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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 28 Dec 2009 12:57:26 -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/28/t1262030398kt08x1xeaxoglo0.htm/, Retrieved Sun, 05 May 2024 16:22:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71046, Retrieved Sun, 05 May 2024 16:22:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [VRM Olie] [2008-12-19 13:50:37] [7458e879e85b911182071700fff19fbd]
- RM D  [Variance Reduction Matrix] [] [2009-12-28 18:04:03] [a171cf7519360d15de770637ace99f7a]
- RM D      [(Partial) Autocorrelation Function] [] [2009-12-28 19:57:26] [8dc3430f82ac55eb052bda9ec3452bd3] [Current]
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Dataseries X:
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27
2513.17
2466.92




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71046&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]2 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=71046&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71046&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2933672.25340.013982
20.077640.59640.276606
30.2221851.70660.046574
40.2405631.84780.034823
50.2524651.93920.028631
6-0.040352-0.310.378845
7-0.051907-0.39870.345775
80.1417851.08910.140275
90.0243640.18710.426095
10-0.169302-1.30040.099255
110.1146390.88060.191065
12-0.012426-0.09540.462142
13-0.039393-0.30260.381635
140.0488170.3750.354514
15-0.058522-0.44950.327353
160.0429460.32990.371331
17-0.124097-0.95320.172186
18-0.170674-1.3110.097473
190.0180370.13850.445142
20-0.09558-0.73420.232879
21-0.170992-1.31340.097064
22-0.177413-1.36270.089073
23-0.159168-1.22260.113173
24-0.116244-0.89290.187773
25-0.07093-0.54480.293964
26-0.123643-0.94970.173065
27-0.029967-0.23020.409374
280.0535750.41150.341092
29-0.034815-0.26740.395039
30-0.037619-0.2890.386814
31-0.079569-0.61120.271714
32-0.020117-0.15450.438863
33-0.039693-0.30490.380761
34-0.090533-0.69540.244768
35-0.115249-0.88520.189808
36-0.044641-0.34290.366447
37-0.007423-0.0570.477363
38-0.03327-0.25550.399594
39-0.053953-0.41440.340035
40-0.04658-0.35780.360889
410.0126550.09720.461446
420.0151030.1160.454019
430.0235980.18130.428394
44-0.007077-0.05440.478416
450.0040280.03090.48771
460.012680.09740.461372
470.0015480.01190.495275
480.0074190.0570.477375
490.0145180.11150.455793
500.0239430.18390.427358
510.0174690.13420.446859
520.0059610.04580.481816
530.0051740.03970.484218
540.019660.1510.44024
550.0183410.14090.444222
560.0094370.07250.471231
570.0006320.00490.498072
58-0.0014-0.01080.495729
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.293367 & 2.2534 & 0.013982 \tabularnewline
2 & 0.07764 & 0.5964 & 0.276606 \tabularnewline
3 & 0.222185 & 1.7066 & 0.046574 \tabularnewline
4 & 0.240563 & 1.8478 & 0.034823 \tabularnewline
5 & 0.252465 & 1.9392 & 0.028631 \tabularnewline
6 & -0.040352 & -0.31 & 0.378845 \tabularnewline
7 & -0.051907 & -0.3987 & 0.345775 \tabularnewline
8 & 0.141785 & 1.0891 & 0.140275 \tabularnewline
9 & 0.024364 & 0.1871 & 0.426095 \tabularnewline
10 & -0.169302 & -1.3004 & 0.099255 \tabularnewline
11 & 0.114639 & 0.8806 & 0.191065 \tabularnewline
12 & -0.012426 & -0.0954 & 0.462142 \tabularnewline
13 & -0.039393 & -0.3026 & 0.381635 \tabularnewline
14 & 0.048817 & 0.375 & 0.354514 \tabularnewline
15 & -0.058522 & -0.4495 & 0.327353 \tabularnewline
16 & 0.042946 & 0.3299 & 0.371331 \tabularnewline
17 & -0.124097 & -0.9532 & 0.172186 \tabularnewline
18 & -0.170674 & -1.311 & 0.097473 \tabularnewline
19 & 0.018037 & 0.1385 & 0.445142 \tabularnewline
20 & -0.09558 & -0.7342 & 0.232879 \tabularnewline
21 & -0.170992 & -1.3134 & 0.097064 \tabularnewline
22 & -0.177413 & -1.3627 & 0.089073 \tabularnewline
23 & -0.159168 & -1.2226 & 0.113173 \tabularnewline
24 & -0.116244 & -0.8929 & 0.187773 \tabularnewline
25 & -0.07093 & -0.5448 & 0.293964 \tabularnewline
26 & -0.123643 & -0.9497 & 0.173065 \tabularnewline
27 & -0.029967 & -0.2302 & 0.409374 \tabularnewline
28 & 0.053575 & 0.4115 & 0.341092 \tabularnewline
29 & -0.034815 & -0.2674 & 0.395039 \tabularnewline
30 & -0.037619 & -0.289 & 0.386814 \tabularnewline
31 & -0.079569 & -0.6112 & 0.271714 \tabularnewline
32 & -0.020117 & -0.1545 & 0.438863 \tabularnewline
33 & -0.039693 & -0.3049 & 0.380761 \tabularnewline
34 & -0.090533 & -0.6954 & 0.244768 \tabularnewline
35 & -0.115249 & -0.8852 & 0.189808 \tabularnewline
36 & -0.044641 & -0.3429 & 0.366447 \tabularnewline
37 & -0.007423 & -0.057 & 0.477363 \tabularnewline
38 & -0.03327 & -0.2555 & 0.399594 \tabularnewline
39 & -0.053953 & -0.4144 & 0.340035 \tabularnewline
40 & -0.04658 & -0.3578 & 0.360889 \tabularnewline
41 & 0.012655 & 0.0972 & 0.461446 \tabularnewline
42 & 0.015103 & 0.116 & 0.454019 \tabularnewline
43 & 0.023598 & 0.1813 & 0.428394 \tabularnewline
44 & -0.007077 & -0.0544 & 0.478416 \tabularnewline
45 & 0.004028 & 0.0309 & 0.48771 \tabularnewline
46 & 0.01268 & 0.0974 & 0.461372 \tabularnewline
47 & 0.001548 & 0.0119 & 0.495275 \tabularnewline
48 & 0.007419 & 0.057 & 0.477375 \tabularnewline
49 & 0.014518 & 0.1115 & 0.455793 \tabularnewline
50 & 0.023943 & 0.1839 & 0.427358 \tabularnewline
51 & 0.017469 & 0.1342 & 0.446859 \tabularnewline
52 & 0.005961 & 0.0458 & 0.481816 \tabularnewline
53 & 0.005174 & 0.0397 & 0.484218 \tabularnewline
54 & 0.01966 & 0.151 & 0.44024 \tabularnewline
55 & 0.018341 & 0.1409 & 0.444222 \tabularnewline
56 & 0.009437 & 0.0725 & 0.471231 \tabularnewline
57 & 0.000632 & 0.0049 & 0.498072 \tabularnewline
58 & -0.0014 & -0.0108 & 0.495729 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71046&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]0.293367[/C][C]2.2534[/C][C]0.013982[/C][/ROW]
[ROW][C]2[/C][C]0.07764[/C][C]0.5964[/C][C]0.276606[/C][/ROW]
[ROW][C]3[/C][C]0.222185[/C][C]1.7066[/C][C]0.046574[/C][/ROW]
[ROW][C]4[/C][C]0.240563[/C][C]1.8478[/C][C]0.034823[/C][/ROW]
[ROW][C]5[/C][C]0.252465[/C][C]1.9392[/C][C]0.028631[/C][/ROW]
[ROW][C]6[/C][C]-0.040352[/C][C]-0.31[/C][C]0.378845[/C][/ROW]
[ROW][C]7[/C][C]-0.051907[/C][C]-0.3987[/C][C]0.345775[/C][/ROW]
[ROW][C]8[/C][C]0.141785[/C][C]1.0891[/C][C]0.140275[/C][/ROW]
[ROW][C]9[/C][C]0.024364[/C][C]0.1871[/C][C]0.426095[/C][/ROW]
[ROW][C]10[/C][C]-0.169302[/C][C]-1.3004[/C][C]0.099255[/C][/ROW]
[ROW][C]11[/C][C]0.114639[/C][C]0.8806[/C][C]0.191065[/C][/ROW]
[ROW][C]12[/C][C]-0.012426[/C][C]-0.0954[/C][C]0.462142[/C][/ROW]
[ROW][C]13[/C][C]-0.039393[/C][C]-0.3026[/C][C]0.381635[/C][/ROW]
[ROW][C]14[/C][C]0.048817[/C][C]0.375[/C][C]0.354514[/C][/ROW]
[ROW][C]15[/C][C]-0.058522[/C][C]-0.4495[/C][C]0.327353[/C][/ROW]
[ROW][C]16[/C][C]0.042946[/C][C]0.3299[/C][C]0.371331[/C][/ROW]
[ROW][C]17[/C][C]-0.124097[/C][C]-0.9532[/C][C]0.172186[/C][/ROW]
[ROW][C]18[/C][C]-0.170674[/C][C]-1.311[/C][C]0.097473[/C][/ROW]
[ROW][C]19[/C][C]0.018037[/C][C]0.1385[/C][C]0.445142[/C][/ROW]
[ROW][C]20[/C][C]-0.09558[/C][C]-0.7342[/C][C]0.232879[/C][/ROW]
[ROW][C]21[/C][C]-0.170992[/C][C]-1.3134[/C][C]0.097064[/C][/ROW]
[ROW][C]22[/C][C]-0.177413[/C][C]-1.3627[/C][C]0.089073[/C][/ROW]
[ROW][C]23[/C][C]-0.159168[/C][C]-1.2226[/C][C]0.113173[/C][/ROW]
[ROW][C]24[/C][C]-0.116244[/C][C]-0.8929[/C][C]0.187773[/C][/ROW]
[ROW][C]25[/C][C]-0.07093[/C][C]-0.5448[/C][C]0.293964[/C][/ROW]
[ROW][C]26[/C][C]-0.123643[/C][C]-0.9497[/C][C]0.173065[/C][/ROW]
[ROW][C]27[/C][C]-0.029967[/C][C]-0.2302[/C][C]0.409374[/C][/ROW]
[ROW][C]28[/C][C]0.053575[/C][C]0.4115[/C][C]0.341092[/C][/ROW]
[ROW][C]29[/C][C]-0.034815[/C][C]-0.2674[/C][C]0.395039[/C][/ROW]
[ROW][C]30[/C][C]-0.037619[/C][C]-0.289[/C][C]0.386814[/C][/ROW]
[ROW][C]31[/C][C]-0.079569[/C][C]-0.6112[/C][C]0.271714[/C][/ROW]
[ROW][C]32[/C][C]-0.020117[/C][C]-0.1545[/C][C]0.438863[/C][/ROW]
[ROW][C]33[/C][C]-0.039693[/C][C]-0.3049[/C][C]0.380761[/C][/ROW]
[ROW][C]34[/C][C]-0.090533[/C][C]-0.6954[/C][C]0.244768[/C][/ROW]
[ROW][C]35[/C][C]-0.115249[/C][C]-0.8852[/C][C]0.189808[/C][/ROW]
[ROW][C]36[/C][C]-0.044641[/C][C]-0.3429[/C][C]0.366447[/C][/ROW]
[ROW][C]37[/C][C]-0.007423[/C][C]-0.057[/C][C]0.477363[/C][/ROW]
[ROW][C]38[/C][C]-0.03327[/C][C]-0.2555[/C][C]0.399594[/C][/ROW]
[ROW][C]39[/C][C]-0.053953[/C][C]-0.4144[/C][C]0.340035[/C][/ROW]
[ROW][C]40[/C][C]-0.04658[/C][C]-0.3578[/C][C]0.360889[/C][/ROW]
[ROW][C]41[/C][C]0.012655[/C][C]0.0972[/C][C]0.461446[/C][/ROW]
[ROW][C]42[/C][C]0.015103[/C][C]0.116[/C][C]0.454019[/C][/ROW]
[ROW][C]43[/C][C]0.023598[/C][C]0.1813[/C][C]0.428394[/C][/ROW]
[ROW][C]44[/C][C]-0.007077[/C][C]-0.0544[/C][C]0.478416[/C][/ROW]
[ROW][C]45[/C][C]0.004028[/C][C]0.0309[/C][C]0.48771[/C][/ROW]
[ROW][C]46[/C][C]0.01268[/C][C]0.0974[/C][C]0.461372[/C][/ROW]
[ROW][C]47[/C][C]0.001548[/C][C]0.0119[/C][C]0.495275[/C][/ROW]
[ROW][C]48[/C][C]0.007419[/C][C]0.057[/C][C]0.477375[/C][/ROW]
[ROW][C]49[/C][C]0.014518[/C][C]0.1115[/C][C]0.455793[/C][/ROW]
[ROW][C]50[/C][C]0.023943[/C][C]0.1839[/C][C]0.427358[/C][/ROW]
[ROW][C]51[/C][C]0.017469[/C][C]0.1342[/C][C]0.446859[/C][/ROW]
[ROW][C]52[/C][C]0.005961[/C][C]0.0458[/C][C]0.481816[/C][/ROW]
[ROW][C]53[/C][C]0.005174[/C][C]0.0397[/C][C]0.484218[/C][/ROW]
[ROW][C]54[/C][C]0.01966[/C][C]0.151[/C][C]0.44024[/C][/ROW]
[ROW][C]55[/C][C]0.018341[/C][C]0.1409[/C][C]0.444222[/C][/ROW]
[ROW][C]56[/C][C]0.009437[/C][C]0.0725[/C][C]0.471231[/C][/ROW]
[ROW][C]57[/C][C]0.000632[/C][C]0.0049[/C][C]0.498072[/C][/ROW]
[ROW][C]58[/C][C]-0.0014[/C][C]-0.0108[/C][C]0.495729[/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=71046&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71046&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
10.2933672.25340.013982
20.077640.59640.276606
30.2221851.70660.046574
40.2405631.84780.034823
50.2524651.93920.028631
6-0.040352-0.310.378845
7-0.051907-0.39870.345775
80.1417851.08910.140275
90.0243640.18710.426095
10-0.169302-1.30040.099255
110.1146390.88060.191065
12-0.012426-0.09540.462142
13-0.039393-0.30260.381635
140.0488170.3750.354514
15-0.058522-0.44950.327353
160.0429460.32990.371331
17-0.124097-0.95320.172186
18-0.170674-1.3110.097473
190.0180370.13850.445142
20-0.09558-0.73420.232879
21-0.170992-1.31340.097064
22-0.177413-1.36270.089073
23-0.159168-1.22260.113173
24-0.116244-0.89290.187773
25-0.07093-0.54480.293964
26-0.123643-0.94970.173065
27-0.029967-0.23020.409374
280.0535750.41150.341092
29-0.034815-0.26740.395039
30-0.037619-0.2890.386814
31-0.079569-0.61120.271714
32-0.020117-0.15450.438863
33-0.039693-0.30490.380761
34-0.090533-0.69540.244768
35-0.115249-0.88520.189808
36-0.044641-0.34290.366447
37-0.007423-0.0570.477363
38-0.03327-0.25550.399594
39-0.053953-0.41440.340035
40-0.04658-0.35780.360889
410.0126550.09720.461446
420.0151030.1160.454019
430.0235980.18130.428394
44-0.007077-0.05440.478416
450.0040280.03090.48771
460.012680.09740.461372
470.0015480.01190.495275
480.0074190.0570.477375
490.0145180.11150.455793
500.0239430.18390.427358
510.0174690.13420.446859
520.0059610.04580.481816
530.0051740.03970.484218
540.019660.1510.44024
550.0183410.14090.444222
560.0094370.07250.471231
570.0006320.00490.498072
58-0.0014-0.01080.495729
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2933672.25340.013982
2-0.009218-0.07080.471897
30.2209341.6970.047481
40.1326511.01890.156202
50.1746991.34190.092387
6-0.217285-1.6690.050209
7-0.057807-0.4440.329325
80.0726630.55810.289431
9-0.061318-0.4710.319691
10-0.172441-1.32450.095216
110.3081952.36730.010609
12-0.179998-1.38260.086001
130.0198720.15260.439602
140.1100280.84510.200724
15-0.056897-0.4370.33184
16-0.092939-0.71390.239058
17-0.091982-0.70650.241322
18-0.060666-0.4660.321472
19-0.006218-0.04780.481034
20-0.087256-0.67020.252663
210.0633780.48680.314096
22-0.206877-1.58910.058696
23-0.0011-0.00840.496644
24-0.045473-0.34930.36406
250.0536150.41180.340979
260.0030950.02380.490557
270.0538240.41340.340395
280.1061820.81560.209005
29-0.025131-0.1930.423797
30-0.162629-1.24920.108267
310.0159740.12270.451382
32-0.090504-0.69520.244837
33-0.084261-0.64720.259999
340.0098970.0760.469831
35-0.034761-0.2670.395199
360.0224550.17250.431825
370.0409230.31430.377187
380.0719330.55250.291338
39-0.141722-1.08860.140382
40-0.064896-0.49850.31
410.0134680.10350.458978
42-0.051069-0.39230.348137
430.0229680.17640.430284
440.0157150.12070.452166
45-0.02366-0.18170.428208
46-0.011574-0.08890.464731
47-0.05012-0.3850.350819
480.016510.12680.449757
490.0162230.12460.450627
500.041220.31660.376326
510.0158460.12170.45177
52-0.033316-0.25590.399457
53-0.048727-0.37430.354768
54-0.038271-0.2940.384909
55-0.034485-0.26490.39601
56-0.056396-0.43320.333229
57-0.090805-0.69750.244118
580.0678530.52120.302093
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.293367 & 2.2534 & 0.013982 \tabularnewline
2 & -0.009218 & -0.0708 & 0.471897 \tabularnewline
3 & 0.220934 & 1.697 & 0.047481 \tabularnewline
4 & 0.132651 & 1.0189 & 0.156202 \tabularnewline
5 & 0.174699 & 1.3419 & 0.092387 \tabularnewline
6 & -0.217285 & -1.669 & 0.050209 \tabularnewline
7 & -0.057807 & -0.444 & 0.329325 \tabularnewline
8 & 0.072663 & 0.5581 & 0.289431 \tabularnewline
9 & -0.061318 & -0.471 & 0.319691 \tabularnewline
10 & -0.172441 & -1.3245 & 0.095216 \tabularnewline
11 & 0.308195 & 2.3673 & 0.010609 \tabularnewline
12 & -0.179998 & -1.3826 & 0.086001 \tabularnewline
13 & 0.019872 & 0.1526 & 0.439602 \tabularnewline
14 & 0.110028 & 0.8451 & 0.200724 \tabularnewline
15 & -0.056897 & -0.437 & 0.33184 \tabularnewline
16 & -0.092939 & -0.7139 & 0.239058 \tabularnewline
17 & -0.091982 & -0.7065 & 0.241322 \tabularnewline
18 & -0.060666 & -0.466 & 0.321472 \tabularnewline
19 & -0.006218 & -0.0478 & 0.481034 \tabularnewline
20 & -0.087256 & -0.6702 & 0.252663 \tabularnewline
21 & 0.063378 & 0.4868 & 0.314096 \tabularnewline
22 & -0.206877 & -1.5891 & 0.058696 \tabularnewline
23 & -0.0011 & -0.0084 & 0.496644 \tabularnewline
24 & -0.045473 & -0.3493 & 0.36406 \tabularnewline
25 & 0.053615 & 0.4118 & 0.340979 \tabularnewline
26 & 0.003095 & 0.0238 & 0.490557 \tabularnewline
27 & 0.053824 & 0.4134 & 0.340395 \tabularnewline
28 & 0.106182 & 0.8156 & 0.209005 \tabularnewline
29 & -0.025131 & -0.193 & 0.423797 \tabularnewline
30 & -0.162629 & -1.2492 & 0.108267 \tabularnewline
31 & 0.015974 & 0.1227 & 0.451382 \tabularnewline
32 & -0.090504 & -0.6952 & 0.244837 \tabularnewline
33 & -0.084261 & -0.6472 & 0.259999 \tabularnewline
34 & 0.009897 & 0.076 & 0.469831 \tabularnewline
35 & -0.034761 & -0.267 & 0.395199 \tabularnewline
36 & 0.022455 & 0.1725 & 0.431825 \tabularnewline
37 & 0.040923 & 0.3143 & 0.377187 \tabularnewline
38 & 0.071933 & 0.5525 & 0.291338 \tabularnewline
39 & -0.141722 & -1.0886 & 0.140382 \tabularnewline
40 & -0.064896 & -0.4985 & 0.31 \tabularnewline
41 & 0.013468 & 0.1035 & 0.458978 \tabularnewline
42 & -0.051069 & -0.3923 & 0.348137 \tabularnewline
43 & 0.022968 & 0.1764 & 0.430284 \tabularnewline
44 & 0.015715 & 0.1207 & 0.452166 \tabularnewline
45 & -0.02366 & -0.1817 & 0.428208 \tabularnewline
46 & -0.011574 & -0.0889 & 0.464731 \tabularnewline
47 & -0.05012 & -0.385 & 0.350819 \tabularnewline
48 & 0.01651 & 0.1268 & 0.449757 \tabularnewline
49 & 0.016223 & 0.1246 & 0.450627 \tabularnewline
50 & 0.04122 & 0.3166 & 0.376326 \tabularnewline
51 & 0.015846 & 0.1217 & 0.45177 \tabularnewline
52 & -0.033316 & -0.2559 & 0.399457 \tabularnewline
53 & -0.048727 & -0.3743 & 0.354768 \tabularnewline
54 & -0.038271 & -0.294 & 0.384909 \tabularnewline
55 & -0.034485 & -0.2649 & 0.39601 \tabularnewline
56 & -0.056396 & -0.4332 & 0.333229 \tabularnewline
57 & -0.090805 & -0.6975 & 0.244118 \tabularnewline
58 & 0.067853 & 0.5212 & 0.302093 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71046&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]0.293367[/C][C]2.2534[/C][C]0.013982[/C][/ROW]
[ROW][C]2[/C][C]-0.009218[/C][C]-0.0708[/C][C]0.471897[/C][/ROW]
[ROW][C]3[/C][C]0.220934[/C][C]1.697[/C][C]0.047481[/C][/ROW]
[ROW][C]4[/C][C]0.132651[/C][C]1.0189[/C][C]0.156202[/C][/ROW]
[ROW][C]5[/C][C]0.174699[/C][C]1.3419[/C][C]0.092387[/C][/ROW]
[ROW][C]6[/C][C]-0.217285[/C][C]-1.669[/C][C]0.050209[/C][/ROW]
[ROW][C]7[/C][C]-0.057807[/C][C]-0.444[/C][C]0.329325[/C][/ROW]
[ROW][C]8[/C][C]0.072663[/C][C]0.5581[/C][C]0.289431[/C][/ROW]
[ROW][C]9[/C][C]-0.061318[/C][C]-0.471[/C][C]0.319691[/C][/ROW]
[ROW][C]10[/C][C]-0.172441[/C][C]-1.3245[/C][C]0.095216[/C][/ROW]
[ROW][C]11[/C][C]0.308195[/C][C]2.3673[/C][C]0.010609[/C][/ROW]
[ROW][C]12[/C][C]-0.179998[/C][C]-1.3826[/C][C]0.086001[/C][/ROW]
[ROW][C]13[/C][C]0.019872[/C][C]0.1526[/C][C]0.439602[/C][/ROW]
[ROW][C]14[/C][C]0.110028[/C][C]0.8451[/C][C]0.200724[/C][/ROW]
[ROW][C]15[/C][C]-0.056897[/C][C]-0.437[/C][C]0.33184[/C][/ROW]
[ROW][C]16[/C][C]-0.092939[/C][C]-0.7139[/C][C]0.239058[/C][/ROW]
[ROW][C]17[/C][C]-0.091982[/C][C]-0.7065[/C][C]0.241322[/C][/ROW]
[ROW][C]18[/C][C]-0.060666[/C][C]-0.466[/C][C]0.321472[/C][/ROW]
[ROW][C]19[/C][C]-0.006218[/C][C]-0.0478[/C][C]0.481034[/C][/ROW]
[ROW][C]20[/C][C]-0.087256[/C][C]-0.6702[/C][C]0.252663[/C][/ROW]
[ROW][C]21[/C][C]0.063378[/C][C]0.4868[/C][C]0.314096[/C][/ROW]
[ROW][C]22[/C][C]-0.206877[/C][C]-1.5891[/C][C]0.058696[/C][/ROW]
[ROW][C]23[/C][C]-0.0011[/C][C]-0.0084[/C][C]0.496644[/C][/ROW]
[ROW][C]24[/C][C]-0.045473[/C][C]-0.3493[/C][C]0.36406[/C][/ROW]
[ROW][C]25[/C][C]0.053615[/C][C]0.4118[/C][C]0.340979[/C][/ROW]
[ROW][C]26[/C][C]0.003095[/C][C]0.0238[/C][C]0.490557[/C][/ROW]
[ROW][C]27[/C][C]0.053824[/C][C]0.4134[/C][C]0.340395[/C][/ROW]
[ROW][C]28[/C][C]0.106182[/C][C]0.8156[/C][C]0.209005[/C][/ROW]
[ROW][C]29[/C][C]-0.025131[/C][C]-0.193[/C][C]0.423797[/C][/ROW]
[ROW][C]30[/C][C]-0.162629[/C][C]-1.2492[/C][C]0.108267[/C][/ROW]
[ROW][C]31[/C][C]0.015974[/C][C]0.1227[/C][C]0.451382[/C][/ROW]
[ROW][C]32[/C][C]-0.090504[/C][C]-0.6952[/C][C]0.244837[/C][/ROW]
[ROW][C]33[/C][C]-0.084261[/C][C]-0.6472[/C][C]0.259999[/C][/ROW]
[ROW][C]34[/C][C]0.009897[/C][C]0.076[/C][C]0.469831[/C][/ROW]
[ROW][C]35[/C][C]-0.034761[/C][C]-0.267[/C][C]0.395199[/C][/ROW]
[ROW][C]36[/C][C]0.022455[/C][C]0.1725[/C][C]0.431825[/C][/ROW]
[ROW][C]37[/C][C]0.040923[/C][C]0.3143[/C][C]0.377187[/C][/ROW]
[ROW][C]38[/C][C]0.071933[/C][C]0.5525[/C][C]0.291338[/C][/ROW]
[ROW][C]39[/C][C]-0.141722[/C][C]-1.0886[/C][C]0.140382[/C][/ROW]
[ROW][C]40[/C][C]-0.064896[/C][C]-0.4985[/C][C]0.31[/C][/ROW]
[ROW][C]41[/C][C]0.013468[/C][C]0.1035[/C][C]0.458978[/C][/ROW]
[ROW][C]42[/C][C]-0.051069[/C][C]-0.3923[/C][C]0.348137[/C][/ROW]
[ROW][C]43[/C][C]0.022968[/C][C]0.1764[/C][C]0.430284[/C][/ROW]
[ROW][C]44[/C][C]0.015715[/C][C]0.1207[/C][C]0.452166[/C][/ROW]
[ROW][C]45[/C][C]-0.02366[/C][C]-0.1817[/C][C]0.428208[/C][/ROW]
[ROW][C]46[/C][C]-0.011574[/C][C]-0.0889[/C][C]0.464731[/C][/ROW]
[ROW][C]47[/C][C]-0.05012[/C][C]-0.385[/C][C]0.350819[/C][/ROW]
[ROW][C]48[/C][C]0.01651[/C][C]0.1268[/C][C]0.449757[/C][/ROW]
[ROW][C]49[/C][C]0.016223[/C][C]0.1246[/C][C]0.450627[/C][/ROW]
[ROW][C]50[/C][C]0.04122[/C][C]0.3166[/C][C]0.376326[/C][/ROW]
[ROW][C]51[/C][C]0.015846[/C][C]0.1217[/C][C]0.45177[/C][/ROW]
[ROW][C]52[/C][C]-0.033316[/C][C]-0.2559[/C][C]0.399457[/C][/ROW]
[ROW][C]53[/C][C]-0.048727[/C][C]-0.3743[/C][C]0.354768[/C][/ROW]
[ROW][C]54[/C][C]-0.038271[/C][C]-0.294[/C][C]0.384909[/C][/ROW]
[ROW][C]55[/C][C]-0.034485[/C][C]-0.2649[/C][C]0.39601[/C][/ROW]
[ROW][C]56[/C][C]-0.056396[/C][C]-0.4332[/C][C]0.333229[/C][/ROW]
[ROW][C]57[/C][C]-0.090805[/C][C]-0.6975[/C][C]0.244118[/C][/ROW]
[ROW][C]58[/C][C]0.067853[/C][C]0.5212[/C][C]0.302093[/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=71046&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71046&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
10.2933672.25340.013982
2-0.009218-0.07080.471897
30.2209341.6970.047481
40.1326511.01890.156202
50.1746991.34190.092387
6-0.217285-1.6690.050209
7-0.057807-0.4440.329325
80.0726630.55810.289431
9-0.061318-0.4710.319691
10-0.172441-1.32450.095216
110.3081952.36730.010609
12-0.179998-1.38260.086001
130.0198720.15260.439602
140.1100280.84510.200724
15-0.056897-0.4370.33184
16-0.092939-0.71390.239058
17-0.091982-0.70650.241322
18-0.060666-0.4660.321472
19-0.006218-0.04780.481034
20-0.087256-0.67020.252663
210.0633780.48680.314096
22-0.206877-1.58910.058696
23-0.0011-0.00840.496644
24-0.045473-0.34930.36406
250.0536150.41180.340979
260.0030950.02380.490557
270.0538240.41340.340395
280.1061820.81560.209005
29-0.025131-0.1930.423797
30-0.162629-1.24920.108267
310.0159740.12270.451382
32-0.090504-0.69520.244837
33-0.084261-0.64720.259999
340.0098970.0760.469831
35-0.034761-0.2670.395199
360.0224550.17250.431825
370.0409230.31430.377187
380.0719330.55250.291338
39-0.141722-1.08860.140382
40-0.064896-0.49850.31
410.0134680.10350.458978
42-0.051069-0.39230.348137
430.0229680.17640.430284
440.0157150.12070.452166
45-0.02366-0.18170.428208
46-0.011574-0.08890.464731
47-0.05012-0.3850.350819
480.016510.12680.449757
490.0162230.12460.450627
500.041220.31660.376326
510.0158460.12170.45177
52-0.033316-0.25590.399457
53-0.048727-0.37430.354768
54-0.038271-0.2940.384909
55-0.034485-0.26490.39601
56-0.056396-0.43320.333229
57-0.090805-0.69750.244118
580.0678530.52120.302093
59NANANA
60NANANA



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 0.9 ; 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')