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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 13 Dec 2009 03:07:50 -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/13/t1260698988lsq9fjwrd047sb9.htm/, Retrieved Sun, 28 Apr 2024 07:06:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67187, Retrieved Sun, 28 Apr 2024 07:06:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [] [2009-10-27 11:47:31] [e5e09c53da17fb7444fa9ceb236a5291]
- RMP   [Mean Plot] [] [2009-12-02 08:56:02] [e5e09c53da17fb7444fa9ceb236a5291]
- RMPD      [(Partial) Autocorrelation Function] [] [2009-12-13 10:07:50] [ab2b68d5442f7c9b7e2e9d790849a234] [Current]
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Dataseries X:
2.14
2.45
2.52
2.3
2.2541086
39690
43129
37863
35953
29133
24693
22205
21725
27192
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698

2.06
1.99
2.25
2.26
2.36
2.3
2.19
2.31
2.21
2.21
2.26
2.18
2.21
2.33
2.12
2.08
1.97
2.09
2.11
2.24
2.45
2.68
2.73
2.76
2.83
3.16
3.22
3.22
3.34
3.35
3.42
3.58
3.71
3.68
3.83
3.94
3.88
4.03
4.15
4.32
4.4
4.37
4.14
4.11
4.16
3.98
4.13
3.76
3.66
3.85
4.03
4.31
4.58
4.46
4.41
3.84
2.84
2.66
2.17
1.43
1.47
1.29
1.23
1.09
0.94
0.76
0.67




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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=67187&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]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=67187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67187&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.150315-1.79120.037695
2-0.121051-1.44250.075682
30.0787580.93850.174788
4-0.145475-1.73350.042585
5-0.011174-0.13320.447129
6-0.061946-0.73820.230814
7-0.060237-0.71780.237027
80.035420.42210.336802
90.0151690.18080.428409
10-0.159525-1.9010.029667
110.0634880.75650.225287
120.3656974.35781.3e-05
13-0.09936-1.1840.119193
14-0.075372-0.89820.185311
150.0808980.9640.16834
16-0.131967-1.57260.059022
170.0244460.29130.385622
18-0.053887-0.64210.26091
19-0.089269-1.06380.144622
200.1394261.66150.049414
21-0.044227-0.5270.299501
22-0.170554-2.03240.021989
230.1137531.35550.088702
240.2959533.52670.000284
25-0.09988-1.19020.117975
260.0134690.16050.436359
27-0.060905-0.72580.234588
28-0.098191-1.17010.121965
290.0700340.83460.202686
30-0.114979-1.37010.086403
31-0.014583-0.17380.431145
320.0727650.86710.193675
33-0.042227-0.50320.307804
34-0.102699-1.22380.111526
350.1205751.43680.076486
360.1224121.45870.073427
37-0.030048-0.35810.360413
380.0043910.05230.479174
39-0.027949-0.33310.369793
40-0.065922-0.78560.216718
410.0746670.88980.187549
42-0.110003-1.31080.096014
430.0268230.31960.37486
440.0863331.02880.152666
45-0.095462-1.13760.12861
46-0.006968-0.0830.466973
470.0385130.45890.323493
480.0980821.16880.122226
490.0469870.55990.28821
50-0.041271-0.49180.311809
51-0.068837-0.82030.206712
52-0.015981-0.19040.42462
530.0089670.10690.457526
54-0.051595-0.61480.269827
550.0233130.27780.390781
560.0423350.50450.307354
57-0.05686-0.67760.249573
58-0.022995-0.2740.392236
590.1078191.28480.100476
60-0.062571-0.74560.228566

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.150315 & -1.7912 & 0.037695 \tabularnewline
2 & -0.121051 & -1.4425 & 0.075682 \tabularnewline
3 & 0.078758 & 0.9385 & 0.174788 \tabularnewline
4 & -0.145475 & -1.7335 & 0.042585 \tabularnewline
5 & -0.011174 & -0.1332 & 0.447129 \tabularnewline
6 & -0.061946 & -0.7382 & 0.230814 \tabularnewline
7 & -0.060237 & -0.7178 & 0.237027 \tabularnewline
8 & 0.03542 & 0.4221 & 0.336802 \tabularnewline
9 & 0.015169 & 0.1808 & 0.428409 \tabularnewline
10 & -0.159525 & -1.901 & 0.029667 \tabularnewline
11 & 0.063488 & 0.7565 & 0.225287 \tabularnewline
12 & 0.365697 & 4.3578 & 1.3e-05 \tabularnewline
13 & -0.09936 & -1.184 & 0.119193 \tabularnewline
14 & -0.075372 & -0.8982 & 0.185311 \tabularnewline
15 & 0.080898 & 0.964 & 0.16834 \tabularnewline
16 & -0.131967 & -1.5726 & 0.059022 \tabularnewline
17 & 0.024446 & 0.2913 & 0.385622 \tabularnewline
18 & -0.053887 & -0.6421 & 0.26091 \tabularnewline
19 & -0.089269 & -1.0638 & 0.144622 \tabularnewline
20 & 0.139426 & 1.6615 & 0.049414 \tabularnewline
21 & -0.044227 & -0.527 & 0.299501 \tabularnewline
22 & -0.170554 & -2.0324 & 0.021989 \tabularnewline
23 & 0.113753 & 1.3555 & 0.088702 \tabularnewline
24 & 0.295953 & 3.5267 & 0.000284 \tabularnewline
25 & -0.09988 & -1.1902 & 0.117975 \tabularnewline
26 & 0.013469 & 0.1605 & 0.436359 \tabularnewline
27 & -0.060905 & -0.7258 & 0.234588 \tabularnewline
28 & -0.098191 & -1.1701 & 0.121965 \tabularnewline
29 & 0.070034 & 0.8346 & 0.202686 \tabularnewline
30 & -0.114979 & -1.3701 & 0.086403 \tabularnewline
31 & -0.014583 & -0.1738 & 0.431145 \tabularnewline
32 & 0.072765 & 0.8671 & 0.193675 \tabularnewline
33 & -0.042227 & -0.5032 & 0.307804 \tabularnewline
34 & -0.102699 & -1.2238 & 0.111526 \tabularnewline
35 & 0.120575 & 1.4368 & 0.076486 \tabularnewline
36 & 0.122412 & 1.4587 & 0.073427 \tabularnewline
37 & -0.030048 & -0.3581 & 0.360413 \tabularnewline
38 & 0.004391 & 0.0523 & 0.479174 \tabularnewline
39 & -0.027949 & -0.3331 & 0.369793 \tabularnewline
40 & -0.065922 & -0.7856 & 0.216718 \tabularnewline
41 & 0.074667 & 0.8898 & 0.187549 \tabularnewline
42 & -0.110003 & -1.3108 & 0.096014 \tabularnewline
43 & 0.026823 & 0.3196 & 0.37486 \tabularnewline
44 & 0.086333 & 1.0288 & 0.152666 \tabularnewline
45 & -0.095462 & -1.1376 & 0.12861 \tabularnewline
46 & -0.006968 & -0.083 & 0.466973 \tabularnewline
47 & 0.038513 & 0.4589 & 0.323493 \tabularnewline
48 & 0.098082 & 1.1688 & 0.122226 \tabularnewline
49 & 0.046987 & 0.5599 & 0.28821 \tabularnewline
50 & -0.041271 & -0.4918 & 0.311809 \tabularnewline
51 & -0.068837 & -0.8203 & 0.206712 \tabularnewline
52 & -0.015981 & -0.1904 & 0.42462 \tabularnewline
53 & 0.008967 & 0.1069 & 0.457526 \tabularnewline
54 & -0.051595 & -0.6148 & 0.269827 \tabularnewline
55 & 0.023313 & 0.2778 & 0.390781 \tabularnewline
56 & 0.042335 & 0.5045 & 0.307354 \tabularnewline
57 & -0.05686 & -0.6776 & 0.249573 \tabularnewline
58 & -0.022995 & -0.274 & 0.392236 \tabularnewline
59 & 0.107819 & 1.2848 & 0.100476 \tabularnewline
60 & -0.062571 & -0.7456 & 0.228566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67187&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]-0.150315[/C][C]-1.7912[/C][C]0.037695[/C][/ROW]
[ROW][C]2[/C][C]-0.121051[/C][C]-1.4425[/C][C]0.075682[/C][/ROW]
[ROW][C]3[/C][C]0.078758[/C][C]0.9385[/C][C]0.174788[/C][/ROW]
[ROW][C]4[/C][C]-0.145475[/C][C]-1.7335[/C][C]0.042585[/C][/ROW]
[ROW][C]5[/C][C]-0.011174[/C][C]-0.1332[/C][C]0.447129[/C][/ROW]
[ROW][C]6[/C][C]-0.061946[/C][C]-0.7382[/C][C]0.230814[/C][/ROW]
[ROW][C]7[/C][C]-0.060237[/C][C]-0.7178[/C][C]0.237027[/C][/ROW]
[ROW][C]8[/C][C]0.03542[/C][C]0.4221[/C][C]0.336802[/C][/ROW]
[ROW][C]9[/C][C]0.015169[/C][C]0.1808[/C][C]0.428409[/C][/ROW]
[ROW][C]10[/C][C]-0.159525[/C][C]-1.901[/C][C]0.029667[/C][/ROW]
[ROW][C]11[/C][C]0.063488[/C][C]0.7565[/C][C]0.225287[/C][/ROW]
[ROW][C]12[/C][C]0.365697[/C][C]4.3578[/C][C]1.3e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.09936[/C][C]-1.184[/C][C]0.119193[/C][/ROW]
[ROW][C]14[/C][C]-0.075372[/C][C]-0.8982[/C][C]0.185311[/C][/ROW]
[ROW][C]15[/C][C]0.080898[/C][C]0.964[/C][C]0.16834[/C][/ROW]
[ROW][C]16[/C][C]-0.131967[/C][C]-1.5726[/C][C]0.059022[/C][/ROW]
[ROW][C]17[/C][C]0.024446[/C][C]0.2913[/C][C]0.385622[/C][/ROW]
[ROW][C]18[/C][C]-0.053887[/C][C]-0.6421[/C][C]0.26091[/C][/ROW]
[ROW][C]19[/C][C]-0.089269[/C][C]-1.0638[/C][C]0.144622[/C][/ROW]
[ROW][C]20[/C][C]0.139426[/C][C]1.6615[/C][C]0.049414[/C][/ROW]
[ROW][C]21[/C][C]-0.044227[/C][C]-0.527[/C][C]0.299501[/C][/ROW]
[ROW][C]22[/C][C]-0.170554[/C][C]-2.0324[/C][C]0.021989[/C][/ROW]
[ROW][C]23[/C][C]0.113753[/C][C]1.3555[/C][C]0.088702[/C][/ROW]
[ROW][C]24[/C][C]0.295953[/C][C]3.5267[/C][C]0.000284[/C][/ROW]
[ROW][C]25[/C][C]-0.09988[/C][C]-1.1902[/C][C]0.117975[/C][/ROW]
[ROW][C]26[/C][C]0.013469[/C][C]0.1605[/C][C]0.436359[/C][/ROW]
[ROW][C]27[/C][C]-0.060905[/C][C]-0.7258[/C][C]0.234588[/C][/ROW]
[ROW][C]28[/C][C]-0.098191[/C][C]-1.1701[/C][C]0.121965[/C][/ROW]
[ROW][C]29[/C][C]0.070034[/C][C]0.8346[/C][C]0.202686[/C][/ROW]
[ROW][C]30[/C][C]-0.114979[/C][C]-1.3701[/C][C]0.086403[/C][/ROW]
[ROW][C]31[/C][C]-0.014583[/C][C]-0.1738[/C][C]0.431145[/C][/ROW]
[ROW][C]32[/C][C]0.072765[/C][C]0.8671[/C][C]0.193675[/C][/ROW]
[ROW][C]33[/C][C]-0.042227[/C][C]-0.5032[/C][C]0.307804[/C][/ROW]
[ROW][C]34[/C][C]-0.102699[/C][C]-1.2238[/C][C]0.111526[/C][/ROW]
[ROW][C]35[/C][C]0.120575[/C][C]1.4368[/C][C]0.076486[/C][/ROW]
[ROW][C]36[/C][C]0.122412[/C][C]1.4587[/C][C]0.073427[/C][/ROW]
[ROW][C]37[/C][C]-0.030048[/C][C]-0.3581[/C][C]0.360413[/C][/ROW]
[ROW][C]38[/C][C]0.004391[/C][C]0.0523[/C][C]0.479174[/C][/ROW]
[ROW][C]39[/C][C]-0.027949[/C][C]-0.3331[/C][C]0.369793[/C][/ROW]
[ROW][C]40[/C][C]-0.065922[/C][C]-0.7856[/C][C]0.216718[/C][/ROW]
[ROW][C]41[/C][C]0.074667[/C][C]0.8898[/C][C]0.187549[/C][/ROW]
[ROW][C]42[/C][C]-0.110003[/C][C]-1.3108[/C][C]0.096014[/C][/ROW]
[ROW][C]43[/C][C]0.026823[/C][C]0.3196[/C][C]0.37486[/C][/ROW]
[ROW][C]44[/C][C]0.086333[/C][C]1.0288[/C][C]0.152666[/C][/ROW]
[ROW][C]45[/C][C]-0.095462[/C][C]-1.1376[/C][C]0.12861[/C][/ROW]
[ROW][C]46[/C][C]-0.006968[/C][C]-0.083[/C][C]0.466973[/C][/ROW]
[ROW][C]47[/C][C]0.038513[/C][C]0.4589[/C][C]0.323493[/C][/ROW]
[ROW][C]48[/C][C]0.098082[/C][C]1.1688[/C][C]0.122226[/C][/ROW]
[ROW][C]49[/C][C]0.046987[/C][C]0.5599[/C][C]0.28821[/C][/ROW]
[ROW][C]50[/C][C]-0.041271[/C][C]-0.4918[/C][C]0.311809[/C][/ROW]
[ROW][C]51[/C][C]-0.068837[/C][C]-0.8203[/C][C]0.206712[/C][/ROW]
[ROW][C]52[/C][C]-0.015981[/C][C]-0.1904[/C][C]0.42462[/C][/ROW]
[ROW][C]53[/C][C]0.008967[/C][C]0.1069[/C][C]0.457526[/C][/ROW]
[ROW][C]54[/C][C]-0.051595[/C][C]-0.6148[/C][C]0.269827[/C][/ROW]
[ROW][C]55[/C][C]0.023313[/C][C]0.2778[/C][C]0.390781[/C][/ROW]
[ROW][C]56[/C][C]0.042335[/C][C]0.5045[/C][C]0.307354[/C][/ROW]
[ROW][C]57[/C][C]-0.05686[/C][C]-0.6776[/C][C]0.249573[/C][/ROW]
[ROW][C]58[/C][C]-0.022995[/C][C]-0.274[/C][C]0.392236[/C][/ROW]
[ROW][C]59[/C][C]0.107819[/C][C]1.2848[/C][C]0.100476[/C][/ROW]
[ROW][C]60[/C][C]-0.062571[/C][C]-0.7456[/C][C]0.228566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67187&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
1-0.150315-1.79120.037695
2-0.121051-1.44250.075682
30.0787580.93850.174788
4-0.145475-1.73350.042585
5-0.011174-0.13320.447129
6-0.061946-0.73820.230814
7-0.060237-0.71780.237027
80.035420.42210.336802
90.0151690.18080.428409
10-0.159525-1.9010.029667
110.0634880.75650.225287
120.3656974.35781.3e-05
13-0.09936-1.1840.119193
14-0.075372-0.89820.185311
150.0808980.9640.16834
16-0.131967-1.57260.059022
170.0244460.29130.385622
18-0.053887-0.64210.26091
19-0.089269-1.06380.144622
200.1394261.66150.049414
21-0.044227-0.5270.299501
22-0.170554-2.03240.021989
230.1137531.35550.088702
240.2959533.52670.000284
25-0.09988-1.19020.117975
260.0134690.16050.436359
27-0.060905-0.72580.234588
28-0.098191-1.17010.121965
290.0700340.83460.202686
30-0.114979-1.37010.086403
31-0.014583-0.17380.431145
320.0727650.86710.193675
33-0.042227-0.50320.307804
34-0.102699-1.22380.111526
350.1205751.43680.076486
360.1224121.45870.073427
37-0.030048-0.35810.360413
380.0043910.05230.479174
39-0.027949-0.33310.369793
40-0.065922-0.78560.216718
410.0746670.88980.187549
42-0.110003-1.31080.096014
430.0268230.31960.37486
440.0863331.02880.152666
45-0.095462-1.13760.12861
46-0.006968-0.0830.466973
470.0385130.45890.323493
480.0980821.16880.122226
490.0469870.55990.28821
50-0.041271-0.49180.311809
51-0.068837-0.82030.206712
52-0.015981-0.19040.42462
530.0089670.10690.457526
54-0.051595-0.61480.269827
550.0233130.27780.390781
560.0423350.50450.307354
57-0.05686-0.67760.249573
58-0.022995-0.2740.392236
590.1078191.28480.100476
60-0.062571-0.74560.228566







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.150315-1.79120.037695
2-0.146967-1.75130.041026
30.0374320.44610.328117
4-0.150492-1.79330.037525
5-0.046108-0.54940.291783
6-0.122073-1.45470.073985
7-0.092273-1.09960.136691
8-0.040892-0.48730.313403
9-0.012774-0.15220.439614
10-0.202159-2.4090.008639
11-0.033996-0.40510.343005
120.3410864.06454e-05
130.0357010.42540.335584
14-0.066139-0.78810.215965
150.0409240.48770.313268
16-0.042227-0.50320.307806
170.0166870.19890.421331
18-0.024676-0.2940.384577
19-0.069796-0.83170.203483
200.040550.48320.314846
21-0.003333-0.03970.484189
22-0.109109-1.30020.097821
23-0.033094-0.39440.346954
240.225152.6830.004082
250.029690.35380.362008
260.035860.42730.334898
27-0.109834-1.30880.096354
28-0.032986-0.39310.347429
290.0432230.51510.303656
30-0.013668-0.16290.435424
31-0.025716-0.30640.37986
32-0.101619-1.21090.113967
330.0228250.2720.393013
34-0.002043-0.02430.490305
35-0.007793-0.09290.463072
36-0.041426-0.49360.311159
370.0178950.21320.41572
380.0043880.05230.479187
390.039110.4660.320947
40-0.042252-0.50350.3077
410.027320.32560.372621
420.0152360.18160.428093
430.0535550.63820.262192
44-0.026447-0.31510.376556
45-0.018401-0.21930.413374
460.0447430.53320.297375
47-0.006718-0.080.468156
480.0220250.26250.396674
490.0475870.56710.285783
50-0.018092-0.21560.414806
51-0.012795-0.15250.439517
520.009190.10950.456474
53-0.029394-0.35030.36333
540.0196490.23410.407605
55-0.007352-0.08760.465155
560.0090030.10730.457359
57-0.025399-0.30270.381295
58-0.023269-0.27730.390984
590.0907571.08150.140656
60-0.127793-1.52280.065013

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.150315 & -1.7912 & 0.037695 \tabularnewline
2 & -0.146967 & -1.7513 & 0.041026 \tabularnewline
3 & 0.037432 & 0.4461 & 0.328117 \tabularnewline
4 & -0.150492 & -1.7933 & 0.037525 \tabularnewline
5 & -0.046108 & -0.5494 & 0.291783 \tabularnewline
6 & -0.122073 & -1.4547 & 0.073985 \tabularnewline
7 & -0.092273 & -1.0996 & 0.136691 \tabularnewline
8 & -0.040892 & -0.4873 & 0.313403 \tabularnewline
9 & -0.012774 & -0.1522 & 0.439614 \tabularnewline
10 & -0.202159 & -2.409 & 0.008639 \tabularnewline
11 & -0.033996 & -0.4051 & 0.343005 \tabularnewline
12 & 0.341086 & 4.0645 & 4e-05 \tabularnewline
13 & 0.035701 & 0.4254 & 0.335584 \tabularnewline
14 & -0.066139 & -0.7881 & 0.215965 \tabularnewline
15 & 0.040924 & 0.4877 & 0.313268 \tabularnewline
16 & -0.042227 & -0.5032 & 0.307806 \tabularnewline
17 & 0.016687 & 0.1989 & 0.421331 \tabularnewline
18 & -0.024676 & -0.294 & 0.384577 \tabularnewline
19 & -0.069796 & -0.8317 & 0.203483 \tabularnewline
20 & 0.04055 & 0.4832 & 0.314846 \tabularnewline
21 & -0.003333 & -0.0397 & 0.484189 \tabularnewline
22 & -0.109109 & -1.3002 & 0.097821 \tabularnewline
23 & -0.033094 & -0.3944 & 0.346954 \tabularnewline
24 & 0.22515 & 2.683 & 0.004082 \tabularnewline
25 & 0.02969 & 0.3538 & 0.362008 \tabularnewline
26 & 0.03586 & 0.4273 & 0.334898 \tabularnewline
27 & -0.109834 & -1.3088 & 0.096354 \tabularnewline
28 & -0.032986 & -0.3931 & 0.347429 \tabularnewline
29 & 0.043223 & 0.5151 & 0.303656 \tabularnewline
30 & -0.013668 & -0.1629 & 0.435424 \tabularnewline
31 & -0.025716 & -0.3064 & 0.37986 \tabularnewline
32 & -0.101619 & -1.2109 & 0.113967 \tabularnewline
33 & 0.022825 & 0.272 & 0.393013 \tabularnewline
34 & -0.002043 & -0.0243 & 0.490305 \tabularnewline
35 & -0.007793 & -0.0929 & 0.463072 \tabularnewline
36 & -0.041426 & -0.4936 & 0.311159 \tabularnewline
37 & 0.017895 & 0.2132 & 0.41572 \tabularnewline
38 & 0.004388 & 0.0523 & 0.479187 \tabularnewline
39 & 0.03911 & 0.466 & 0.320947 \tabularnewline
40 & -0.042252 & -0.5035 & 0.3077 \tabularnewline
41 & 0.02732 & 0.3256 & 0.372621 \tabularnewline
42 & 0.015236 & 0.1816 & 0.428093 \tabularnewline
43 & 0.053555 & 0.6382 & 0.262192 \tabularnewline
44 & -0.026447 & -0.3151 & 0.376556 \tabularnewline
45 & -0.018401 & -0.2193 & 0.413374 \tabularnewline
46 & 0.044743 & 0.5332 & 0.297375 \tabularnewline
47 & -0.006718 & -0.08 & 0.468156 \tabularnewline
48 & 0.022025 & 0.2625 & 0.396674 \tabularnewline
49 & 0.047587 & 0.5671 & 0.285783 \tabularnewline
50 & -0.018092 & -0.2156 & 0.414806 \tabularnewline
51 & -0.012795 & -0.1525 & 0.439517 \tabularnewline
52 & 0.00919 & 0.1095 & 0.456474 \tabularnewline
53 & -0.029394 & -0.3503 & 0.36333 \tabularnewline
54 & 0.019649 & 0.2341 & 0.407605 \tabularnewline
55 & -0.007352 & -0.0876 & 0.465155 \tabularnewline
56 & 0.009003 & 0.1073 & 0.457359 \tabularnewline
57 & -0.025399 & -0.3027 & 0.381295 \tabularnewline
58 & -0.023269 & -0.2773 & 0.390984 \tabularnewline
59 & 0.090757 & 1.0815 & 0.140656 \tabularnewline
60 & -0.127793 & -1.5228 & 0.065013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67187&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]-0.150315[/C][C]-1.7912[/C][C]0.037695[/C][/ROW]
[ROW][C]2[/C][C]-0.146967[/C][C]-1.7513[/C][C]0.041026[/C][/ROW]
[ROW][C]3[/C][C]0.037432[/C][C]0.4461[/C][C]0.328117[/C][/ROW]
[ROW][C]4[/C][C]-0.150492[/C][C]-1.7933[/C][C]0.037525[/C][/ROW]
[ROW][C]5[/C][C]-0.046108[/C][C]-0.5494[/C][C]0.291783[/C][/ROW]
[ROW][C]6[/C][C]-0.122073[/C][C]-1.4547[/C][C]0.073985[/C][/ROW]
[ROW][C]7[/C][C]-0.092273[/C][C]-1.0996[/C][C]0.136691[/C][/ROW]
[ROW][C]8[/C][C]-0.040892[/C][C]-0.4873[/C][C]0.313403[/C][/ROW]
[ROW][C]9[/C][C]-0.012774[/C][C]-0.1522[/C][C]0.439614[/C][/ROW]
[ROW][C]10[/C][C]-0.202159[/C][C]-2.409[/C][C]0.008639[/C][/ROW]
[ROW][C]11[/C][C]-0.033996[/C][C]-0.4051[/C][C]0.343005[/C][/ROW]
[ROW][C]12[/C][C]0.341086[/C][C]4.0645[/C][C]4e-05[/C][/ROW]
[ROW][C]13[/C][C]0.035701[/C][C]0.4254[/C][C]0.335584[/C][/ROW]
[ROW][C]14[/C][C]-0.066139[/C][C]-0.7881[/C][C]0.215965[/C][/ROW]
[ROW][C]15[/C][C]0.040924[/C][C]0.4877[/C][C]0.313268[/C][/ROW]
[ROW][C]16[/C][C]-0.042227[/C][C]-0.5032[/C][C]0.307806[/C][/ROW]
[ROW][C]17[/C][C]0.016687[/C][C]0.1989[/C][C]0.421331[/C][/ROW]
[ROW][C]18[/C][C]-0.024676[/C][C]-0.294[/C][C]0.384577[/C][/ROW]
[ROW][C]19[/C][C]-0.069796[/C][C]-0.8317[/C][C]0.203483[/C][/ROW]
[ROW][C]20[/C][C]0.04055[/C][C]0.4832[/C][C]0.314846[/C][/ROW]
[ROW][C]21[/C][C]-0.003333[/C][C]-0.0397[/C][C]0.484189[/C][/ROW]
[ROW][C]22[/C][C]-0.109109[/C][C]-1.3002[/C][C]0.097821[/C][/ROW]
[ROW][C]23[/C][C]-0.033094[/C][C]-0.3944[/C][C]0.346954[/C][/ROW]
[ROW][C]24[/C][C]0.22515[/C][C]2.683[/C][C]0.004082[/C][/ROW]
[ROW][C]25[/C][C]0.02969[/C][C]0.3538[/C][C]0.362008[/C][/ROW]
[ROW][C]26[/C][C]0.03586[/C][C]0.4273[/C][C]0.334898[/C][/ROW]
[ROW][C]27[/C][C]-0.109834[/C][C]-1.3088[/C][C]0.096354[/C][/ROW]
[ROW][C]28[/C][C]-0.032986[/C][C]-0.3931[/C][C]0.347429[/C][/ROW]
[ROW][C]29[/C][C]0.043223[/C][C]0.5151[/C][C]0.303656[/C][/ROW]
[ROW][C]30[/C][C]-0.013668[/C][C]-0.1629[/C][C]0.435424[/C][/ROW]
[ROW][C]31[/C][C]-0.025716[/C][C]-0.3064[/C][C]0.37986[/C][/ROW]
[ROW][C]32[/C][C]-0.101619[/C][C]-1.2109[/C][C]0.113967[/C][/ROW]
[ROW][C]33[/C][C]0.022825[/C][C]0.272[/C][C]0.393013[/C][/ROW]
[ROW][C]34[/C][C]-0.002043[/C][C]-0.0243[/C][C]0.490305[/C][/ROW]
[ROW][C]35[/C][C]-0.007793[/C][C]-0.0929[/C][C]0.463072[/C][/ROW]
[ROW][C]36[/C][C]-0.041426[/C][C]-0.4936[/C][C]0.311159[/C][/ROW]
[ROW][C]37[/C][C]0.017895[/C][C]0.2132[/C][C]0.41572[/C][/ROW]
[ROW][C]38[/C][C]0.004388[/C][C]0.0523[/C][C]0.479187[/C][/ROW]
[ROW][C]39[/C][C]0.03911[/C][C]0.466[/C][C]0.320947[/C][/ROW]
[ROW][C]40[/C][C]-0.042252[/C][C]-0.5035[/C][C]0.3077[/C][/ROW]
[ROW][C]41[/C][C]0.02732[/C][C]0.3256[/C][C]0.372621[/C][/ROW]
[ROW][C]42[/C][C]0.015236[/C][C]0.1816[/C][C]0.428093[/C][/ROW]
[ROW][C]43[/C][C]0.053555[/C][C]0.6382[/C][C]0.262192[/C][/ROW]
[ROW][C]44[/C][C]-0.026447[/C][C]-0.3151[/C][C]0.376556[/C][/ROW]
[ROW][C]45[/C][C]-0.018401[/C][C]-0.2193[/C][C]0.413374[/C][/ROW]
[ROW][C]46[/C][C]0.044743[/C][C]0.5332[/C][C]0.297375[/C][/ROW]
[ROW][C]47[/C][C]-0.006718[/C][C]-0.08[/C][C]0.468156[/C][/ROW]
[ROW][C]48[/C][C]0.022025[/C][C]0.2625[/C][C]0.396674[/C][/ROW]
[ROW][C]49[/C][C]0.047587[/C][C]0.5671[/C][C]0.285783[/C][/ROW]
[ROW][C]50[/C][C]-0.018092[/C][C]-0.2156[/C][C]0.414806[/C][/ROW]
[ROW][C]51[/C][C]-0.012795[/C][C]-0.1525[/C][C]0.439517[/C][/ROW]
[ROW][C]52[/C][C]0.00919[/C][C]0.1095[/C][C]0.456474[/C][/ROW]
[ROW][C]53[/C][C]-0.029394[/C][C]-0.3503[/C][C]0.36333[/C][/ROW]
[ROW][C]54[/C][C]0.019649[/C][C]0.2341[/C][C]0.407605[/C][/ROW]
[ROW][C]55[/C][C]-0.007352[/C][C]-0.0876[/C][C]0.465155[/C][/ROW]
[ROW][C]56[/C][C]0.009003[/C][C]0.1073[/C][C]0.457359[/C][/ROW]
[ROW][C]57[/C][C]-0.025399[/C][C]-0.3027[/C][C]0.381295[/C][/ROW]
[ROW][C]58[/C][C]-0.023269[/C][C]-0.2773[/C][C]0.390984[/C][/ROW]
[ROW][C]59[/C][C]0.090757[/C][C]1.0815[/C][C]0.140656[/C][/ROW]
[ROW][C]60[/C][C]-0.127793[/C][C]-1.5228[/C][C]0.065013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67187&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
1-0.150315-1.79120.037695
2-0.146967-1.75130.041026
30.0374320.44610.328117
4-0.150492-1.79330.037525
5-0.046108-0.54940.291783
6-0.122073-1.45470.073985
7-0.092273-1.09960.136691
8-0.040892-0.48730.313403
9-0.012774-0.15220.439614
10-0.202159-2.4090.008639
11-0.033996-0.40510.343005
120.3410864.06454e-05
130.0357010.42540.335584
14-0.066139-0.78810.215965
150.0409240.48770.313268
16-0.042227-0.50320.307806
170.0166870.19890.421331
18-0.024676-0.2940.384577
19-0.069796-0.83170.203483
200.040550.48320.314846
21-0.003333-0.03970.484189
22-0.109109-1.30020.097821
23-0.033094-0.39440.346954
240.225152.6830.004082
250.029690.35380.362008
260.035860.42730.334898
27-0.109834-1.30880.096354
28-0.032986-0.39310.347429
290.0432230.51510.303656
30-0.013668-0.16290.435424
31-0.025716-0.30640.37986
32-0.101619-1.21090.113967
330.0228250.2720.393013
34-0.002043-0.02430.490305
35-0.007793-0.09290.463072
36-0.041426-0.49360.311159
370.0178950.21320.41572
380.0043880.05230.479187
390.039110.4660.320947
40-0.042252-0.50350.3077
410.027320.32560.372621
420.0152360.18160.428093
430.0535550.63820.262192
44-0.026447-0.31510.376556
45-0.018401-0.21930.413374
460.0447430.53320.297375
47-0.006718-0.080.468156
480.0220250.26250.396674
490.0475870.56710.285783
50-0.018092-0.21560.414806
51-0.012795-0.15250.439517
520.009190.10950.456474
53-0.029394-0.35030.36333
540.0196490.23410.407605
55-0.007352-0.08760.465155
560.0090030.10730.457359
57-0.025399-0.30270.381295
58-0.023269-0.27730.390984
590.0907571.08150.140656
60-0.127793-1.52280.065013



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; 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')