140883-1.29120.100085
30-0.0089-0.08160.467592
31-0.021381-0.1960.422559
320.0227850.20880.417545
33-0.0603-0.55270.290982
340.1024460.93890.175228
35-0.062159-0.56970.285201
360.0007610.0070.497227
37-0.012455-0.11410.454696
38-0.082308-0.75440.226369
390.1137551.04260.150067
400.0117170.10740.457367
41-0.172226-1.57850.059107
420.0248250.22750.410283
430.0262590.24070.405199
440.0941570.8630.195306
450.0231160.21190.416365
46-0.009372-0.08590.465878
470.0248140.22740.410325
480.0936230.85810.196649

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.109993 & -1.0081 & 0.15815 \tabularnewline
2 & -0.033361 & -0.3058 & 0.380274 \tabularnewline
3 & -0.094641 & -0.8674 & 0.194097 \tabularnewline
4 & 0.068846 & 0.631 & 0.264882 \tabularnewline
5 & -0.010905 & -0.0999 & 0.460312 \tabularnewline
6 & 0.133754 & 1.2259 & 0.111835 \tabularnewline
7 & -0.105842 & -0.9701 & 0.167402 \tabularnewline
8 & 0.115603 & 1.0595 & 0.1462 \tabularnewline
9 & -0.045295 & -0.4151 & 0.339551 \tabularnewline
10 & -0.058564 & -0.5367 & 0.296431 \tabularnewline
11 & 0.074698 & 0.6846 & 0.247735 \tabularnewline
12 & -0.001048 & -0.0096 & 0.496179 \tabularnewline
13 & -0.24828 & -2.2755 & 0.01271 \tabularnewline
14 & 0.087428 & 0.8013 & 0.212611 \tabularnewline
15 & -0.037997 & -0.3482 & 0.364264 \tabularnewline
16 & 0.001162 & 0.0107 & 0.495763 \tabularnewline
17 & -0.025059 & -0.2297 & 0.409452 \tabularnewline
18 & -0.176619 & -1.6187 & 0.054626 \tabularnewline
19 & 0.031686 & 0.2904 & 0.386111 \tabularnewline
20 & 0.214749 & 1.9682 & 0.026172 \tabularnewline
21 & -0.174991 & -1.6038 & 0.056254 \tabularnewline
22 & 0.034668 & 0.3177 & 0.375735 \tabularnewline
23 & -0.051981 & -0.4764 & 0.317508 \tabularnewline
24 & 0.049618 & 0.4548 & 0.325228 \tabularnewline
25 & -0.00887 & -0.0813 & 0.467699 \tabularnewline
26 & 0.081571 & 0.7476 & 0.228392 \tabularnewline
27 & -0.161204 & -1.4775 & 0.071646 \tabularnewline
28 & 0.203341 & 1.8637 & 0.032932 \tabularnewline
29 & -0.140883 & -1.2912 & 0.100085 \tabularnewline
30 & -0.0089 & -0.0816 & 0.467592 \tabularnewline
31 & -0.021381 & -0.196 & 0.422559 \tabularnewline
32 & 0.022785 & 0.2088 & 0.417545 \tabularnewline
33 & -0.0603 & -0.5527 & 0.290982 \tabularnewline
34 & 0.102446 & 0.9389 & 0.175228 \tabularnewline
35 & -0.062159 & -0.5697 & 0.285201 \tabularnewline
36 & 0.000761 & 0.007 & 0.497227 \tabularnewline
37 & -0.012455 & -0.1141 & 0.454696 \tabularnewline
38 & -0.082308 & -0.7544 & 0.226369 \tabularnewline
39 & 0.113755 & 1.0426 & 0.150067 \tabularnewline
40 & 0.011717 & 0.1074 & 0.457367 \tabularnewline
41 & -0.172226 & -1.5785 & 0.059107 \tabularnewline
42 & 0.024825 & 0.2275 & 0.410283 \tabularnewline
43 & 0.026259 & 0.2407 & 0.405199 \tabularnewline
44 & 0.094157 & 0.863 & 0.195306 \tabularnewline
45 & 0.023116 & 0.2119 & 0.416365 \tabularnewline
46 & -0.009372 & -0.0859 & 0.465878 \tabularnewline
47 & 0.024814 & 0.2274 & 0.410325 \tabularnewline
48 & 0.093623 & 0.8581 & 0.196649 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42856&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]-0.109993[/C][C]-1.0081[/C][C]0.15815[/C][/ROW]
[ROW][C]2[/C][C]-0.033361[/C][C]-0.3058[/C][C]0.380274[/C][/ROW]
[ROW][C]3[/C][C]-0.094641[/C][C]-0.8674[/C][C]0.194097[/C][/ROW]
[ROW][C]4[/C][C]0.068846[/C][C]0.631[/C][C]0.264882[/C][/ROW]
[ROW][C]5[/C][C]-0.010905[/C][C]-0.0999[/C][C]0.460312[/C][/ROW]
[ROW][C]6[/C][C]0.133754[/C][C]1.2259[/C][C]0.111835[/C][/ROW]
[ROW][C]7[/C][C]-0.105842[/C][C]-0.9701[/C][C]0.167402[/C][/ROW]
[ROW][C]8[/C][C]0.115603[/C][C]1.0595[/C][C]0.1462[/C][/ROW]
[ROW][C]9[/C][C]-0.045295[/C][C]-0.4151[/C][C]0.339551[/C][/ROW]
[ROW][C]10[/C][C]-0.058564[/C][C]-0.5367[/C][C]0.296431[/C][/ROW]
[ROW][C]11[/C][C]0.074698[/C][C]0.6846[/C][C]0.247735[/C][/ROW]
[ROW][C]12[/C][C]-0.001048[/C][C]-0.0096[/C][C]0.496179[/C][/ROW]
[ROW][C]13[/C][C]-0.24828[/C][C]-2.2755[/C][C]0.01271[/C][/ROW]
[ROW][C]14[/C][C]0.087428[/C][C]0.8013[/C][C]0.212611[/C][/ROW]
[ROW][C]15[/C][C]-0.037997[/C][C]-0.3482[/C][C]0.364264[/C][/ROW]
[ROW][C]16[/C][C]0.001162[/C][C]0.0107[/C][C]0.495763[/C][/ROW]
[ROW][C]17[/C][C]-0.025059[/C][C]-0.2297[/C][C]0.409452[/C][/ROW]
[ROW][C]18[/C][C]-0.176619[/C][C]-1.6187[/C][C]0.054626[/C][/ROW]
[ROW][C]19[/C][C]0.031686[/C][C]0.2904[/C][C]0.386111[/C][/ROW]
[ROW][C]20[/C][C]0.214749[/C][C]1.9682[/C][C]0.026172[/C][/ROW]
[ROW][C]21[/C][C]-0.174991[/C][C]-1.6038[/C][C]0.056254[/C][/ROW]
[ROW][C]22[/C][C]0.034668[/C][C]0.3177[/C][C]0.375735[/C][/ROW]
[ROW][C]23[/C][C]-0.051981[/C][C]-0.4764[/C][C]0.317508[/C][/ROW]
[ROW][C]24[/C][C]0.049618[/C][C]0.4548[/C][C]0.325228[/C][/ROW]
[ROW][C]25[/C][C]-0.00887[/C][C]-0.0813[/C][C]0.467699[/C][/ROW]
[ROW][C]26[/C][C]0.081571[/C][C]0.7476[/C][C]0.228392[/C][/ROW]
[ROW][C]27[/C][C]-0.161204[/C][C]-1.4775[/C][C]0.071646[/C][/ROW]
[ROW][C]28[/C][C]0.203341[/C][C]1.8637[/C][C]0.032932[/C][/ROW]
[ROW][C]29[/C][C]-0.140883[/C][C]-1.2912[/C][C]0.100085[/C][/ROW]
[ROW][C]30[/C][C]-0.0089[/C][C]-0.0816[/C][C]0.467592[/C][/ROW]
[ROW][C]31[/C][C]-0.021381[/C][C]-0.196[/C][C]0.422559[/C][/ROW]
[ROW][C]32[/C][C]0.022785[/C][C]0.2088[/C][C]0.417545[/C][/ROW]
[ROW][C]33[/C][C]-0.0603[/C][C]-0.5527[/C][C]0.290982[/C][/ROW]
[ROW][C]34[/C][C]0.102446[/C][C]0.9389[/C][C]0.175228[/C][/ROW]
[ROW][C]35[/C][C]-0.062159[/C][C]-0.5697[/C][C]0.285201[/C][/ROW]
[ROW][C]36[/C][C]0.000761[/C][C]0.007[/C][C]0.497227[/C][/ROW]
[ROW][C]37[/C][C]-0.012455[/C][C]-0.1141[/C][C]0.454696[/C][/ROW]
[ROW][C]38[/C][C]-0.082308[/C][C]-0.7544[/C][C]0.226369[/C][/ROW]
[ROW][C]39[/C][C]0.113755[/C][C]1.0426[/C][C]0.150067[/C][/ROW]
[ROW][C]40[/C][C]0.011717[/C][C]0.1074[/C][C]0.457367[/C][/ROW]
[ROW][C]41[/C][C]-0.172226[/C][C]-1.5785[/C][C]0.059107[/C][/ROW]
[ROW][C]42[/C][C]0.024825[/C][C]0.2275[/C][C]0.410283[/C][/ROW]
[ROW][C]43[/C][C]0.026259[/C][C]0.2407[/C][C]0.405199[/C][/ROW]
[ROW][C]44[/C][C]0.094157[/C][C]0.863[/C][C]0.195306[/C][/ROW]
[ROW][C]45[/C][C]0.023116[/C][C]0.2119[/C][C]0.416365[/C][/ROW]
[ROW][C]46[/C][C]-0.009372[/C][C]-0.0859[/C][C]0.465878[/C][/ROW]
[ROW][C]47[/C][C]0.024814[/C][C]0.2274[/C][C]0.410325[/C][/ROW]
[ROW][C]48[/C][C]0.093623[/C][C]0.8581[/C][C]0.196649[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42856&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42856&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
1-0.109993-1.00810.15815
2-0.033361-0.30580.380274
3-0.094641-0.86740.194097
40.0688460.6310.264882
5-0.010905-0.09990.460312
60.1337541.22590.111835
7-0.105842-0.97010.167402
80.1156031.05950.1462
9-0.045295-0.41510.339551
10-0.058564-0.53670.296431
110.0746980.68460.247735
12-0.001048-0.00960.496179
13-0.24828-2.27550.01271
140.0874280.80130.212611
15-0.037997-0.34820.364264
160.0011620.01070.495763
17-0.025059-0.22970.409452
18-0.176619-1.61870.054626
190.0316860.29040.386111
200.2147491.96820.026172
21-0.174991-1.60380.056254
220.0346680.31770.375735
23-0.051981-0.47640.317508
240.0496180.45480.325228
25-0.00887-0.08130.467699
260.0815710.74760.228392
27-0.161204-1.47750.071646
280.2033411.86370.032932
29-0.140883-1.29120.100085
30-0.0089-0.08160.467592
31-0.021381-0.1960.422559
320.0227850.20880.417545
33-0.0603-0.55270.290982
340.1024460.93890.175228
35-0.062159-0.56970.285201
360.0007610.0070.497227
37-0.012455-0.11410.454696
38-0.082308-0.75440.226369
390.1137551.04260.150067
400.0117170.10740.457367
41-0.172226-1.57850.059107
420.0248250.22750.410283
430.0262590.24070.405199
440.0941570.8630.195306
450.0231160.21190.416365
46-0.009372-0.08590.465878
470.0248140.22740.410325
480.0936230.85810.196649







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.109993-1.00810.15815
2-0.046016-0.42170.337145
3-0.105031-0.96260.169248
40.045140.41370.340069
5-0.00677-0.0620.475337
60.1311941.20240.116291
7-0.068704-0.62970.265305
80.1109561.01690.156053
9-0.00919-0.08420.466539
10-0.085063-0.77960.218903
110.0915360.83890.201943
12-0.030836-0.28260.389082
13-0.247008-2.26390.01308
140.0342080.31350.377332
15-0.045005-0.41250.340521
16-0.051367-0.47080.319508
17-0.016174-0.14820.441255
18-0.183918-1.68560.047789
190.0386270.3540.362103
200.1894661.73650.043072
21-0.122439-1.12220.132493
220.0385490.35330.36237
23-0.042538-0.38990.348812
240.0841910.77160.221251
25-0.023386-0.21430.415403
260.0052210.04780.480976
27-0.099657-0.91340.18183
280.1093151.00190.159638
29-0.068702-0.62970.265312
30-0.088589-0.81190.209564
31-0.123031-1.12760.13135
320.0244630.22420.41157
330.0333470.30560.380321
34-0.033218-0.30440.38077
350.020120.18440.427069
36-0.085023-0.77920.219013
370.0791190.72510.235191
38-0.011632-0.10660.457676
390.0339660.31130.378171
40-0.053341-0.48890.3131
41-0.089601-0.82120.206925
42-0.018264-0.16740.433733
43-0.009766-0.08950.464447
440.0675830.61940.268663
45-0.014565-0.13350.447063
460.0587570.53850.295821
470.1050530.96280.1692
48-0.007087-0.0650.474183

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.109993 & -1.0081 & 0.15815 \tabularnewline
2 & -0.046016 & -0.4217 & 0.337145 \tabularnewline
3 & -0.105031 & -0.9626 & 0.169248 \tabularnewline
4 & 0.04514 & 0.4137 & 0.340069 \tabularnewline
5 & -0.00677 & -0.062 & 0.475337 \tabularnewline
6 & 0.131194 & 1.2024 & 0.116291 \tabularnewline
7 & -0.068704 & -0.6297 & 0.265305 \tabularnewline
8 & 0.110956 & 1.0169 & 0.156053 \tabularnewline
9 & -0.00919 & -0.0842 & 0.466539 \tabularnewline
10 & -0.085063 & -0.7796 & 0.218903 \tabularnewline
11 & 0.091536 & 0.8389 & 0.201943 \tabularnewline
12 & -0.030836 & -0.2826 & 0.389082 \tabularnewline
13 & -0.247008 & -2.2639 & 0.01308 \tabularnewline
14 & 0.034208 & 0.3135 & 0.377332 \tabularnewline
15 & -0.045005 & -0.4125 & 0.340521 \tabularnewline
16 & -0.051367 & -0.4708 & 0.319508 \tabularnewline
17 & -0.016174 & -0.1482 & 0.441255 \tabularnewline
18 & -0.183918 & -1.6856 & 0.047789 \tabularnewline
19 & 0.038627 & 0.354 & 0.362103 \tabularnewline
20 & 0.189466 & 1.7365 & 0.043072 \tabularnewline
21 & -0.122439 & -1.1222 & 0.132493 \tabularnewline
22 & 0.038549 & 0.3533 & 0.36237 \tabularnewline
23 & -0.042538 & -0.3899 & 0.348812 \tabularnewline
24 & 0.084191 & 0.7716 & 0.221251 \tabularnewline
25 & -0.023386 & -0.2143 & 0.415403 \tabularnewline
26 & 0.005221 & 0.0478 & 0.480976 \tabularnewline
27 & -0.099657 & -0.9134 & 0.18183 \tabularnewline
28 & 0.109315 & 1.0019 & 0.159638 \tabularnewline
29 & -0.068702 & -0.6297 & 0.265312 \tabularnewline
30 & -0.088589 & -0.8119 & 0.209564 \tabularnewline
31 & -0.123031 & -1.1276 & 0.13135 \tabularnewline
32 & 0.024463 & 0.2242 & 0.41157 \tabularnewline
33 & 0.033347 & 0.3056 & 0.380321 \tabularnewline
34 & -0.033218 & -0.3044 & 0.38077 \tabularnewline
35 & 0.02012 & 0.1844 & 0.427069 \tabularnewline
36 & -0.085023 & -0.7792 & 0.219013 \tabularnewline
37 & 0.079119 & 0.7251 & 0.235191 \tabularnewline
38 & -0.011632 & -0.1066 & 0.457676 \tabularnewline
39 & 0.033966 & 0.3113 & 0.378171 \tabularnewline
40 & -0.053341 & -0.4889 & 0.3131 \tabularnewline
41 & -0.089601 & -0.8212 & 0.206925 \tabularnewline
42 & -0.018264 & -0.1674 & 0.433733 \tabularnewline
43 & -0.009766 & -0.0895 & 0.464447 \tabularnewline
44 & 0.067583 & 0.6194 & 0.268663 \tabularnewline
45 & -0.014565 & -0.1335 & 0.447063 \tabularnewline
46 & 0.058757 & 0.5385 & 0.295821 \tabularnewline
47 & 0.105053 & 0.9628 & 0.1692 \tabularnewline
48 & -0.007087 & -0.065 & 0.474183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42856&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]-0.109993[/C][C]-1.0081[/C][C]0.15815[/C][/ROW]
[ROW][C]2[/C][C]-0.046016[/C][C]-0.4217[/C][C]0.337145[/C][/ROW]
[ROW][C]3[/C][C]-0.105031[/C][C]-0.9626[/C][C]0.169248[/C][/ROW]
[ROW][C]4[/C][C]0.04514[/C][C]0.4137[/C][C]0.340069[/C][/ROW]
[ROW][C]5[/C][C]-0.00677[/C][C]-0.062[/C][C]0.475337[/C][/ROW]
[ROW][C]6[/C][C]0.131194[/C][C]1.2024[/C][C]0.116291[/C][/ROW]
[ROW][C]7[/C][C]-0.068704[/C][C]-0.6297[/C][C]0.265305[/C][/ROW]
[ROW][C]8[/C][C]0.110956[/C][C]1.0169[/C][C]0.156053[/C][/ROW]
[ROW][C]9[/C][C]-0.00919[/C][C]-0.0842[/C][C]0.466539[/C][/ROW]
[ROW][C]10[/C][C]-0.085063[/C][C]-0.7796[/C][C]0.218903[/C][/ROW]
[ROW][C]11[/C][C]0.091536[/C][C]0.8389[/C][C]0.201943[/C][/ROW]
[ROW][C]12[/C][C]-0.030836[/C][C]-0.2826[/C][C]0.389082[/C][/ROW]
[ROW][C]13[/C][C]-0.247008[/C][C]-2.2639[/C][C]0.01308[/C][/ROW]
[ROW][C]14[/C][C]0.034208[/C][C]0.3135[/C][C]0.377332[/C][/ROW]
[ROW][C]15[/C][C]-0.045005[/C][C]-0.4125[/C][C]0.340521[/C][/ROW]
[ROW][C]16[/C][C]-0.051367[/C][C]-0.4708[/C][C]0.319508[/C][/ROW]
[ROW][C]17[/C][C]-0.016174[/C][C]-0.1482[/C][C]0.441255[/C][/ROW]
[ROW][C]18[/C][C]-0.183918[/C][C]-1.6856[/C][C]0.047789[/C][/ROW]
[ROW][C]19[/C][C]0.038627[/C][C]0.354[/C][C]0.362103[/C][/ROW]
[ROW][C]20[/C][C]0.189466[/C][C]1.7365[/C][C]0.043072[/C][/ROW]
[ROW][C]21[/C][C]-0.122439[/C][C]-1.1222[/C][C]0.132493[/C][/ROW]
[ROW][C]22[/C][C]0.038549[/C][C]0.3533[/C][C]0.36237[/C][/ROW]
[ROW][C]23[/C][C]-0.042538[/C][C]-0.3899[/C][C]0.348812[/C][/ROW]
[ROW][C]24[/C][C]0.084191[/C][C]0.7716[/C][C]0.221251[/C][/ROW]
[ROW][C]25[/C][C]-0.023386[/C][C]-0.2143[/C][C]0.415403[/C][/ROW]
[ROW][C]26[/C][C]0.005221[/C][C]0.0478[/C][C]0.480976[/C][/ROW]
[ROW][C]27[/C][C]-0.099657[/C][C]-0.9134[/C][C]0.18183[/C][/ROW]
[ROW][C]28[/C][C]0.109315[/C][C]1.0019[/C][C]0.159638[/C][/ROW]
[ROW][C]29[/C][C]-0.068702[/C][C]-0.6297[/C][C]0.265312[/C][/ROW]
[ROW][C]30[/C][C]-0.088589[/C][C]-0.8119[/C][C]0.209564[/C][/ROW]
[ROW][C]31[/C][C]-0.123031[/C][C]-1.1276[/C][C]0.13135[/C][/ROW]
[ROW][C]32[/C][C]0.024463[/C][C]0.2242[/C][C]0.41157[/C][/ROW]
[ROW][C]33[/C][C]0.033347[/C][C]0.3056[/C][C]0.380321[/C][/ROW]
[ROW][C]34[/C][C]-0.033218[/C][C]-0.3044[/C][C]0.38077[/C][/ROW]
[ROW][C]35[/C][C]0.02012[/C][C]0.1844[/C][C]0.427069[/C][/ROW]
[ROW][C]36[/C][C]-0.085023[/C][C]-0.7792[/C][C]0.219013[/C][/ROW]
[ROW][C]37[/C][C]0.079119[/C][C]0.7251[/C][C]0.235191[/C][/ROW]
[ROW][C]38[/C][C]-0.011632[/C][C]-0.1066[/C][C]0.457676[/C][/ROW]
[ROW][C]39[/C][C]0.033966[/C][C]0.3113[/C][C]0.378171[/C][/ROW]
[ROW][C]40[/C][C]-0.053341[/C][C]-0.4889[/C][C]0.3131[/C][/ROW]
[ROW][C]41[/C][C]-0.089601[/C][C]-0.8212[/C][C]0.206925[/C][/ROW]
[ROW][C]42[/C][C]-0.018264[/C][C]-0.1674[/C][C]0.433733[/C][/ROW]
[ROW][C]43[/C][C]-0.009766[/C][C]-0.0895[/C][C]0.464447[/C][/ROW]
[ROW][C]44[/C][C]0.067583[/C][C]0.6194[/C][C]0.268663[/C][/ROW]
[ROW][C]45[/C][C]-0.014565[/C][C]-0.1335[/C][C]0.447063[/C][/ROW]
[ROW][C]46[/C][C]0.058757[/C][C]0.5385[/C][C]0.295821[/C][/ROW]
[ROW][C]47[/C][C]0.105053[/C][C]0.9628[/C][C]0.1692[/C][/ROW]
[ROW][C]48[/C][C]-0.007087[/C][C]-0.065[/C][C]0.474183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42856&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42856&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
1-0.109993-1.00810.15815
2-0.046016-0.42170.337145
3-0.105031-0.96260.169248
40.045140.41370.340069
5-0.00677-0.0620.475337
60.1311941.20240.116291
7-0.068704-0.62970.265305
80.1109561.01690.156053
9-0.00919-0.08420.466539
10-0.085063-0.77960.218903
110.0915360.83890.201943
12-0.030836-0.28260.389082
13-0.247008-2.26390.01308
140.0342080.31350.377332
15-0.045005-0.41250.340521
16-0.051367-0.47080.319508
17-0.016174-0.14820.441255
18-0.183918-1.68560.047789
190.0386270.3540.362103
200.1894661.73650.043072
21-0.122439-1.12220.132493
220.0385490.35330.36237
23-0.042538-0.38990.348812
240.0841910.77160.221251
25-0.023386-0.21430.415403
260.0052210.04780.480976
27-0.099657-0.91340.18183
280.1093151.00190.159638
29-0.068702-0.62970.265312
30-0.088589-0.81190.209564
31-0.123031-1.12760.13135
320.0244630.22420.41157
330.0333470.30560.380321
34-0.033218-0.30440.38077
350.020120.18440.427069
36-0.085023-0.77920.219013
370.0791190.72510.235191
38-0.011632-0.10660.457676
390.0339660.31130.378171
40-0.053341-0.48890.3131
41-0.089601-0.82120.206925
42-0.018264-0.16740.433733
43-0.009766-0.08950.464447
440.0675830.61940.268663
45-0.014565-0.13350.447063
460.0587570.53850.295821
470.1050530.96280.1692
48-0.007087-0.0650.474183



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')