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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 18 Dec 2009 04:39:58 -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/18/t1261136422qqerhxfczjvdsuf.htm/, Retrieved Sat, 27 Apr 2024 13:14:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69251, Retrieved Sat, 27 Apr 2024 13:14:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2009-12-18 11:39:58] [02cb93c9d037d32bf77dfc632a3a9fbe] [Current]
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Dataseries X:
100.00
100.00
93.55
88.17
89.25
91.40
92.47
91.40
88.17
87.10
84.95
92.47
93.55
93.55
91.40
90.32
91.40
93.55
93.55
92.47
91.40
89.25
86.02
88.17
87.10
87.10
86.02
84.95
84.95
86.02
86.02
84.95
86.02
82.80
77.42
80.65
78.49
75.27
75.27
75.27
77.42
78.49
76.34
73.12
68.82
65.59
69.89
82.80
84.95
80.65
74.19
70.97
74.19
82.80
86.02
86.02
82.80
78.49
79.57
87.10
89.25




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=69251&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=69251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69251&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3380872.61880.005578
2-0.295585-2.28960.012789
3-0.525179-4.0687e-05
4-0.352056-2.7270.004184
50.1445971.120.133579
60.534554.14065.5e-05
70.352742.73230.004125
8-0.057328-0.44410.329299
9-0.337762-2.61630.005615
10-0.319812-2.47730.008037
11-0.014082-0.10910.456753
120.3634242.81510.003294
130.0828460.64170.261748
14-0.06568-0.50880.306396
15-0.078723-0.60980.272154
16-0.088736-0.68730.247258
17-0.004284-0.03320.486818
180.0932990.72270.236338
190.0250630.19410.423361
20-0.053174-0.41190.340947
21-0.061141-0.47360.318754
22-0.057299-0.44380.329379
230.0436720.33830.368167
240.1628751.26160.105984
25-0.107472-0.83250.20422
26-0.142776-1.10590.136584
27-0.072378-0.56060.288567
28-0.014652-0.11350.455008
290.0829190.64230.261567
300.1292921.00150.160306
310.0390050.30210.381799
32-0.119974-0.92930.178226
33-0.168425-1.30460.098503
340.0051630.040.484115
350.1706871.32210.09557
360.2341471.81370.037363
37-0.023159-0.17940.429119
38-0.177244-1.37290.087442
39-0.192009-1.48730.071087
40-0.036799-0.2850.388296
410.1627491.26070.106157
420.2668092.06670.021543
430.0722790.55990.288825
44-0.190231-1.47350.072918
45-0.260447-2.01740.024066
46-0.062972-0.48780.313742
470.1343851.04090.151039
480.2074731.60710.056644
490.0483930.37490.354547
50-0.104083-0.80620.211649
51-0.147456-1.14220.128956
52-0.061849-0.47910.316811
530.0273690.2120.416414
540.08380.64910.259371
550.0451240.34950.363959
56-0.060884-0.47160.31946
57-0.080072-0.62020.268726
58-0.017581-0.13620.446067
590.0005550.00430.498293
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.338087 & 2.6188 & 0.005578 \tabularnewline
2 & -0.295585 & -2.2896 & 0.012789 \tabularnewline
3 & -0.525179 & -4.068 & 7e-05 \tabularnewline
4 & -0.352056 & -2.727 & 0.004184 \tabularnewline
5 & 0.144597 & 1.12 & 0.133579 \tabularnewline
6 & 0.53455 & 4.1406 & 5.5e-05 \tabularnewline
7 & 0.35274 & 2.7323 & 0.004125 \tabularnewline
8 & -0.057328 & -0.4441 & 0.329299 \tabularnewline
9 & -0.337762 & -2.6163 & 0.005615 \tabularnewline
10 & -0.319812 & -2.4773 & 0.008037 \tabularnewline
11 & -0.014082 & -0.1091 & 0.456753 \tabularnewline
12 & 0.363424 & 2.8151 & 0.003294 \tabularnewline
13 & 0.082846 & 0.6417 & 0.261748 \tabularnewline
14 & -0.06568 & -0.5088 & 0.306396 \tabularnewline
15 & -0.078723 & -0.6098 & 0.272154 \tabularnewline
16 & -0.088736 & -0.6873 & 0.247258 \tabularnewline
17 & -0.004284 & -0.0332 & 0.486818 \tabularnewline
18 & 0.093299 & 0.7227 & 0.236338 \tabularnewline
19 & 0.025063 & 0.1941 & 0.423361 \tabularnewline
20 & -0.053174 & -0.4119 & 0.340947 \tabularnewline
21 & -0.061141 & -0.4736 & 0.318754 \tabularnewline
22 & -0.057299 & -0.4438 & 0.329379 \tabularnewline
23 & 0.043672 & 0.3383 & 0.368167 \tabularnewline
24 & 0.162875 & 1.2616 & 0.105984 \tabularnewline
25 & -0.107472 & -0.8325 & 0.20422 \tabularnewline
26 & -0.142776 & -1.1059 & 0.136584 \tabularnewline
27 & -0.072378 & -0.5606 & 0.288567 \tabularnewline
28 & -0.014652 & -0.1135 & 0.455008 \tabularnewline
29 & 0.082919 & 0.6423 & 0.261567 \tabularnewline
30 & 0.129292 & 1.0015 & 0.160306 \tabularnewline
31 & 0.039005 & 0.3021 & 0.381799 \tabularnewline
32 & -0.119974 & -0.9293 & 0.178226 \tabularnewline
33 & -0.168425 & -1.3046 & 0.098503 \tabularnewline
34 & 0.005163 & 0.04 & 0.484115 \tabularnewline
35 & 0.170687 & 1.3221 & 0.09557 \tabularnewline
36 & 0.234147 & 1.8137 & 0.037363 \tabularnewline
37 & -0.023159 & -0.1794 & 0.429119 \tabularnewline
38 & -0.177244 & -1.3729 & 0.087442 \tabularnewline
39 & -0.192009 & -1.4873 & 0.071087 \tabularnewline
40 & -0.036799 & -0.285 & 0.388296 \tabularnewline
41 & 0.162749 & 1.2607 & 0.106157 \tabularnewline
42 & 0.266809 & 2.0667 & 0.021543 \tabularnewline
43 & 0.072279 & 0.5599 & 0.288825 \tabularnewline
44 & -0.190231 & -1.4735 & 0.072918 \tabularnewline
45 & -0.260447 & -2.0174 & 0.024066 \tabularnewline
46 & -0.062972 & -0.4878 & 0.313742 \tabularnewline
47 & 0.134385 & 1.0409 & 0.151039 \tabularnewline
48 & 0.207473 & 1.6071 & 0.056644 \tabularnewline
49 & 0.048393 & 0.3749 & 0.354547 \tabularnewline
50 & -0.104083 & -0.8062 & 0.211649 \tabularnewline
51 & -0.147456 & -1.1422 & 0.128956 \tabularnewline
52 & -0.061849 & -0.4791 & 0.316811 \tabularnewline
53 & 0.027369 & 0.212 & 0.416414 \tabularnewline
54 & 0.0838 & 0.6491 & 0.259371 \tabularnewline
55 & 0.045124 & 0.3495 & 0.363959 \tabularnewline
56 & -0.060884 & -0.4716 & 0.31946 \tabularnewline
57 & -0.080072 & -0.6202 & 0.268726 \tabularnewline
58 & -0.017581 & -0.1362 & 0.446067 \tabularnewline
59 & 0.000555 & 0.0043 & 0.498293 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69251&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]0.338087[/C][C]2.6188[/C][C]0.005578[/C][/ROW]
[ROW][C]2[/C][C]-0.295585[/C][C]-2.2896[/C][C]0.012789[/C][/ROW]
[ROW][C]3[/C][C]-0.525179[/C][C]-4.068[/C][C]7e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.352056[/C][C]-2.727[/C][C]0.004184[/C][/ROW]
[ROW][C]5[/C][C]0.144597[/C][C]1.12[/C][C]0.133579[/C][/ROW]
[ROW][C]6[/C][C]0.53455[/C][C]4.1406[/C][C]5.5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.35274[/C][C]2.7323[/C][C]0.004125[/C][/ROW]
[ROW][C]8[/C][C]-0.057328[/C][C]-0.4441[/C][C]0.329299[/C][/ROW]
[ROW][C]9[/C][C]-0.337762[/C][C]-2.6163[/C][C]0.005615[/C][/ROW]
[ROW][C]10[/C][C]-0.319812[/C][C]-2.4773[/C][C]0.008037[/C][/ROW]
[ROW][C]11[/C][C]-0.014082[/C][C]-0.1091[/C][C]0.456753[/C][/ROW]
[ROW][C]12[/C][C]0.363424[/C][C]2.8151[/C][C]0.003294[/C][/ROW]
[ROW][C]13[/C][C]0.082846[/C][C]0.6417[/C][C]0.261748[/C][/ROW]
[ROW][C]14[/C][C]-0.06568[/C][C]-0.5088[/C][C]0.306396[/C][/ROW]
[ROW][C]15[/C][C]-0.078723[/C][C]-0.6098[/C][C]0.272154[/C][/ROW]
[ROW][C]16[/C][C]-0.088736[/C][C]-0.6873[/C][C]0.247258[/C][/ROW]
[ROW][C]17[/C][C]-0.004284[/C][C]-0.0332[/C][C]0.486818[/C][/ROW]
[ROW][C]18[/C][C]0.093299[/C][C]0.7227[/C][C]0.236338[/C][/ROW]
[ROW][C]19[/C][C]0.025063[/C][C]0.1941[/C][C]0.423361[/C][/ROW]
[ROW][C]20[/C][C]-0.053174[/C][C]-0.4119[/C][C]0.340947[/C][/ROW]
[ROW][C]21[/C][C]-0.061141[/C][C]-0.4736[/C][C]0.318754[/C][/ROW]
[ROW][C]22[/C][C]-0.057299[/C][C]-0.4438[/C][C]0.329379[/C][/ROW]
[ROW][C]23[/C][C]0.043672[/C][C]0.3383[/C][C]0.368167[/C][/ROW]
[ROW][C]24[/C][C]0.162875[/C][C]1.2616[/C][C]0.105984[/C][/ROW]
[ROW][C]25[/C][C]-0.107472[/C][C]-0.8325[/C][C]0.20422[/C][/ROW]
[ROW][C]26[/C][C]-0.142776[/C][C]-1.1059[/C][C]0.136584[/C][/ROW]
[ROW][C]27[/C][C]-0.072378[/C][C]-0.5606[/C][C]0.288567[/C][/ROW]
[ROW][C]28[/C][C]-0.014652[/C][C]-0.1135[/C][C]0.455008[/C][/ROW]
[ROW][C]29[/C][C]0.082919[/C][C]0.6423[/C][C]0.261567[/C][/ROW]
[ROW][C]30[/C][C]0.129292[/C][C]1.0015[/C][C]0.160306[/C][/ROW]
[ROW][C]31[/C][C]0.039005[/C][C]0.3021[/C][C]0.381799[/C][/ROW]
[ROW][C]32[/C][C]-0.119974[/C][C]-0.9293[/C][C]0.178226[/C][/ROW]
[ROW][C]33[/C][C]-0.168425[/C][C]-1.3046[/C][C]0.098503[/C][/ROW]
[ROW][C]34[/C][C]0.005163[/C][C]0.04[/C][C]0.484115[/C][/ROW]
[ROW][C]35[/C][C]0.170687[/C][C]1.3221[/C][C]0.09557[/C][/ROW]
[ROW][C]36[/C][C]0.234147[/C][C]1.8137[/C][C]0.037363[/C][/ROW]
[ROW][C]37[/C][C]-0.023159[/C][C]-0.1794[/C][C]0.429119[/C][/ROW]
[ROW][C]38[/C][C]-0.177244[/C][C]-1.3729[/C][C]0.087442[/C][/ROW]
[ROW][C]39[/C][C]-0.192009[/C][C]-1.4873[/C][C]0.071087[/C][/ROW]
[ROW][C]40[/C][C]-0.036799[/C][C]-0.285[/C][C]0.388296[/C][/ROW]
[ROW][C]41[/C][C]0.162749[/C][C]1.2607[/C][C]0.106157[/C][/ROW]
[ROW][C]42[/C][C]0.266809[/C][C]2.0667[/C][C]0.021543[/C][/ROW]
[ROW][C]43[/C][C]0.072279[/C][C]0.5599[/C][C]0.288825[/C][/ROW]
[ROW][C]44[/C][C]-0.190231[/C][C]-1.4735[/C][C]0.072918[/C][/ROW]
[ROW][C]45[/C][C]-0.260447[/C][C]-2.0174[/C][C]0.024066[/C][/ROW]
[ROW][C]46[/C][C]-0.062972[/C][C]-0.4878[/C][C]0.313742[/C][/ROW]
[ROW][C]47[/C][C]0.134385[/C][C]1.0409[/C][C]0.151039[/C][/ROW]
[ROW][C]48[/C][C]0.207473[/C][C]1.6071[/C][C]0.056644[/C][/ROW]
[ROW][C]49[/C][C]0.048393[/C][C]0.3749[/C][C]0.354547[/C][/ROW]
[ROW][C]50[/C][C]-0.104083[/C][C]-0.8062[/C][C]0.211649[/C][/ROW]
[ROW][C]51[/C][C]-0.147456[/C][C]-1.1422[/C][C]0.128956[/C][/ROW]
[ROW][C]52[/C][C]-0.061849[/C][C]-0.4791[/C][C]0.316811[/C][/ROW]
[ROW][C]53[/C][C]0.027369[/C][C]0.212[/C][C]0.416414[/C][/ROW]
[ROW][C]54[/C][C]0.0838[/C][C]0.6491[/C][C]0.259371[/C][/ROW]
[ROW][C]55[/C][C]0.045124[/C][C]0.3495[/C][C]0.363959[/C][/ROW]
[ROW][C]56[/C][C]-0.060884[/C][C]-0.4716[/C][C]0.31946[/C][/ROW]
[ROW][C]57[/C][C]-0.080072[/C][C]-0.6202[/C][C]0.268726[/C][/ROW]
[ROW][C]58[/C][C]-0.017581[/C][C]-0.1362[/C][C]0.446067[/C][/ROW]
[ROW][C]59[/C][C]0.000555[/C][C]0.0043[/C][C]0.498293[/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=69251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69251&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3380872.61880.005578
2-0.295585-2.28960.012789
3-0.525179-4.0687e-05
4-0.352056-2.7270.004184
50.1445971.120.133579
60.534554.14065.5e-05
70.352742.73230.004125
8-0.057328-0.44410.329299
9-0.337762-2.61630.005615
10-0.319812-2.47730.008037
11-0.014082-0.10910.456753
120.3634242.81510.003294
130.0828460.64170.261748
14-0.06568-0.50880.306396
15-0.078723-0.60980.272154
16-0.088736-0.68730.247258
17-0.004284-0.03320.486818
180.0932990.72270.236338
190.0250630.19410.423361
20-0.053174-0.41190.340947
21-0.061141-0.47360.318754
22-0.057299-0.44380.329379
230.0436720.33830.368167
240.1628751.26160.105984
25-0.107472-0.83250.20422
26-0.142776-1.10590.136584
27-0.072378-0.56060.288567
28-0.014652-0.11350.455008
290.0829190.64230.261567
300.1292921.00150.160306
310.0390050.30210.381799
32-0.119974-0.92930.178226
33-0.168425-1.30460.098503
340.0051630.040.484115
350.1706871.32210.09557
360.2341471.81370.037363
37-0.023159-0.17940.429119
38-0.177244-1.37290.087442
39-0.192009-1.48730.071087
40-0.036799-0.2850.388296
410.1627491.26070.106157
420.2668092.06670.021543
430.0722790.55990.288825
44-0.190231-1.47350.072918
45-0.260447-2.01740.024066
46-0.062972-0.48780.313742
470.1343851.04090.151039
480.2074731.60710.056644
490.0483930.37490.354547
50-0.104083-0.80620.211649
51-0.147456-1.14220.128956
52-0.061849-0.47910.316811
530.0273690.2120.416414
540.08380.64910.259371
550.0451240.34950.363959
56-0.060884-0.47160.31946
57-0.080072-0.62020.268726
58-0.017581-0.13620.446067
590.0005550.00430.498293
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3380872.61880.005578
2-0.462786-3.58470.000339
3-0.319732-2.47660.00805
4-0.24325-1.88420.032192
50.0900880.69780.243994
60.2596322.01110.024407
70.043870.33980.367591
80.0751130.58180.281434
90.0390980.30290.381525
100.0016890.01310.494803
110.0062710.04860.48071
120.1527251.1830.120737
13-0.46302-3.58650.000337
140.1199280.9290.178316
150.0764180.59190.27806
160.0090370.070.472215
17-0.054986-0.42590.335845
18-0.008136-0.0630.474981
190.0955640.74020.231023
20-0.019882-0.1540.439061
21-0.0425-0.32920.371574
22-0.149778-1.16020.125287
230.0680710.52730.299973
240.04930.38190.351952
25-0.1623-1.25720.106782
26-0.080311-0.62210.26812
27-0.094278-0.73030.234031
280.0647780.50180.308834
29-0.011388-0.08820.465002
30-0.026166-0.20270.420035
310.0633820.4910.312626
32-0.031396-0.24320.404344
333e-052e-040.499907
340.2434491.88570.032086
35-0.00103-0.0080.496831
360.0278210.21550.415054
370.0386570.29940.382822
38-0.100684-0.77990.219259
39-0.083027-0.64310.261297
40-0.020185-0.15640.438139
41-0.044329-0.34340.36626
420.1014960.78620.217426
43-0.093199-0.72190.236576
440.0482970.37410.354821
450.0667070.51670.303629
46-0.017598-0.13630.446016
47-0.028618-0.22170.412662
48-0.107585-0.83330.203977
490.0052420.04060.483872
50-0.072284-0.55990.288813
510.0357510.27690.391393
52-0.096745-0.74940.228278
53-0.033247-0.25750.398827
54-0.059313-0.45940.323791
550.0444560.34440.365892
560.0045690.03540.485944
57-0.057506-0.44540.328802
58-0.084703-0.65610.257132
590.0692660.53650.296788
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.338087 & 2.6188 & 0.005578 \tabularnewline
2 & -0.462786 & -3.5847 & 0.000339 \tabularnewline
3 & -0.319732 & -2.4766 & 0.00805 \tabularnewline
4 & -0.24325 & -1.8842 & 0.032192 \tabularnewline
5 & 0.090088 & 0.6978 & 0.243994 \tabularnewline
6 & 0.259632 & 2.0111 & 0.024407 \tabularnewline
7 & 0.04387 & 0.3398 & 0.367591 \tabularnewline
8 & 0.075113 & 0.5818 & 0.281434 \tabularnewline
9 & 0.039098 & 0.3029 & 0.381525 \tabularnewline
10 & 0.001689 & 0.0131 & 0.494803 \tabularnewline
11 & 0.006271 & 0.0486 & 0.48071 \tabularnewline
12 & 0.152725 & 1.183 & 0.120737 \tabularnewline
13 & -0.46302 & -3.5865 & 0.000337 \tabularnewline
14 & 0.119928 & 0.929 & 0.178316 \tabularnewline
15 & 0.076418 & 0.5919 & 0.27806 \tabularnewline
16 & 0.009037 & 0.07 & 0.472215 \tabularnewline
17 & -0.054986 & -0.4259 & 0.335845 \tabularnewline
18 & -0.008136 & -0.063 & 0.474981 \tabularnewline
19 & 0.095564 & 0.7402 & 0.231023 \tabularnewline
20 & -0.019882 & -0.154 & 0.439061 \tabularnewline
21 & -0.0425 & -0.3292 & 0.371574 \tabularnewline
22 & -0.149778 & -1.1602 & 0.125287 \tabularnewline
23 & 0.068071 & 0.5273 & 0.299973 \tabularnewline
24 & 0.0493 & 0.3819 & 0.351952 \tabularnewline
25 & -0.1623 & -1.2572 & 0.106782 \tabularnewline
26 & -0.080311 & -0.6221 & 0.26812 \tabularnewline
27 & -0.094278 & -0.7303 & 0.234031 \tabularnewline
28 & 0.064778 & 0.5018 & 0.308834 \tabularnewline
29 & -0.011388 & -0.0882 & 0.465002 \tabularnewline
30 & -0.026166 & -0.2027 & 0.420035 \tabularnewline
31 & 0.063382 & 0.491 & 0.312626 \tabularnewline
32 & -0.031396 & -0.2432 & 0.404344 \tabularnewline
33 & 3e-05 & 2e-04 & 0.499907 \tabularnewline
34 & 0.243449 & 1.8857 & 0.032086 \tabularnewline
35 & -0.00103 & -0.008 & 0.496831 \tabularnewline
36 & 0.027821 & 0.2155 & 0.415054 \tabularnewline
37 & 0.038657 & 0.2994 & 0.382822 \tabularnewline
38 & -0.100684 & -0.7799 & 0.219259 \tabularnewline
39 & -0.083027 & -0.6431 & 0.261297 \tabularnewline
40 & -0.020185 & -0.1564 & 0.438139 \tabularnewline
41 & -0.044329 & -0.3434 & 0.36626 \tabularnewline
42 & 0.101496 & 0.7862 & 0.217426 \tabularnewline
43 & -0.093199 & -0.7219 & 0.236576 \tabularnewline
44 & 0.048297 & 0.3741 & 0.354821 \tabularnewline
45 & 0.066707 & 0.5167 & 0.303629 \tabularnewline
46 & -0.017598 & -0.1363 & 0.446016 \tabularnewline
47 & -0.028618 & -0.2217 & 0.412662 \tabularnewline
48 & -0.107585 & -0.8333 & 0.203977 \tabularnewline
49 & 0.005242 & 0.0406 & 0.483872 \tabularnewline
50 & -0.072284 & -0.5599 & 0.288813 \tabularnewline
51 & 0.035751 & 0.2769 & 0.391393 \tabularnewline
52 & -0.096745 & -0.7494 & 0.228278 \tabularnewline
53 & -0.033247 & -0.2575 & 0.398827 \tabularnewline
54 & -0.059313 & -0.4594 & 0.323791 \tabularnewline
55 & 0.044456 & 0.3444 & 0.365892 \tabularnewline
56 & 0.004569 & 0.0354 & 0.485944 \tabularnewline
57 & -0.057506 & -0.4454 & 0.328802 \tabularnewline
58 & -0.084703 & -0.6561 & 0.257132 \tabularnewline
59 & 0.069266 & 0.5365 & 0.296788 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69251&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]0.338087[/C][C]2.6188[/C][C]0.005578[/C][/ROW]
[ROW][C]2[/C][C]-0.462786[/C][C]-3.5847[/C][C]0.000339[/C][/ROW]
[ROW][C]3[/C][C]-0.319732[/C][C]-2.4766[/C][C]0.00805[/C][/ROW]
[ROW][C]4[/C][C]-0.24325[/C][C]-1.8842[/C][C]0.032192[/C][/ROW]
[ROW][C]5[/C][C]0.090088[/C][C]0.6978[/C][C]0.243994[/C][/ROW]
[ROW][C]6[/C][C]0.259632[/C][C]2.0111[/C][C]0.024407[/C][/ROW]
[ROW][C]7[/C][C]0.04387[/C][C]0.3398[/C][C]0.367591[/C][/ROW]
[ROW][C]8[/C][C]0.075113[/C][C]0.5818[/C][C]0.281434[/C][/ROW]
[ROW][C]9[/C][C]0.039098[/C][C]0.3029[/C][C]0.381525[/C][/ROW]
[ROW][C]10[/C][C]0.001689[/C][C]0.0131[/C][C]0.494803[/C][/ROW]
[ROW][C]11[/C][C]0.006271[/C][C]0.0486[/C][C]0.48071[/C][/ROW]
[ROW][C]12[/C][C]0.152725[/C][C]1.183[/C][C]0.120737[/C][/ROW]
[ROW][C]13[/C][C]-0.46302[/C][C]-3.5865[/C][C]0.000337[/C][/ROW]
[ROW][C]14[/C][C]0.119928[/C][C]0.929[/C][C]0.178316[/C][/ROW]
[ROW][C]15[/C][C]0.076418[/C][C]0.5919[/C][C]0.27806[/C][/ROW]
[ROW][C]16[/C][C]0.009037[/C][C]0.07[/C][C]0.472215[/C][/ROW]
[ROW][C]17[/C][C]-0.054986[/C][C]-0.4259[/C][C]0.335845[/C][/ROW]
[ROW][C]18[/C][C]-0.008136[/C][C]-0.063[/C][C]0.474981[/C][/ROW]
[ROW][C]19[/C][C]0.095564[/C][C]0.7402[/C][C]0.231023[/C][/ROW]
[ROW][C]20[/C][C]-0.019882[/C][C]-0.154[/C][C]0.439061[/C][/ROW]
[ROW][C]21[/C][C]-0.0425[/C][C]-0.3292[/C][C]0.371574[/C][/ROW]
[ROW][C]22[/C][C]-0.149778[/C][C]-1.1602[/C][C]0.125287[/C][/ROW]
[ROW][C]23[/C][C]0.068071[/C][C]0.5273[/C][C]0.299973[/C][/ROW]
[ROW][C]24[/C][C]0.0493[/C][C]0.3819[/C][C]0.351952[/C][/ROW]
[ROW][C]25[/C][C]-0.1623[/C][C]-1.2572[/C][C]0.106782[/C][/ROW]
[ROW][C]26[/C][C]-0.080311[/C][C]-0.6221[/C][C]0.26812[/C][/ROW]
[ROW][C]27[/C][C]-0.094278[/C][C]-0.7303[/C][C]0.234031[/C][/ROW]
[ROW][C]28[/C][C]0.064778[/C][C]0.5018[/C][C]0.308834[/C][/ROW]
[ROW][C]29[/C][C]-0.011388[/C][C]-0.0882[/C][C]0.465002[/C][/ROW]
[ROW][C]30[/C][C]-0.026166[/C][C]-0.2027[/C][C]0.420035[/C][/ROW]
[ROW][C]31[/C][C]0.063382[/C][C]0.491[/C][C]0.312626[/C][/ROW]
[ROW][C]32[/C][C]-0.031396[/C][C]-0.2432[/C][C]0.404344[/C][/ROW]
[ROW][C]33[/C][C]3e-05[/C][C]2e-04[/C][C]0.499907[/C][/ROW]
[ROW][C]34[/C][C]0.243449[/C][C]1.8857[/C][C]0.032086[/C][/ROW]
[ROW][C]35[/C][C]-0.00103[/C][C]-0.008[/C][C]0.496831[/C][/ROW]
[ROW][C]36[/C][C]0.027821[/C][C]0.2155[/C][C]0.415054[/C][/ROW]
[ROW][C]37[/C][C]0.038657[/C][C]0.2994[/C][C]0.382822[/C][/ROW]
[ROW][C]38[/C][C]-0.100684[/C][C]-0.7799[/C][C]0.219259[/C][/ROW]
[ROW][C]39[/C][C]-0.083027[/C][C]-0.6431[/C][C]0.261297[/C][/ROW]
[ROW][C]40[/C][C]-0.020185[/C][C]-0.1564[/C][C]0.438139[/C][/ROW]
[ROW][C]41[/C][C]-0.044329[/C][C]-0.3434[/C][C]0.36626[/C][/ROW]
[ROW][C]42[/C][C]0.101496[/C][C]0.7862[/C][C]0.217426[/C][/ROW]
[ROW][C]43[/C][C]-0.093199[/C][C]-0.7219[/C][C]0.236576[/C][/ROW]
[ROW][C]44[/C][C]0.048297[/C][C]0.3741[/C][C]0.354821[/C][/ROW]
[ROW][C]45[/C][C]0.066707[/C][C]0.5167[/C][C]0.303629[/C][/ROW]
[ROW][C]46[/C][C]-0.017598[/C][C]-0.1363[/C][C]0.446016[/C][/ROW]
[ROW][C]47[/C][C]-0.028618[/C][C]-0.2217[/C][C]0.412662[/C][/ROW]
[ROW][C]48[/C][C]-0.107585[/C][C]-0.8333[/C][C]0.203977[/C][/ROW]
[ROW][C]49[/C][C]0.005242[/C][C]0.0406[/C][C]0.483872[/C][/ROW]
[ROW][C]50[/C][C]-0.072284[/C][C]-0.5599[/C][C]0.288813[/C][/ROW]
[ROW][C]51[/C][C]0.035751[/C][C]0.2769[/C][C]0.391393[/C][/ROW]
[ROW][C]52[/C][C]-0.096745[/C][C]-0.7494[/C][C]0.228278[/C][/ROW]
[ROW][C]53[/C][C]-0.033247[/C][C]-0.2575[/C][C]0.398827[/C][/ROW]
[ROW][C]54[/C][C]-0.059313[/C][C]-0.4594[/C][C]0.323791[/C][/ROW]
[ROW][C]55[/C][C]0.044456[/C][C]0.3444[/C][C]0.365892[/C][/ROW]
[ROW][C]56[/C][C]0.004569[/C][C]0.0354[/C][C]0.485944[/C][/ROW]
[ROW][C]57[/C][C]-0.057506[/C][C]-0.4454[/C][C]0.328802[/C][/ROW]
[ROW][C]58[/C][C]-0.084703[/C][C]-0.6561[/C][C]0.257132[/C][/ROW]
[ROW][C]59[/C][C]0.069266[/C][C]0.5365[/C][C]0.296788[/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=69251&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69251&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3380872.61880.005578
2-0.462786-3.58470.000339
3-0.319732-2.47660.00805
4-0.24325-1.88420.032192
50.0900880.69780.243994
60.2596322.01110.024407
70.043870.33980.367591
80.0751130.58180.281434
90.0390980.30290.381525
100.0016890.01310.494803
110.0062710.04860.48071
120.1527251.1830.120737
13-0.46302-3.58650.000337
140.1199280.9290.178316
150.0764180.59190.27806
160.0090370.070.472215
17-0.054986-0.42590.335845
18-0.008136-0.0630.474981
190.0955640.74020.231023
20-0.019882-0.1540.439061
21-0.0425-0.32920.371574
22-0.149778-1.16020.125287
230.0680710.52730.299973
240.04930.38190.351952
25-0.1623-1.25720.106782
26-0.080311-0.62210.26812
27-0.094278-0.73030.234031
280.0647780.50180.308834
29-0.011388-0.08820.465002
30-0.026166-0.20270.420035
310.0633820.4910.312626
32-0.031396-0.24320.404344
333e-052e-040.499907
340.2434491.88570.032086
35-0.00103-0.0080.496831
360.0278210.21550.415054
370.0386570.29940.382822
38-0.100684-0.77990.219259
39-0.083027-0.64310.261297
40-0.020185-0.15640.438139
41-0.044329-0.34340.36626
420.1014960.78620.217426
43-0.093199-0.72190.236576
440.0482970.37410.354821
450.0667070.51670.303629
46-0.017598-0.13630.446016
47-0.028618-0.22170.412662
48-0.107585-0.83330.203977
490.0052420.04060.483872
50-0.072284-0.55990.288813
510.0357510.27690.391393
52-0.096745-0.74940.228278
53-0.033247-0.25750.398827
54-0.059313-0.45940.323791
550.0444560.34440.365892
560.0045690.03540.485944
57-0.057506-0.44540.328802
58-0.084703-0.65610.257132
590.0692660.53650.296788
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')