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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 computationMon, 08 Dec 2008 11:21:00 -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/2008/Dec/08/t1228760500kitj9bkppjti7g8.htm/, Retrieved Thu, 16 May 2024 21:54:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30642, Retrieved Thu, 16 May 2024 21:54:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [ACF] [2008-12-05 06:53:00] [c5a66f1c8528a963efc2b82a8519f117]
-    D    [(Partial) Autocorrelation Function] [ACF bouwvergunnin...] [2008-12-05 13:00:50] [c5a66f1c8528a963efc2b82a8519f117]
-    D        [(Partial) Autocorrelation Function] [ACF - woninghuur] [2008-12-08 18:21:00] [b4fc5040f26b33db57f84cfb8d1d2b82] [Current]
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Dataseries X:
106,6
106,8
107
107,1
107,3
107,4
107,6
107,7
107,9
108,2
108,3
108,5
108,92
109,23
109,41
109,65
109,91
110,01
110,2
110,49
110,57
110,72
110,94
111,09
111,28
111,41
111,62
111,76
111,89
112,04
112,12
112,3
112,47
112,59
112,78
112,73
112,99
113,1
113,33
113,38
113,68
113,65
113,81
113,88
114,02
114,25
114,28
114,38
114,73
114,97
115,05
115,29
115,37
115,54
115,76
115,92
116,02
116,21
116,26
116,51




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30642&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30642&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9479857.34310
20.8973776.95110
30.8460286.55330
40.7942166.1520
50.7421675.74880
60.6896615.34211e-06
70.6381614.94323e-06
80.5863544.54191.4e-05
90.5344614.13995.5e-05
100.4851923.75830.000195
110.4349133.36880.000662
120.3861582.99120.002014
130.3426052.65380.005087
140.3008712.33050.011579
150.2588652.00520.024732
160.2191791.69780.047368
170.1814571.40560.082506
180.1431021.10850.136043
190.1061630.82230.207072
200.0698690.54120.295187
210.0352670.27320.392828
220.0006120.00470.498117
23-0.031444-0.24360.4042
24-0.062816-0.48660.314168
25-0.091516-0.70890.240571
26-0.121242-0.93910.175712
27-0.148708-1.15190.126968
28-0.175309-1.35790.089784
29-0.200604-1.55390.062737
30-0.224238-1.73690.043765
31-0.247939-1.92050.029774
32-0.269816-2.090.020433
33-0.29029-2.24860.014112
34-0.309695-2.39890.009785
35-0.326476-2.52890.007045
36-0.34404-2.66490.004939
37-0.358657-2.77810.003643
38-0.372002-2.88150.002741
39-0.382097-2.95970.002202
40-0.391541-3.03290.001788
41-0.398247-3.08480.001539
42-0.403668-3.12680.001362
43-0.406703-3.15030.001272
44-0.409121-3.1690.001204
45-0.408574-3.16480.001219
46-0.404224-3.13110.001345
47-0.398707-3.08840.001523
48-0.390065-3.02140.001847
49-0.374364-2.89980.002605
50-0.354727-2.74770.003957
51-0.333831-2.58580.00608
52-0.307966-2.38550.010115
53-0.279693-2.16650.017128
54-0.249035-1.9290.029231
55-0.214366-1.66050.051019
56-0.177284-1.37320.087394
57-0.137391-1.06420.145745
58-0.094662-0.73320.233132
59-0.049603-0.38420.351087
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.947985 & 7.3431 & 0 \tabularnewline
2 & 0.897377 & 6.9511 & 0 \tabularnewline
3 & 0.846028 & 6.5533 & 0 \tabularnewline
4 & 0.794216 & 6.152 & 0 \tabularnewline
5 & 0.742167 & 5.7488 & 0 \tabularnewline
6 & 0.689661 & 5.3421 & 1e-06 \tabularnewline
7 & 0.638161 & 4.9432 & 3e-06 \tabularnewline
8 & 0.586354 & 4.5419 & 1.4e-05 \tabularnewline
9 & 0.534461 & 4.1399 & 5.5e-05 \tabularnewline
10 & 0.485192 & 3.7583 & 0.000195 \tabularnewline
11 & 0.434913 & 3.3688 & 0.000662 \tabularnewline
12 & 0.386158 & 2.9912 & 0.002014 \tabularnewline
13 & 0.342605 & 2.6538 & 0.005087 \tabularnewline
14 & 0.300871 & 2.3305 & 0.011579 \tabularnewline
15 & 0.258865 & 2.0052 & 0.024732 \tabularnewline
16 & 0.219179 & 1.6978 & 0.047368 \tabularnewline
17 & 0.181457 & 1.4056 & 0.082506 \tabularnewline
18 & 0.143102 & 1.1085 & 0.136043 \tabularnewline
19 & 0.106163 & 0.8223 & 0.207072 \tabularnewline
20 & 0.069869 & 0.5412 & 0.295187 \tabularnewline
21 & 0.035267 & 0.2732 & 0.392828 \tabularnewline
22 & 0.000612 & 0.0047 & 0.498117 \tabularnewline
23 & -0.031444 & -0.2436 & 0.4042 \tabularnewline
24 & -0.062816 & -0.4866 & 0.314168 \tabularnewline
25 & -0.091516 & -0.7089 & 0.240571 \tabularnewline
26 & -0.121242 & -0.9391 & 0.175712 \tabularnewline
27 & -0.148708 & -1.1519 & 0.126968 \tabularnewline
28 & -0.175309 & -1.3579 & 0.089784 \tabularnewline
29 & -0.200604 & -1.5539 & 0.062737 \tabularnewline
30 & -0.224238 & -1.7369 & 0.043765 \tabularnewline
31 & -0.247939 & -1.9205 & 0.029774 \tabularnewline
32 & -0.269816 & -2.09 & 0.020433 \tabularnewline
33 & -0.29029 & -2.2486 & 0.014112 \tabularnewline
34 & -0.309695 & -2.3989 & 0.009785 \tabularnewline
35 & -0.326476 & -2.5289 & 0.007045 \tabularnewline
36 & -0.34404 & -2.6649 & 0.004939 \tabularnewline
37 & -0.358657 & -2.7781 & 0.003643 \tabularnewline
38 & -0.372002 & -2.8815 & 0.002741 \tabularnewline
39 & -0.382097 & -2.9597 & 0.002202 \tabularnewline
40 & -0.391541 & -3.0329 & 0.001788 \tabularnewline
41 & -0.398247 & -3.0848 & 0.001539 \tabularnewline
42 & -0.403668 & -3.1268 & 0.001362 \tabularnewline
43 & -0.406703 & -3.1503 & 0.001272 \tabularnewline
44 & -0.409121 & -3.169 & 0.001204 \tabularnewline
45 & -0.408574 & -3.1648 & 0.001219 \tabularnewline
46 & -0.404224 & -3.1311 & 0.001345 \tabularnewline
47 & -0.398707 & -3.0884 & 0.001523 \tabularnewline
48 & -0.390065 & -3.0214 & 0.001847 \tabularnewline
49 & -0.374364 & -2.8998 & 0.002605 \tabularnewline
50 & -0.354727 & -2.7477 & 0.003957 \tabularnewline
51 & -0.333831 & -2.5858 & 0.00608 \tabularnewline
52 & -0.307966 & -2.3855 & 0.010115 \tabularnewline
53 & -0.279693 & -2.1665 & 0.017128 \tabularnewline
54 & -0.249035 & -1.929 & 0.029231 \tabularnewline
55 & -0.214366 & -1.6605 & 0.051019 \tabularnewline
56 & -0.177284 & -1.3732 & 0.087394 \tabularnewline
57 & -0.137391 & -1.0642 & 0.145745 \tabularnewline
58 & -0.094662 & -0.7332 & 0.233132 \tabularnewline
59 & -0.049603 & -0.3842 & 0.351087 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30642&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]0.947985[/C][C]7.3431[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.897377[/C][C]6.9511[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.846028[/C][C]6.5533[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.794216[/C][C]6.152[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.742167[/C][C]5.7488[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.689661[/C][C]5.3421[/C][C]1e-06[/C][/ROW]
[ROW][C]7[/C][C]0.638161[/C][C]4.9432[/C][C]3e-06[/C][/ROW]
[ROW][C]8[/C][C]0.586354[/C][C]4.5419[/C][C]1.4e-05[/C][/ROW]
[ROW][C]9[/C][C]0.534461[/C][C]4.1399[/C][C]5.5e-05[/C][/ROW]
[ROW][C]10[/C][C]0.485192[/C][C]3.7583[/C][C]0.000195[/C][/ROW]
[ROW][C]11[/C][C]0.434913[/C][C]3.3688[/C][C]0.000662[/C][/ROW]
[ROW][C]12[/C][C]0.386158[/C][C]2.9912[/C][C]0.002014[/C][/ROW]
[ROW][C]13[/C][C]0.342605[/C][C]2.6538[/C][C]0.005087[/C][/ROW]
[ROW][C]14[/C][C]0.300871[/C][C]2.3305[/C][C]0.011579[/C][/ROW]
[ROW][C]15[/C][C]0.258865[/C][C]2.0052[/C][C]0.024732[/C][/ROW]
[ROW][C]16[/C][C]0.219179[/C][C]1.6978[/C][C]0.047368[/C][/ROW]
[ROW][C]17[/C][C]0.181457[/C][C]1.4056[/C][C]0.082506[/C][/ROW]
[ROW][C]18[/C][C]0.143102[/C][C]1.1085[/C][C]0.136043[/C][/ROW]
[ROW][C]19[/C][C]0.106163[/C][C]0.8223[/C][C]0.207072[/C][/ROW]
[ROW][C]20[/C][C]0.069869[/C][C]0.5412[/C][C]0.295187[/C][/ROW]
[ROW][C]21[/C][C]0.035267[/C][C]0.2732[/C][C]0.392828[/C][/ROW]
[ROW][C]22[/C][C]0.000612[/C][C]0.0047[/C][C]0.498117[/C][/ROW]
[ROW][C]23[/C][C]-0.031444[/C][C]-0.2436[/C][C]0.4042[/C][/ROW]
[ROW][C]24[/C][C]-0.062816[/C][C]-0.4866[/C][C]0.314168[/C][/ROW]
[ROW][C]25[/C][C]-0.091516[/C][C]-0.7089[/C][C]0.240571[/C][/ROW]
[ROW][C]26[/C][C]-0.121242[/C][C]-0.9391[/C][C]0.175712[/C][/ROW]
[ROW][C]27[/C][C]-0.148708[/C][C]-1.1519[/C][C]0.126968[/C][/ROW]
[ROW][C]28[/C][C]-0.175309[/C][C]-1.3579[/C][C]0.089784[/C][/ROW]
[ROW][C]29[/C][C]-0.200604[/C][C]-1.5539[/C][C]0.062737[/C][/ROW]
[ROW][C]30[/C][C]-0.224238[/C][C]-1.7369[/C][C]0.043765[/C][/ROW]
[ROW][C]31[/C][C]-0.247939[/C][C]-1.9205[/C][C]0.029774[/C][/ROW]
[ROW][C]32[/C][C]-0.269816[/C][C]-2.09[/C][C]0.020433[/C][/ROW]
[ROW][C]33[/C][C]-0.29029[/C][C]-2.2486[/C][C]0.014112[/C][/ROW]
[ROW][C]34[/C][C]-0.309695[/C][C]-2.3989[/C][C]0.009785[/C][/ROW]
[ROW][C]35[/C][C]-0.326476[/C][C]-2.5289[/C][C]0.007045[/C][/ROW]
[ROW][C]36[/C][C]-0.34404[/C][C]-2.6649[/C][C]0.004939[/C][/ROW]
[ROW][C]37[/C][C]-0.358657[/C][C]-2.7781[/C][C]0.003643[/C][/ROW]
[ROW][C]38[/C][C]-0.372002[/C][C]-2.8815[/C][C]0.002741[/C][/ROW]
[ROW][C]39[/C][C]-0.382097[/C][C]-2.9597[/C][C]0.002202[/C][/ROW]
[ROW][C]40[/C][C]-0.391541[/C][C]-3.0329[/C][C]0.001788[/C][/ROW]
[ROW][C]41[/C][C]-0.398247[/C][C]-3.0848[/C][C]0.001539[/C][/ROW]
[ROW][C]42[/C][C]-0.403668[/C][C]-3.1268[/C][C]0.001362[/C][/ROW]
[ROW][C]43[/C][C]-0.406703[/C][C]-3.1503[/C][C]0.001272[/C][/ROW]
[ROW][C]44[/C][C]-0.409121[/C][C]-3.169[/C][C]0.001204[/C][/ROW]
[ROW][C]45[/C][C]-0.408574[/C][C]-3.1648[/C][C]0.001219[/C][/ROW]
[ROW][C]46[/C][C]-0.404224[/C][C]-3.1311[/C][C]0.001345[/C][/ROW]
[ROW][C]47[/C][C]-0.398707[/C][C]-3.0884[/C][C]0.001523[/C][/ROW]
[ROW][C]48[/C][C]-0.390065[/C][C]-3.0214[/C][C]0.001847[/C][/ROW]
[ROW][C]49[/C][C]-0.374364[/C][C]-2.8998[/C][C]0.002605[/C][/ROW]
[ROW][C]50[/C][C]-0.354727[/C][C]-2.7477[/C][C]0.003957[/C][/ROW]
[ROW][C]51[/C][C]-0.333831[/C][C]-2.5858[/C][C]0.00608[/C][/ROW]
[ROW][C]52[/C][C]-0.307966[/C][C]-2.3855[/C][C]0.010115[/C][/ROW]
[ROW][C]53[/C][C]-0.279693[/C][C]-2.1665[/C][C]0.017128[/C][/ROW]
[ROW][C]54[/C][C]-0.249035[/C][C]-1.929[/C][C]0.029231[/C][/ROW]
[ROW][C]55[/C][C]-0.214366[/C][C]-1.6605[/C][C]0.051019[/C][/ROW]
[ROW][C]56[/C][C]-0.177284[/C][C]-1.3732[/C][C]0.087394[/C][/ROW]
[ROW][C]57[/C][C]-0.137391[/C][C]-1.0642[/C][C]0.145745[/C][/ROW]
[ROW][C]58[/C][C]-0.094662[/C][C]-0.7332[/C][C]0.233132[/C][/ROW]
[ROW][C]59[/C][C]-0.049603[/C][C]-0.3842[/C][C]0.351087[/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=30642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30642&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
10.9479857.34310
20.8973776.95110
30.8460286.55330
40.7942166.1520
50.7421675.74880
60.6896615.34211e-06
70.6381614.94323e-06
80.5863544.54191.4e-05
90.5344614.13995.5e-05
100.4851923.75830.000195
110.4349133.36880.000662
120.3861582.99120.002014
130.3426052.65380.005087
140.3008712.33050.011579
150.2588652.00520.024732
160.2191791.69780.047368
170.1814571.40560.082506
180.1431021.10850.136043
190.1061630.82230.207072
200.0698690.54120.295187
210.0352670.27320.392828
220.0006120.00470.498117
23-0.031444-0.24360.4042
24-0.062816-0.48660.314168
25-0.091516-0.70890.240571
26-0.121242-0.93910.175712
27-0.148708-1.15190.126968
28-0.175309-1.35790.089784
29-0.200604-1.55390.062737
30-0.224238-1.73690.043765
31-0.247939-1.92050.029774
32-0.269816-2.090.020433
33-0.29029-2.24860.014112
34-0.309695-2.39890.009785
35-0.326476-2.52890.007045
36-0.34404-2.66490.004939
37-0.358657-2.77810.003643
38-0.372002-2.88150.002741
39-0.382097-2.95970.002202
40-0.391541-3.03290.001788
41-0.398247-3.08480.001539
42-0.403668-3.12680.001362
43-0.406703-3.15030.001272
44-0.409121-3.1690.001204
45-0.408574-3.16480.001219
46-0.404224-3.13110.001345
47-0.398707-3.08840.001523
48-0.390065-3.02140.001847
49-0.374364-2.89980.002605
50-0.354727-2.74770.003957
51-0.333831-2.58580.00608
52-0.307966-2.38550.010115
53-0.279693-2.16650.017128
54-0.249035-1.9290.029231
55-0.214366-1.66050.051019
56-0.177284-1.37320.087394
57-0.137391-1.06420.145745
58-0.094662-0.73320.233132
59-0.049603-0.38420.351087
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9479857.34310
2-0.012806-0.09920.460658
3-0.033816-0.26190.397134
4-0.032577-0.25230.400819
5-0.031301-0.24250.404625
6-0.034395-0.26640.395412
7-0.02118-0.16410.435117
8-0.034139-0.26440.396174
9-0.033677-0.26090.397546
10-0.007774-0.06020.476092
11-0.042563-0.32970.371392
12-0.020528-0.1590.437098
130.0170050.13170.447824
14-0.013679-0.1060.457986
15-0.035966-0.27860.390757
16-0.011138-0.08630.465768
17-0.014228-0.11020.456304
18-0.039814-0.30840.379424
19-0.020101-0.15570.438394
20-0.028964-0.22440.411621
21-0.018875-0.14620.442124
22-0.033772-0.26160.397263
23-0.011106-0.0860.465865
24-0.028694-0.22230.412433
25-0.006322-0.0490.480552
26-0.044036-0.34110.367109
27-0.016285-0.12610.45002
28-0.025686-0.1990.421481
29-0.022567-0.17480.430913
30-0.021267-0.16470.434853
31-0.037403-0.28970.386515
32-0.019128-0.14820.441356
33-0.023587-0.18270.427825
34-0.026489-0.20520.419062
35-0.011771-0.09120.463828
36-0.042636-0.33030.371178
37-0.009439-0.07310.470979
38-0.024577-0.19040.424829
39-0.003598-0.02790.48893
40-0.028733-0.22260.412314
41-0.007218-0.05590.477798
42-0.022179-0.17180.432088
43-0.009329-0.07230.471317
44-0.0263-0.20370.41963
45-0.002241-0.01740.493105
460.0082370.06380.47467
47-0.01368-0.1060.457981
480.0040690.03150.48748
490.0486960.37720.353678
500.0253380.19630.422531
510.0010990.00850.496618
520.0394520.30560.380487
530.020120.15580.438337
540.0229170.17750.429851
550.0442990.34310.366346
560.0310190.24030.405469
570.0422990.32760.372158
580.0493230.38210.351886
590.0476460.36910.35669
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.947985 & 7.3431 & 0 \tabularnewline
2 & -0.012806 & -0.0992 & 0.460658 \tabularnewline
3 & -0.033816 & -0.2619 & 0.397134 \tabularnewline
4 & -0.032577 & -0.2523 & 0.400819 \tabularnewline
5 & -0.031301 & -0.2425 & 0.404625 \tabularnewline
6 & -0.034395 & -0.2664 & 0.395412 \tabularnewline
7 & -0.02118 & -0.1641 & 0.435117 \tabularnewline
8 & -0.034139 & -0.2644 & 0.396174 \tabularnewline
9 & -0.033677 & -0.2609 & 0.397546 \tabularnewline
10 & -0.007774 & -0.0602 & 0.476092 \tabularnewline
11 & -0.042563 & -0.3297 & 0.371392 \tabularnewline
12 & -0.020528 & -0.159 & 0.437098 \tabularnewline
13 & 0.017005 & 0.1317 & 0.447824 \tabularnewline
14 & -0.013679 & -0.106 & 0.457986 \tabularnewline
15 & -0.035966 & -0.2786 & 0.390757 \tabularnewline
16 & -0.011138 & -0.0863 & 0.465768 \tabularnewline
17 & -0.014228 & -0.1102 & 0.456304 \tabularnewline
18 & -0.039814 & -0.3084 & 0.379424 \tabularnewline
19 & -0.020101 & -0.1557 & 0.438394 \tabularnewline
20 & -0.028964 & -0.2244 & 0.411621 \tabularnewline
21 & -0.018875 & -0.1462 & 0.442124 \tabularnewline
22 & -0.033772 & -0.2616 & 0.397263 \tabularnewline
23 & -0.011106 & -0.086 & 0.465865 \tabularnewline
24 & -0.028694 & -0.2223 & 0.412433 \tabularnewline
25 & -0.006322 & -0.049 & 0.480552 \tabularnewline
26 & -0.044036 & -0.3411 & 0.367109 \tabularnewline
27 & -0.016285 & -0.1261 & 0.45002 \tabularnewline
28 & -0.025686 & -0.199 & 0.421481 \tabularnewline
29 & -0.022567 & -0.1748 & 0.430913 \tabularnewline
30 & -0.021267 & -0.1647 & 0.434853 \tabularnewline
31 & -0.037403 & -0.2897 & 0.386515 \tabularnewline
32 & -0.019128 & -0.1482 & 0.441356 \tabularnewline
33 & -0.023587 & -0.1827 & 0.427825 \tabularnewline
34 & -0.026489 & -0.2052 & 0.419062 \tabularnewline
35 & -0.011771 & -0.0912 & 0.463828 \tabularnewline
36 & -0.042636 & -0.3303 & 0.371178 \tabularnewline
37 & -0.009439 & -0.0731 & 0.470979 \tabularnewline
38 & -0.024577 & -0.1904 & 0.424829 \tabularnewline
39 & -0.003598 & -0.0279 & 0.48893 \tabularnewline
40 & -0.028733 & -0.2226 & 0.412314 \tabularnewline
41 & -0.007218 & -0.0559 & 0.477798 \tabularnewline
42 & -0.022179 & -0.1718 & 0.432088 \tabularnewline
43 & -0.009329 & -0.0723 & 0.471317 \tabularnewline
44 & -0.0263 & -0.2037 & 0.41963 \tabularnewline
45 & -0.002241 & -0.0174 & 0.493105 \tabularnewline
46 & 0.008237 & 0.0638 & 0.47467 \tabularnewline
47 & -0.01368 & -0.106 & 0.457981 \tabularnewline
48 & 0.004069 & 0.0315 & 0.48748 \tabularnewline
49 & 0.048696 & 0.3772 & 0.353678 \tabularnewline
50 & 0.025338 & 0.1963 & 0.422531 \tabularnewline
51 & 0.001099 & 0.0085 & 0.496618 \tabularnewline
52 & 0.039452 & 0.3056 & 0.380487 \tabularnewline
53 & 0.02012 & 0.1558 & 0.438337 \tabularnewline
54 & 0.022917 & 0.1775 & 0.429851 \tabularnewline
55 & 0.044299 & 0.3431 & 0.366346 \tabularnewline
56 & 0.031019 & 0.2403 & 0.405469 \tabularnewline
57 & 0.042299 & 0.3276 & 0.372158 \tabularnewline
58 & 0.049323 & 0.3821 & 0.351886 \tabularnewline
59 & 0.047646 & 0.3691 & 0.35669 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30642&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]0.947985[/C][C]7.3431[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.012806[/C][C]-0.0992[/C][C]0.460658[/C][/ROW]
[ROW][C]3[/C][C]-0.033816[/C][C]-0.2619[/C][C]0.397134[/C][/ROW]
[ROW][C]4[/C][C]-0.032577[/C][C]-0.2523[/C][C]0.400819[/C][/ROW]
[ROW][C]5[/C][C]-0.031301[/C][C]-0.2425[/C][C]0.404625[/C][/ROW]
[ROW][C]6[/C][C]-0.034395[/C][C]-0.2664[/C][C]0.395412[/C][/ROW]
[ROW][C]7[/C][C]-0.02118[/C][C]-0.1641[/C][C]0.435117[/C][/ROW]
[ROW][C]8[/C][C]-0.034139[/C][C]-0.2644[/C][C]0.396174[/C][/ROW]
[ROW][C]9[/C][C]-0.033677[/C][C]-0.2609[/C][C]0.397546[/C][/ROW]
[ROW][C]10[/C][C]-0.007774[/C][C]-0.0602[/C][C]0.476092[/C][/ROW]
[ROW][C]11[/C][C]-0.042563[/C][C]-0.3297[/C][C]0.371392[/C][/ROW]
[ROW][C]12[/C][C]-0.020528[/C][C]-0.159[/C][C]0.437098[/C][/ROW]
[ROW][C]13[/C][C]0.017005[/C][C]0.1317[/C][C]0.447824[/C][/ROW]
[ROW][C]14[/C][C]-0.013679[/C][C]-0.106[/C][C]0.457986[/C][/ROW]
[ROW][C]15[/C][C]-0.035966[/C][C]-0.2786[/C][C]0.390757[/C][/ROW]
[ROW][C]16[/C][C]-0.011138[/C][C]-0.0863[/C][C]0.465768[/C][/ROW]
[ROW][C]17[/C][C]-0.014228[/C][C]-0.1102[/C][C]0.456304[/C][/ROW]
[ROW][C]18[/C][C]-0.039814[/C][C]-0.3084[/C][C]0.379424[/C][/ROW]
[ROW][C]19[/C][C]-0.020101[/C][C]-0.1557[/C][C]0.438394[/C][/ROW]
[ROW][C]20[/C][C]-0.028964[/C][C]-0.2244[/C][C]0.411621[/C][/ROW]
[ROW][C]21[/C][C]-0.018875[/C][C]-0.1462[/C][C]0.442124[/C][/ROW]
[ROW][C]22[/C][C]-0.033772[/C][C]-0.2616[/C][C]0.397263[/C][/ROW]
[ROW][C]23[/C][C]-0.011106[/C][C]-0.086[/C][C]0.465865[/C][/ROW]
[ROW][C]24[/C][C]-0.028694[/C][C]-0.2223[/C][C]0.412433[/C][/ROW]
[ROW][C]25[/C][C]-0.006322[/C][C]-0.049[/C][C]0.480552[/C][/ROW]
[ROW][C]26[/C][C]-0.044036[/C][C]-0.3411[/C][C]0.367109[/C][/ROW]
[ROW][C]27[/C][C]-0.016285[/C][C]-0.1261[/C][C]0.45002[/C][/ROW]
[ROW][C]28[/C][C]-0.025686[/C][C]-0.199[/C][C]0.421481[/C][/ROW]
[ROW][C]29[/C][C]-0.022567[/C][C]-0.1748[/C][C]0.430913[/C][/ROW]
[ROW][C]30[/C][C]-0.021267[/C][C]-0.1647[/C][C]0.434853[/C][/ROW]
[ROW][C]31[/C][C]-0.037403[/C][C]-0.2897[/C][C]0.386515[/C][/ROW]
[ROW][C]32[/C][C]-0.019128[/C][C]-0.1482[/C][C]0.441356[/C][/ROW]
[ROW][C]33[/C][C]-0.023587[/C][C]-0.1827[/C][C]0.427825[/C][/ROW]
[ROW][C]34[/C][C]-0.026489[/C][C]-0.2052[/C][C]0.419062[/C][/ROW]
[ROW][C]35[/C][C]-0.011771[/C][C]-0.0912[/C][C]0.463828[/C][/ROW]
[ROW][C]36[/C][C]-0.042636[/C][C]-0.3303[/C][C]0.371178[/C][/ROW]
[ROW][C]37[/C][C]-0.009439[/C][C]-0.0731[/C][C]0.470979[/C][/ROW]
[ROW][C]38[/C][C]-0.024577[/C][C]-0.1904[/C][C]0.424829[/C][/ROW]
[ROW][C]39[/C][C]-0.003598[/C][C]-0.0279[/C][C]0.48893[/C][/ROW]
[ROW][C]40[/C][C]-0.028733[/C][C]-0.2226[/C][C]0.412314[/C][/ROW]
[ROW][C]41[/C][C]-0.007218[/C][C]-0.0559[/C][C]0.477798[/C][/ROW]
[ROW][C]42[/C][C]-0.022179[/C][C]-0.1718[/C][C]0.432088[/C][/ROW]
[ROW][C]43[/C][C]-0.009329[/C][C]-0.0723[/C][C]0.471317[/C][/ROW]
[ROW][C]44[/C][C]-0.0263[/C][C]-0.2037[/C][C]0.41963[/C][/ROW]
[ROW][C]45[/C][C]-0.002241[/C][C]-0.0174[/C][C]0.493105[/C][/ROW]
[ROW][C]46[/C][C]0.008237[/C][C]0.0638[/C][C]0.47467[/C][/ROW]
[ROW][C]47[/C][C]-0.01368[/C][C]-0.106[/C][C]0.457981[/C][/ROW]
[ROW][C]48[/C][C]0.004069[/C][C]0.0315[/C][C]0.48748[/C][/ROW]
[ROW][C]49[/C][C]0.048696[/C][C]0.3772[/C][C]0.353678[/C][/ROW]
[ROW][C]50[/C][C]0.025338[/C][C]0.1963[/C][C]0.422531[/C][/ROW]
[ROW][C]51[/C][C]0.001099[/C][C]0.0085[/C][C]0.496618[/C][/ROW]
[ROW][C]52[/C][C]0.039452[/C][C]0.3056[/C][C]0.380487[/C][/ROW]
[ROW][C]53[/C][C]0.02012[/C][C]0.1558[/C][C]0.438337[/C][/ROW]
[ROW][C]54[/C][C]0.022917[/C][C]0.1775[/C][C]0.429851[/C][/ROW]
[ROW][C]55[/C][C]0.044299[/C][C]0.3431[/C][C]0.366346[/C][/ROW]
[ROW][C]56[/C][C]0.031019[/C][C]0.2403[/C][C]0.405469[/C][/ROW]
[ROW][C]57[/C][C]0.042299[/C][C]0.3276[/C][C]0.372158[/C][/ROW]
[ROW][C]58[/C][C]0.049323[/C][C]0.3821[/C][C]0.351886[/C][/ROW]
[ROW][C]59[/C][C]0.047646[/C][C]0.3691[/C][C]0.35669[/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=30642&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30642&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
10.9479857.34310
2-0.012806-0.09920.460658
3-0.033816-0.26190.397134
4-0.032577-0.25230.400819
5-0.031301-0.24250.404625
6-0.034395-0.26640.395412
7-0.02118-0.16410.435117
8-0.034139-0.26440.396174
9-0.033677-0.26090.397546
10-0.007774-0.06020.476092
11-0.042563-0.32970.371392
12-0.020528-0.1590.437098
130.0170050.13170.447824
14-0.013679-0.1060.457986
15-0.035966-0.27860.390757
16-0.011138-0.08630.465768
17-0.014228-0.11020.456304
18-0.039814-0.30840.379424
19-0.020101-0.15570.438394
20-0.028964-0.22440.411621
21-0.018875-0.14620.442124
22-0.033772-0.26160.397263
23-0.011106-0.0860.465865
24-0.028694-0.22230.412433
25-0.006322-0.0490.480552
26-0.044036-0.34110.367109
27-0.016285-0.12610.45002
28-0.025686-0.1990.421481
29-0.022567-0.17480.430913
30-0.021267-0.16470.434853
31-0.037403-0.28970.386515
32-0.019128-0.14820.441356
33-0.023587-0.18270.427825
34-0.026489-0.20520.419062
35-0.011771-0.09120.463828
36-0.042636-0.33030.371178
37-0.009439-0.07310.470979
38-0.024577-0.19040.424829
39-0.003598-0.02790.48893
40-0.028733-0.22260.412314
41-0.007218-0.05590.477798
42-0.022179-0.17180.432088
43-0.009329-0.07230.471317
44-0.0263-0.20370.41963
45-0.002241-0.01740.493105
460.0082370.06380.47467
47-0.01368-0.1060.457981
480.0040690.03150.48748
490.0486960.37720.353678
500.0253380.19630.422531
510.0010990.00850.496618
520.0394520.30560.380487
530.020120.15580.438337
540.0229170.17750.429851
550.0442990.34310.366346
560.0310190.24030.405469
570.0422990.32760.372158
580.0493230.38210.351886
590.0476460.36910.35669
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')