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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 computationWed, 30 Dec 2009 15:26:22 -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/30/t1262212037hcv894ufi4piylu.htm/, Retrieved Mon, 29 Apr 2024 05:19:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71384, Retrieved Mon, 29 Apr 2024 05:19:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [acf d=D=0] [2009-12-30 22:25:00] [bd8e774728cf1f2f4e6868fd314defe3]
-   P     [(Partial) Autocorrelation Function] [acf wagens D=0 d=1] [2009-12-30 22:26:22] [a315839f8c359622c3a1e6ed387dd5cd] [Current]
-   P       [(Partial) Autocorrelation Function] [acf d=D=1] [2009-12-30 22:27:55] [bd8e774728cf1f2f4e6868fd314defe3]
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Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971




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=71384&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=71384&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71384&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
1-0.364807-2.80210.003428
2-0.001194-0.00920.496357
3-0.011172-0.08580.465953
4-0.062382-0.47920.316797
50.1424491.09420.139163
6-0.365199-2.80510.0034
70.0818690.62880.265938
80.0080530.06190.475444
9-0.024218-0.1860.426534
10-0.031576-0.24250.404603
11-0.260959-2.00450.024809
120.7726625.93490
13-0.270242-2.07580.021141
140.0027230.02090.491691
15-0.011527-0.08850.464872
16-0.051146-0.39290.347918
170.1110470.8530.198563
18-0.288983-2.21970.015147
190.0759560.58340.280915
200.0117550.09030.464179
21-0.024321-0.18680.426225
22-0.032223-0.24750.402685
23-0.194894-1.4970.069861
240.5403994.15095.4e-05
25-0.160727-1.23460.110944
26-0.023688-0.1820.428122
270.033360.25620.399327
28-0.082743-0.63560.263759
290.1097510.8430.201313
30-0.207391-1.5930.058252
310.0474760.36470.358331
320.0147660.11340.455042
33-0.036457-0.280.390216
34-0.003118-0.02390.490488
35-0.124707-0.95790.171012
360.3203012.46030.008415
37-0.069365-0.53280.298086
38-0.033067-0.2540.400193
390.0446370.34290.366461
40-0.06939-0.5330.298019
410.0578150.44410.329302
42-0.1019-0.78270.218465
430.0261070.20050.420877
44-0.008462-0.0650.474198
450.0093480.07180.471499
46-0.015522-0.11920.452751
47-0.055077-0.42310.336898
480.137121.05320.148263
49-0.04269-0.32790.372072
50-0.002649-0.02030.491917
510.0164480.12630.449946
52-0.043816-0.33660.368822
530.0337980.25960.398036
54-0.017634-0.13540.44636
55-0.013091-0.10060.460121
560.0111150.08540.466125
57-0.000749-0.00580.497715
58-0.001873-0.01440.494286
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.364807 & -2.8021 & 0.003428 \tabularnewline
2 & -0.001194 & -0.0092 & 0.496357 \tabularnewline
3 & -0.011172 & -0.0858 & 0.465953 \tabularnewline
4 & -0.062382 & -0.4792 & 0.316797 \tabularnewline
5 & 0.142449 & 1.0942 & 0.139163 \tabularnewline
6 & -0.365199 & -2.8051 & 0.0034 \tabularnewline
7 & 0.081869 & 0.6288 & 0.265938 \tabularnewline
8 & 0.008053 & 0.0619 & 0.475444 \tabularnewline
9 & -0.024218 & -0.186 & 0.426534 \tabularnewline
10 & -0.031576 & -0.2425 & 0.404603 \tabularnewline
11 & -0.260959 & -2.0045 & 0.024809 \tabularnewline
12 & 0.772662 & 5.9349 & 0 \tabularnewline
13 & -0.270242 & -2.0758 & 0.021141 \tabularnewline
14 & 0.002723 & 0.0209 & 0.491691 \tabularnewline
15 & -0.011527 & -0.0885 & 0.464872 \tabularnewline
16 & -0.051146 & -0.3929 & 0.347918 \tabularnewline
17 & 0.111047 & 0.853 & 0.198563 \tabularnewline
18 & -0.288983 & -2.2197 & 0.015147 \tabularnewline
19 & 0.075956 & 0.5834 & 0.280915 \tabularnewline
20 & 0.011755 & 0.0903 & 0.464179 \tabularnewline
21 & -0.024321 & -0.1868 & 0.426225 \tabularnewline
22 & -0.032223 & -0.2475 & 0.402685 \tabularnewline
23 & -0.194894 & -1.497 & 0.069861 \tabularnewline
24 & 0.540399 & 4.1509 & 5.4e-05 \tabularnewline
25 & -0.160727 & -1.2346 & 0.110944 \tabularnewline
26 & -0.023688 & -0.182 & 0.428122 \tabularnewline
27 & 0.03336 & 0.2562 & 0.399327 \tabularnewline
28 & -0.082743 & -0.6356 & 0.263759 \tabularnewline
29 & 0.109751 & 0.843 & 0.201313 \tabularnewline
30 & -0.207391 & -1.593 & 0.058252 \tabularnewline
31 & 0.047476 & 0.3647 & 0.358331 \tabularnewline
32 & 0.014766 & 0.1134 & 0.455042 \tabularnewline
33 & -0.036457 & -0.28 & 0.390216 \tabularnewline
34 & -0.003118 & -0.0239 & 0.490488 \tabularnewline
35 & -0.124707 & -0.9579 & 0.171012 \tabularnewline
36 & 0.320301 & 2.4603 & 0.008415 \tabularnewline
37 & -0.069365 & -0.5328 & 0.298086 \tabularnewline
38 & -0.033067 & -0.254 & 0.400193 \tabularnewline
39 & 0.044637 & 0.3429 & 0.366461 \tabularnewline
40 & -0.06939 & -0.533 & 0.298019 \tabularnewline
41 & 0.057815 & 0.4441 & 0.329302 \tabularnewline
42 & -0.1019 & -0.7827 & 0.218465 \tabularnewline
43 & 0.026107 & 0.2005 & 0.420877 \tabularnewline
44 & -0.008462 & -0.065 & 0.474198 \tabularnewline
45 & 0.009348 & 0.0718 & 0.471499 \tabularnewline
46 & -0.015522 & -0.1192 & 0.452751 \tabularnewline
47 & -0.055077 & -0.4231 & 0.336898 \tabularnewline
48 & 0.13712 & 1.0532 & 0.148263 \tabularnewline
49 & -0.04269 & -0.3279 & 0.372072 \tabularnewline
50 & -0.002649 & -0.0203 & 0.491917 \tabularnewline
51 & 0.016448 & 0.1263 & 0.449946 \tabularnewline
52 & -0.043816 & -0.3366 & 0.368822 \tabularnewline
53 & 0.033798 & 0.2596 & 0.398036 \tabularnewline
54 & -0.017634 & -0.1354 & 0.44636 \tabularnewline
55 & -0.013091 & -0.1006 & 0.460121 \tabularnewline
56 & 0.011115 & 0.0854 & 0.466125 \tabularnewline
57 & -0.000749 & -0.0058 & 0.497715 \tabularnewline
58 & -0.001873 & -0.0144 & 0.494286 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71384&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]-0.364807[/C][C]-2.8021[/C][C]0.003428[/C][/ROW]
[ROW][C]2[/C][C]-0.001194[/C][C]-0.0092[/C][C]0.496357[/C][/ROW]
[ROW][C]3[/C][C]-0.011172[/C][C]-0.0858[/C][C]0.465953[/C][/ROW]
[ROW][C]4[/C][C]-0.062382[/C][C]-0.4792[/C][C]0.316797[/C][/ROW]
[ROW][C]5[/C][C]0.142449[/C][C]1.0942[/C][C]0.139163[/C][/ROW]
[ROW][C]6[/C][C]-0.365199[/C][C]-2.8051[/C][C]0.0034[/C][/ROW]
[ROW][C]7[/C][C]0.081869[/C][C]0.6288[/C][C]0.265938[/C][/ROW]
[ROW][C]8[/C][C]0.008053[/C][C]0.0619[/C][C]0.475444[/C][/ROW]
[ROW][C]9[/C][C]-0.024218[/C][C]-0.186[/C][C]0.426534[/C][/ROW]
[ROW][C]10[/C][C]-0.031576[/C][C]-0.2425[/C][C]0.404603[/C][/ROW]
[ROW][C]11[/C][C]-0.260959[/C][C]-2.0045[/C][C]0.024809[/C][/ROW]
[ROW][C]12[/C][C]0.772662[/C][C]5.9349[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.270242[/C][C]-2.0758[/C][C]0.021141[/C][/ROW]
[ROW][C]14[/C][C]0.002723[/C][C]0.0209[/C][C]0.491691[/C][/ROW]
[ROW][C]15[/C][C]-0.011527[/C][C]-0.0885[/C][C]0.464872[/C][/ROW]
[ROW][C]16[/C][C]-0.051146[/C][C]-0.3929[/C][C]0.347918[/C][/ROW]
[ROW][C]17[/C][C]0.111047[/C][C]0.853[/C][C]0.198563[/C][/ROW]
[ROW][C]18[/C][C]-0.288983[/C][C]-2.2197[/C][C]0.015147[/C][/ROW]
[ROW][C]19[/C][C]0.075956[/C][C]0.5834[/C][C]0.280915[/C][/ROW]
[ROW][C]20[/C][C]0.011755[/C][C]0.0903[/C][C]0.464179[/C][/ROW]
[ROW][C]21[/C][C]-0.024321[/C][C]-0.1868[/C][C]0.426225[/C][/ROW]
[ROW][C]22[/C][C]-0.032223[/C][C]-0.2475[/C][C]0.402685[/C][/ROW]
[ROW][C]23[/C][C]-0.194894[/C][C]-1.497[/C][C]0.069861[/C][/ROW]
[ROW][C]24[/C][C]0.540399[/C][C]4.1509[/C][C]5.4e-05[/C][/ROW]
[ROW][C]25[/C][C]-0.160727[/C][C]-1.2346[/C][C]0.110944[/C][/ROW]
[ROW][C]26[/C][C]-0.023688[/C][C]-0.182[/C][C]0.428122[/C][/ROW]
[ROW][C]27[/C][C]0.03336[/C][C]0.2562[/C][C]0.399327[/C][/ROW]
[ROW][C]28[/C][C]-0.082743[/C][C]-0.6356[/C][C]0.263759[/C][/ROW]
[ROW][C]29[/C][C]0.109751[/C][C]0.843[/C][C]0.201313[/C][/ROW]
[ROW][C]30[/C][C]-0.207391[/C][C]-1.593[/C][C]0.058252[/C][/ROW]
[ROW][C]31[/C][C]0.047476[/C][C]0.3647[/C][C]0.358331[/C][/ROW]
[ROW][C]32[/C][C]0.014766[/C][C]0.1134[/C][C]0.455042[/C][/ROW]
[ROW][C]33[/C][C]-0.036457[/C][C]-0.28[/C][C]0.390216[/C][/ROW]
[ROW][C]34[/C][C]-0.003118[/C][C]-0.0239[/C][C]0.490488[/C][/ROW]
[ROW][C]35[/C][C]-0.124707[/C][C]-0.9579[/C][C]0.171012[/C][/ROW]
[ROW][C]36[/C][C]0.320301[/C][C]2.4603[/C][C]0.008415[/C][/ROW]
[ROW][C]37[/C][C]-0.069365[/C][C]-0.5328[/C][C]0.298086[/C][/ROW]
[ROW][C]38[/C][C]-0.033067[/C][C]-0.254[/C][C]0.400193[/C][/ROW]
[ROW][C]39[/C][C]0.044637[/C][C]0.3429[/C][C]0.366461[/C][/ROW]
[ROW][C]40[/C][C]-0.06939[/C][C]-0.533[/C][C]0.298019[/C][/ROW]
[ROW][C]41[/C][C]0.057815[/C][C]0.4441[/C][C]0.329302[/C][/ROW]
[ROW][C]42[/C][C]-0.1019[/C][C]-0.7827[/C][C]0.218465[/C][/ROW]
[ROW][C]43[/C][C]0.026107[/C][C]0.2005[/C][C]0.420877[/C][/ROW]
[ROW][C]44[/C][C]-0.008462[/C][C]-0.065[/C][C]0.474198[/C][/ROW]
[ROW][C]45[/C][C]0.009348[/C][C]0.0718[/C][C]0.471499[/C][/ROW]
[ROW][C]46[/C][C]-0.015522[/C][C]-0.1192[/C][C]0.452751[/C][/ROW]
[ROW][C]47[/C][C]-0.055077[/C][C]-0.4231[/C][C]0.336898[/C][/ROW]
[ROW][C]48[/C][C]0.13712[/C][C]1.0532[/C][C]0.148263[/C][/ROW]
[ROW][C]49[/C][C]-0.04269[/C][C]-0.3279[/C][C]0.372072[/C][/ROW]
[ROW][C]50[/C][C]-0.002649[/C][C]-0.0203[/C][C]0.491917[/C][/ROW]
[ROW][C]51[/C][C]0.016448[/C][C]0.1263[/C][C]0.449946[/C][/ROW]
[ROW][C]52[/C][C]-0.043816[/C][C]-0.3366[/C][C]0.368822[/C][/ROW]
[ROW][C]53[/C][C]0.033798[/C][C]0.2596[/C][C]0.398036[/C][/ROW]
[ROW][C]54[/C][C]-0.017634[/C][C]-0.1354[/C][C]0.44636[/C][/ROW]
[ROW][C]55[/C][C]-0.013091[/C][C]-0.1006[/C][C]0.460121[/C][/ROW]
[ROW][C]56[/C][C]0.011115[/C][C]0.0854[/C][C]0.466125[/C][/ROW]
[ROW][C]57[/C][C]-0.000749[/C][C]-0.0058[/C][C]0.497715[/C][/ROW]
[ROW][C]58[/C][C]-0.001873[/C][C]-0.0144[/C][C]0.494286[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71384&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71384&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
1-0.364807-2.80210.003428
2-0.001194-0.00920.496357
3-0.011172-0.08580.465953
4-0.062382-0.47920.316797
50.1424491.09420.139163
6-0.365199-2.80510.0034
70.0818690.62880.265938
80.0080530.06190.475444
9-0.024218-0.1860.426534
10-0.031576-0.24250.404603
11-0.260959-2.00450.024809
120.7726625.93490
13-0.270242-2.07580.021141
140.0027230.02090.491691
15-0.011527-0.08850.464872
16-0.051146-0.39290.347918
170.1110470.8530.198563
18-0.288983-2.21970.015147
190.0759560.58340.280915
200.0117550.09030.464179
21-0.024321-0.18680.426225
22-0.032223-0.24750.402685
23-0.194894-1.4970.069861
240.5403994.15095.4e-05
25-0.160727-1.23460.110944
26-0.023688-0.1820.428122
270.033360.25620.399327
28-0.082743-0.63560.263759
290.1097510.8430.201313
30-0.207391-1.5930.058252
310.0474760.36470.358331
320.0147660.11340.455042
33-0.036457-0.280.390216
34-0.003118-0.02390.490488
35-0.124707-0.95790.171012
360.3203012.46030.008415
37-0.069365-0.53280.298086
38-0.033067-0.2540.400193
390.0446370.34290.366461
40-0.06939-0.5330.298019
410.0578150.44410.329302
42-0.1019-0.78270.218465
430.0261070.20050.420877
44-0.008462-0.0650.474198
450.0093480.07180.471499
46-0.015522-0.11920.452751
47-0.055077-0.42310.336898
480.137121.05320.148263
49-0.04269-0.32790.372072
50-0.002649-0.02030.491917
510.0164480.12630.449946
52-0.043816-0.33660.368822
530.0337980.25960.398036
54-0.017634-0.13540.44636
55-0.013091-0.10060.460121
560.0111150.08540.466125
57-0.000749-0.00580.497715
58-0.001873-0.01440.494286
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.364807-2.80210.003428
2-0.154891-1.18970.119456
3-0.08058-0.61890.269167
4-0.115212-0.8850.189886
50.0847180.65070.258873
6-0.347738-2.6710.004879
7-0.236767-1.81860.037021
8-0.166298-1.27740.10324
9-0.173106-1.32960.094376
10-0.277747-2.13340.01853
11-0.66268-5.09012e-06
120.385882.9640.002187
130.1635161.2560.107035
140.0143480.11020.456309
15-0.044516-0.34190.366809
160.0521940.40090.344968
17-0.142702-1.09610.138741
180.0192450.14780.441492
190.1843341.41590.081032
200.0498640.3830.351545
21-0.016179-0.12430.450759
220.1171380.89980.185954
230.0795470.6110.271769
24-0.197435-1.51650.067363
250.0158370.12160.451795
26-0.005501-0.04230.483219
270.0172880.13280.447404
28-0.101514-0.77970.21933
290.0750050.57610.28336
300.0008760.00670.497326
31-0.080073-0.61510.270442
32-0.048159-0.36990.356384
33-0.03637-0.27940.390471
34-0.031716-0.24360.404188
350.1029630.79090.216093
36-0.003016-0.02320.490799
37-0.062465-0.47980.316571
38-0.005181-0.03980.484194
39-0.047331-0.36360.358743
400.0243040.18670.426276
41-0.068856-0.52890.299432
420.0653760.50220.308712
430.0282160.21670.414583
44-0.006489-0.04980.480206
450.1436881.10370.137104
460.0669650.51440.304457
470.0556360.42740.33534
48-0.028012-0.21520.415191
49-0.079244-0.60870.272535
50-0.046125-0.35430.36219
51-0.056243-0.4320.333653
52-0.035202-0.27040.3939
530.0244920.18810.425711
540.0089820.0690.472616
55-0.140628-1.08020.142228
56-0.028239-0.21690.414515
57-0.105919-0.81360.209578
58-0.127527-0.97960.165654
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.364807 & -2.8021 & 0.003428 \tabularnewline
2 & -0.154891 & -1.1897 & 0.119456 \tabularnewline
3 & -0.08058 & -0.6189 & 0.269167 \tabularnewline
4 & -0.115212 & -0.885 & 0.189886 \tabularnewline
5 & 0.084718 & 0.6507 & 0.258873 \tabularnewline
6 & -0.347738 & -2.671 & 0.004879 \tabularnewline
7 & -0.236767 & -1.8186 & 0.037021 \tabularnewline
8 & -0.166298 & -1.2774 & 0.10324 \tabularnewline
9 & -0.173106 & -1.3296 & 0.094376 \tabularnewline
10 & -0.277747 & -2.1334 & 0.01853 \tabularnewline
11 & -0.66268 & -5.0901 & 2e-06 \tabularnewline
12 & 0.38588 & 2.964 & 0.002187 \tabularnewline
13 & 0.163516 & 1.256 & 0.107035 \tabularnewline
14 & 0.014348 & 0.1102 & 0.456309 \tabularnewline
15 & -0.044516 & -0.3419 & 0.366809 \tabularnewline
16 & 0.052194 & 0.4009 & 0.344968 \tabularnewline
17 & -0.142702 & -1.0961 & 0.138741 \tabularnewline
18 & 0.019245 & 0.1478 & 0.441492 \tabularnewline
19 & 0.184334 & 1.4159 & 0.081032 \tabularnewline
20 & 0.049864 & 0.383 & 0.351545 \tabularnewline
21 & -0.016179 & -0.1243 & 0.450759 \tabularnewline
22 & 0.117138 & 0.8998 & 0.185954 \tabularnewline
23 & 0.079547 & 0.611 & 0.271769 \tabularnewline
24 & -0.197435 & -1.5165 & 0.067363 \tabularnewline
25 & 0.015837 & 0.1216 & 0.451795 \tabularnewline
26 & -0.005501 & -0.0423 & 0.483219 \tabularnewline
27 & 0.017288 & 0.1328 & 0.447404 \tabularnewline
28 & -0.101514 & -0.7797 & 0.21933 \tabularnewline
29 & 0.075005 & 0.5761 & 0.28336 \tabularnewline
30 & 0.000876 & 0.0067 & 0.497326 \tabularnewline
31 & -0.080073 & -0.6151 & 0.270442 \tabularnewline
32 & -0.048159 & -0.3699 & 0.356384 \tabularnewline
33 & -0.03637 & -0.2794 & 0.390471 \tabularnewline
34 & -0.031716 & -0.2436 & 0.404188 \tabularnewline
35 & 0.102963 & 0.7909 & 0.216093 \tabularnewline
36 & -0.003016 & -0.0232 & 0.490799 \tabularnewline
37 & -0.062465 & -0.4798 & 0.316571 \tabularnewline
38 & -0.005181 & -0.0398 & 0.484194 \tabularnewline
39 & -0.047331 & -0.3636 & 0.358743 \tabularnewline
40 & 0.024304 & 0.1867 & 0.426276 \tabularnewline
41 & -0.068856 & -0.5289 & 0.299432 \tabularnewline
42 & 0.065376 & 0.5022 & 0.308712 \tabularnewline
43 & 0.028216 & 0.2167 & 0.414583 \tabularnewline
44 & -0.006489 & -0.0498 & 0.480206 \tabularnewline
45 & 0.143688 & 1.1037 & 0.137104 \tabularnewline
46 & 0.066965 & 0.5144 & 0.304457 \tabularnewline
47 & 0.055636 & 0.4274 & 0.33534 \tabularnewline
48 & -0.028012 & -0.2152 & 0.415191 \tabularnewline
49 & -0.079244 & -0.6087 & 0.272535 \tabularnewline
50 & -0.046125 & -0.3543 & 0.36219 \tabularnewline
51 & -0.056243 & -0.432 & 0.333653 \tabularnewline
52 & -0.035202 & -0.2704 & 0.3939 \tabularnewline
53 & 0.024492 & 0.1881 & 0.425711 \tabularnewline
54 & 0.008982 & 0.069 & 0.472616 \tabularnewline
55 & -0.140628 & -1.0802 & 0.142228 \tabularnewline
56 & -0.028239 & -0.2169 & 0.414515 \tabularnewline
57 & -0.105919 & -0.8136 & 0.209578 \tabularnewline
58 & -0.127527 & -0.9796 & 0.165654 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71384&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]-0.364807[/C][C]-2.8021[/C][C]0.003428[/C][/ROW]
[ROW][C]2[/C][C]-0.154891[/C][C]-1.1897[/C][C]0.119456[/C][/ROW]
[ROW][C]3[/C][C]-0.08058[/C][C]-0.6189[/C][C]0.269167[/C][/ROW]
[ROW][C]4[/C][C]-0.115212[/C][C]-0.885[/C][C]0.189886[/C][/ROW]
[ROW][C]5[/C][C]0.084718[/C][C]0.6507[/C][C]0.258873[/C][/ROW]
[ROW][C]6[/C][C]-0.347738[/C][C]-2.671[/C][C]0.004879[/C][/ROW]
[ROW][C]7[/C][C]-0.236767[/C][C]-1.8186[/C][C]0.037021[/C][/ROW]
[ROW][C]8[/C][C]-0.166298[/C][C]-1.2774[/C][C]0.10324[/C][/ROW]
[ROW][C]9[/C][C]-0.173106[/C][C]-1.3296[/C][C]0.094376[/C][/ROW]
[ROW][C]10[/C][C]-0.277747[/C][C]-2.1334[/C][C]0.01853[/C][/ROW]
[ROW][C]11[/C][C]-0.66268[/C][C]-5.0901[/C][C]2e-06[/C][/ROW]
[ROW][C]12[/C][C]0.38588[/C][C]2.964[/C][C]0.002187[/C][/ROW]
[ROW][C]13[/C][C]0.163516[/C][C]1.256[/C][C]0.107035[/C][/ROW]
[ROW][C]14[/C][C]0.014348[/C][C]0.1102[/C][C]0.456309[/C][/ROW]
[ROW][C]15[/C][C]-0.044516[/C][C]-0.3419[/C][C]0.366809[/C][/ROW]
[ROW][C]16[/C][C]0.052194[/C][C]0.4009[/C][C]0.344968[/C][/ROW]
[ROW][C]17[/C][C]-0.142702[/C][C]-1.0961[/C][C]0.138741[/C][/ROW]
[ROW][C]18[/C][C]0.019245[/C][C]0.1478[/C][C]0.441492[/C][/ROW]
[ROW][C]19[/C][C]0.184334[/C][C]1.4159[/C][C]0.081032[/C][/ROW]
[ROW][C]20[/C][C]0.049864[/C][C]0.383[/C][C]0.351545[/C][/ROW]
[ROW][C]21[/C][C]-0.016179[/C][C]-0.1243[/C][C]0.450759[/C][/ROW]
[ROW][C]22[/C][C]0.117138[/C][C]0.8998[/C][C]0.185954[/C][/ROW]
[ROW][C]23[/C][C]0.079547[/C][C]0.611[/C][C]0.271769[/C][/ROW]
[ROW][C]24[/C][C]-0.197435[/C][C]-1.5165[/C][C]0.067363[/C][/ROW]
[ROW][C]25[/C][C]0.015837[/C][C]0.1216[/C][C]0.451795[/C][/ROW]
[ROW][C]26[/C][C]-0.005501[/C][C]-0.0423[/C][C]0.483219[/C][/ROW]
[ROW][C]27[/C][C]0.017288[/C][C]0.1328[/C][C]0.447404[/C][/ROW]
[ROW][C]28[/C][C]-0.101514[/C][C]-0.7797[/C][C]0.21933[/C][/ROW]
[ROW][C]29[/C][C]0.075005[/C][C]0.5761[/C][C]0.28336[/C][/ROW]
[ROW][C]30[/C][C]0.000876[/C][C]0.0067[/C][C]0.497326[/C][/ROW]
[ROW][C]31[/C][C]-0.080073[/C][C]-0.6151[/C][C]0.270442[/C][/ROW]
[ROW][C]32[/C][C]-0.048159[/C][C]-0.3699[/C][C]0.356384[/C][/ROW]
[ROW][C]33[/C][C]-0.03637[/C][C]-0.2794[/C][C]0.390471[/C][/ROW]
[ROW][C]34[/C][C]-0.031716[/C][C]-0.2436[/C][C]0.404188[/C][/ROW]
[ROW][C]35[/C][C]0.102963[/C][C]0.7909[/C][C]0.216093[/C][/ROW]
[ROW][C]36[/C][C]-0.003016[/C][C]-0.0232[/C][C]0.490799[/C][/ROW]
[ROW][C]37[/C][C]-0.062465[/C][C]-0.4798[/C][C]0.316571[/C][/ROW]
[ROW][C]38[/C][C]-0.005181[/C][C]-0.0398[/C][C]0.484194[/C][/ROW]
[ROW][C]39[/C][C]-0.047331[/C][C]-0.3636[/C][C]0.358743[/C][/ROW]
[ROW][C]40[/C][C]0.024304[/C][C]0.1867[/C][C]0.426276[/C][/ROW]
[ROW][C]41[/C][C]-0.068856[/C][C]-0.5289[/C][C]0.299432[/C][/ROW]
[ROW][C]42[/C][C]0.065376[/C][C]0.5022[/C][C]0.308712[/C][/ROW]
[ROW][C]43[/C][C]0.028216[/C][C]0.2167[/C][C]0.414583[/C][/ROW]
[ROW][C]44[/C][C]-0.006489[/C][C]-0.0498[/C][C]0.480206[/C][/ROW]
[ROW][C]45[/C][C]0.143688[/C][C]1.1037[/C][C]0.137104[/C][/ROW]
[ROW][C]46[/C][C]0.066965[/C][C]0.5144[/C][C]0.304457[/C][/ROW]
[ROW][C]47[/C][C]0.055636[/C][C]0.4274[/C][C]0.33534[/C][/ROW]
[ROW][C]48[/C][C]-0.028012[/C][C]-0.2152[/C][C]0.415191[/C][/ROW]
[ROW][C]49[/C][C]-0.079244[/C][C]-0.6087[/C][C]0.272535[/C][/ROW]
[ROW][C]50[/C][C]-0.046125[/C][C]-0.3543[/C][C]0.36219[/C][/ROW]
[ROW][C]51[/C][C]-0.056243[/C][C]-0.432[/C][C]0.333653[/C][/ROW]
[ROW][C]52[/C][C]-0.035202[/C][C]-0.2704[/C][C]0.3939[/C][/ROW]
[ROW][C]53[/C][C]0.024492[/C][C]0.1881[/C][C]0.425711[/C][/ROW]
[ROW][C]54[/C][C]0.008982[/C][C]0.069[/C][C]0.472616[/C][/ROW]
[ROW][C]55[/C][C]-0.140628[/C][C]-1.0802[/C][C]0.142228[/C][/ROW]
[ROW][C]56[/C][C]-0.028239[/C][C]-0.2169[/C][C]0.414515[/C][/ROW]
[ROW][C]57[/C][C]-0.105919[/C][C]-0.8136[/C][C]0.209578[/C][/ROW]
[ROW][C]58[/C][C]-0.127527[/C][C]-0.9796[/C][C]0.165654[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71384&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71384&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
1-0.364807-2.80210.003428
2-0.154891-1.18970.119456
3-0.08058-0.61890.269167
4-0.115212-0.8850.189886
50.0847180.65070.258873
6-0.347738-2.6710.004879
7-0.236767-1.81860.037021
8-0.166298-1.27740.10324
9-0.173106-1.32960.094376
10-0.277747-2.13340.01853
11-0.66268-5.09012e-06
120.385882.9640.002187
130.1635161.2560.107035
140.0143480.11020.456309
15-0.044516-0.34190.366809
160.0521940.40090.344968
17-0.142702-1.09610.138741
180.0192450.14780.441492
190.1843341.41590.081032
200.0498640.3830.351545
21-0.016179-0.12430.450759
220.1171380.89980.185954
230.0795470.6110.271769
24-0.197435-1.51650.067363
250.0158370.12160.451795
26-0.005501-0.04230.483219
270.0172880.13280.447404
28-0.101514-0.77970.21933
290.0750050.57610.28336
300.0008760.00670.497326
31-0.080073-0.61510.270442
32-0.048159-0.36990.356384
33-0.03637-0.27940.390471
34-0.031716-0.24360.404188
350.1029630.79090.216093
36-0.003016-0.02320.490799
37-0.062465-0.47980.316571
38-0.005181-0.03980.484194
39-0.047331-0.36360.358743
400.0243040.18670.426276
41-0.068856-0.52890.299432
420.0653760.50220.308712
430.0282160.21670.414583
44-0.006489-0.04980.480206
450.1436881.10370.137104
460.0669650.51440.304457
470.0556360.42740.33534
48-0.028012-0.21520.415191
49-0.079244-0.60870.272535
50-0.046125-0.35430.36219
51-0.056243-0.4320.333653
52-0.035202-0.27040.3939
530.0244920.18810.425711
540.0089820.0690.472616
55-0.140628-1.08020.142228
56-0.028239-0.21690.414515
57-0.105919-0.81360.209578
58-0.127527-0.97960.165654
59NANANA
60NANANA



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')