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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 09:59:53 -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/t1262192540hmyu11t57l58z09.htm/, Retrieved Sun, 28 Apr 2024 21:13:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71330, Retrieved Sun, 28 Apr 2024 21:13:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [arima backward se...] [2008-12-17 10:56:10] [11edab5c4db3615abbf782b1c6e7cacf]
- RMPD  [Central Tendency] [central tendency ...] [2008-12-23 10:31:31] [74be16979710d4c4e7c6647856088456]
- RMPD    [ARIMA Forecasting] [paper arima forec...] [2009-12-30 15:31:43] [db72903d7941c8279d5ce0e4e873d517]
- RMPD        [(Partial) Autocorrelation Function] [paper pacf export] [2009-12-30 16:59:53] [90d336e5f53609c0c5a6217e988a780d] [Current]
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Dataseries X:
4223,4
4627,3
5175,3
4550,7
4639,3
5498,7
5031,0
4033,3
4643,5
4873,2
4608,7
4733,5
3955,6
4590,9
5127,5
5257,3
5416,9
5813,3
5261,9
4669,2
5855,8
5274,6
5516,7
5819,5
5156,0
5377,3
6386,8
5144,0
6138,5
5567,8
5822,6
5145,5
5706,6
6078,5
6074,5
5577,6
5727,5
6067,0
7069,9
5490,0
5948,3
6177,5
6890,1
5756,2
6528,8
6792,0
6657,4
5753,7
5750,9
5968,4
5871,7
7004,9
6363,4
6694,7
7101,6
5364,0
6958,6
6503,3
5316,0
5312,7
4478,0




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=71330&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=71330&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71330&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
10.2517571.76230.042128
20.2817631.97230.027114
30.1580311.10620.137017
40.0193170.13520.446495
50.1523381.06640.145742
6-0.04233-0.29630.384123
7-0.09467-0.66270.255317
80.1243030.87010.194239
9-0.002524-0.01770.492989
100.1931391.3520.091296
110.0034290.0240.490473
12-0.111055-0.77740.220335
13-0.084051-0.58840.279498
14-0.084149-0.5890.27927
15-0.014036-0.09830.461067
16-0.174243-1.21970.114208
17-0.044852-0.3140.377439
180.1117120.7820.218993
190.0085280.05970.476319
200.0743030.52010.302662
210.0417830.29250.385576
22-0.035903-0.25130.401309
230.1085370.75980.225519
24-0.181039-1.26730.105523
25-0.002424-0.0170.493266
26-0.01223-0.08560.466063
27-0.046035-0.32220.374319
280.0490280.34320.366458
29-0.016205-0.11340.455074
30-0.121131-0.84790.200304
310.0206620.14460.442798
32-0.146225-1.02360.155531
33-0.112536-0.78780.217317
34-0.246175-1.72320.045577
35-0.178933-1.25250.108161
36-0.090045-0.63030.265708
37-0.091242-0.63870.262997
38-0.114756-0.80330.212842
39-0.127847-0.89490.1876
40-0.093406-0.65380.258134
41-0.02162-0.15130.440165
42-0.026287-0.1840.427382
43-0.016172-0.11320.455166
44-0.010367-0.07260.471221
450.0362440.25370.40039
460.1006420.70450.242231
470.0559470.39160.348515
480.0510240.35720.361249
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.251757 & 1.7623 & 0.042128 \tabularnewline
2 & 0.281763 & 1.9723 & 0.027114 \tabularnewline
3 & 0.158031 & 1.1062 & 0.137017 \tabularnewline
4 & 0.019317 & 0.1352 & 0.446495 \tabularnewline
5 & 0.152338 & 1.0664 & 0.145742 \tabularnewline
6 & -0.04233 & -0.2963 & 0.384123 \tabularnewline
7 & -0.09467 & -0.6627 & 0.255317 \tabularnewline
8 & 0.124303 & 0.8701 & 0.194239 \tabularnewline
9 & -0.002524 & -0.0177 & 0.492989 \tabularnewline
10 & 0.193139 & 1.352 & 0.091296 \tabularnewline
11 & 0.003429 & 0.024 & 0.490473 \tabularnewline
12 & -0.111055 & -0.7774 & 0.220335 \tabularnewline
13 & -0.084051 & -0.5884 & 0.279498 \tabularnewline
14 & -0.084149 & -0.589 & 0.27927 \tabularnewline
15 & -0.014036 & -0.0983 & 0.461067 \tabularnewline
16 & -0.174243 & -1.2197 & 0.114208 \tabularnewline
17 & -0.044852 & -0.314 & 0.377439 \tabularnewline
18 & 0.111712 & 0.782 & 0.218993 \tabularnewline
19 & 0.008528 & 0.0597 & 0.476319 \tabularnewline
20 & 0.074303 & 0.5201 & 0.302662 \tabularnewline
21 & 0.041783 & 0.2925 & 0.385576 \tabularnewline
22 & -0.035903 & -0.2513 & 0.401309 \tabularnewline
23 & 0.108537 & 0.7598 & 0.225519 \tabularnewline
24 & -0.181039 & -1.2673 & 0.105523 \tabularnewline
25 & -0.002424 & -0.017 & 0.493266 \tabularnewline
26 & -0.01223 & -0.0856 & 0.466063 \tabularnewline
27 & -0.046035 & -0.3222 & 0.374319 \tabularnewline
28 & 0.049028 & 0.3432 & 0.366458 \tabularnewline
29 & -0.016205 & -0.1134 & 0.455074 \tabularnewline
30 & -0.121131 & -0.8479 & 0.200304 \tabularnewline
31 & 0.020662 & 0.1446 & 0.442798 \tabularnewline
32 & -0.146225 & -1.0236 & 0.155531 \tabularnewline
33 & -0.112536 & -0.7878 & 0.217317 \tabularnewline
34 & -0.246175 & -1.7232 & 0.045577 \tabularnewline
35 & -0.178933 & -1.2525 & 0.108161 \tabularnewline
36 & -0.090045 & -0.6303 & 0.265708 \tabularnewline
37 & -0.091242 & -0.6387 & 0.262997 \tabularnewline
38 & -0.114756 & -0.8033 & 0.212842 \tabularnewline
39 & -0.127847 & -0.8949 & 0.1876 \tabularnewline
40 & -0.093406 & -0.6538 & 0.258134 \tabularnewline
41 & -0.02162 & -0.1513 & 0.440165 \tabularnewline
42 & -0.026287 & -0.184 & 0.427382 \tabularnewline
43 & -0.016172 & -0.1132 & 0.455166 \tabularnewline
44 & -0.010367 & -0.0726 & 0.471221 \tabularnewline
45 & 0.036244 & 0.2537 & 0.40039 \tabularnewline
46 & 0.100642 & 0.7045 & 0.242231 \tabularnewline
47 & 0.055947 & 0.3916 & 0.348515 \tabularnewline
48 & 0.051024 & 0.3572 & 0.361249 \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71330&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]0.251757[/C][C]1.7623[/C][C]0.042128[/C][/ROW]
[ROW][C]2[/C][C]0.281763[/C][C]1.9723[/C][C]0.027114[/C][/ROW]
[ROW][C]3[/C][C]0.158031[/C][C]1.1062[/C][C]0.137017[/C][/ROW]
[ROW][C]4[/C][C]0.019317[/C][C]0.1352[/C][C]0.446495[/C][/ROW]
[ROW][C]5[/C][C]0.152338[/C][C]1.0664[/C][C]0.145742[/C][/ROW]
[ROW][C]6[/C][C]-0.04233[/C][C]-0.2963[/C][C]0.384123[/C][/ROW]
[ROW][C]7[/C][C]-0.09467[/C][C]-0.6627[/C][C]0.255317[/C][/ROW]
[ROW][C]8[/C][C]0.124303[/C][C]0.8701[/C][C]0.194239[/C][/ROW]
[ROW][C]9[/C][C]-0.002524[/C][C]-0.0177[/C][C]0.492989[/C][/ROW]
[ROW][C]10[/C][C]0.193139[/C][C]1.352[/C][C]0.091296[/C][/ROW]
[ROW][C]11[/C][C]0.003429[/C][C]0.024[/C][C]0.490473[/C][/ROW]
[ROW][C]12[/C][C]-0.111055[/C][C]-0.7774[/C][C]0.220335[/C][/ROW]
[ROW][C]13[/C][C]-0.084051[/C][C]-0.5884[/C][C]0.279498[/C][/ROW]
[ROW][C]14[/C][C]-0.084149[/C][C]-0.589[/C][C]0.27927[/C][/ROW]
[ROW][C]15[/C][C]-0.014036[/C][C]-0.0983[/C][C]0.461067[/C][/ROW]
[ROW][C]16[/C][C]-0.174243[/C][C]-1.2197[/C][C]0.114208[/C][/ROW]
[ROW][C]17[/C][C]-0.044852[/C][C]-0.314[/C][C]0.377439[/C][/ROW]
[ROW][C]18[/C][C]0.111712[/C][C]0.782[/C][C]0.218993[/C][/ROW]
[ROW][C]19[/C][C]0.008528[/C][C]0.0597[/C][C]0.476319[/C][/ROW]
[ROW][C]20[/C][C]0.074303[/C][C]0.5201[/C][C]0.302662[/C][/ROW]
[ROW][C]21[/C][C]0.041783[/C][C]0.2925[/C][C]0.385576[/C][/ROW]
[ROW][C]22[/C][C]-0.035903[/C][C]-0.2513[/C][C]0.401309[/C][/ROW]
[ROW][C]23[/C][C]0.108537[/C][C]0.7598[/C][C]0.225519[/C][/ROW]
[ROW][C]24[/C][C]-0.181039[/C][C]-1.2673[/C][C]0.105523[/C][/ROW]
[ROW][C]25[/C][C]-0.002424[/C][C]-0.017[/C][C]0.493266[/C][/ROW]
[ROW][C]26[/C][C]-0.01223[/C][C]-0.0856[/C][C]0.466063[/C][/ROW]
[ROW][C]27[/C][C]-0.046035[/C][C]-0.3222[/C][C]0.374319[/C][/ROW]
[ROW][C]28[/C][C]0.049028[/C][C]0.3432[/C][C]0.366458[/C][/ROW]
[ROW][C]29[/C][C]-0.016205[/C][C]-0.1134[/C][C]0.455074[/C][/ROW]
[ROW][C]30[/C][C]-0.121131[/C][C]-0.8479[/C][C]0.200304[/C][/ROW]
[ROW][C]31[/C][C]0.020662[/C][C]0.1446[/C][C]0.442798[/C][/ROW]
[ROW][C]32[/C][C]-0.146225[/C][C]-1.0236[/C][C]0.155531[/C][/ROW]
[ROW][C]33[/C][C]-0.112536[/C][C]-0.7878[/C][C]0.217317[/C][/ROW]
[ROW][C]34[/C][C]-0.246175[/C][C]-1.7232[/C][C]0.045577[/C][/ROW]
[ROW][C]35[/C][C]-0.178933[/C][C]-1.2525[/C][C]0.108161[/C][/ROW]
[ROW][C]36[/C][C]-0.090045[/C][C]-0.6303[/C][C]0.265708[/C][/ROW]
[ROW][C]37[/C][C]-0.091242[/C][C]-0.6387[/C][C]0.262997[/C][/ROW]
[ROW][C]38[/C][C]-0.114756[/C][C]-0.8033[/C][C]0.212842[/C][/ROW]
[ROW][C]39[/C][C]-0.127847[/C][C]-0.8949[/C][C]0.1876[/C][/ROW]
[ROW][C]40[/C][C]-0.093406[/C][C]-0.6538[/C][C]0.258134[/C][/ROW]
[ROW][C]41[/C][C]-0.02162[/C][C]-0.1513[/C][C]0.440165[/C][/ROW]
[ROW][C]42[/C][C]-0.026287[/C][C]-0.184[/C][C]0.427382[/C][/ROW]
[ROW][C]43[/C][C]-0.016172[/C][C]-0.1132[/C][C]0.455166[/C][/ROW]
[ROW][C]44[/C][C]-0.010367[/C][C]-0.0726[/C][C]0.471221[/C][/ROW]
[ROW][C]45[/C][C]0.036244[/C][C]0.2537[/C][C]0.40039[/C][/ROW]
[ROW][C]46[/C][C]0.100642[/C][C]0.7045[/C][C]0.242231[/C][/ROW]
[ROW][C]47[/C][C]0.055947[/C][C]0.3916[/C][C]0.348515[/C][/ROW]
[ROW][C]48[/C][C]0.051024[/C][C]0.3572[/C][C]0.361249[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/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=71330&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71330&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
10.2517571.76230.042128
20.2817631.97230.027114
30.1580311.10620.137017
40.0193170.13520.446495
50.1523381.06640.145742
6-0.04233-0.29630.384123
7-0.09467-0.66270.255317
80.1243030.87010.194239
9-0.002524-0.01770.492989
100.1931391.3520.091296
110.0034290.0240.490473
12-0.111055-0.77740.220335
13-0.084051-0.58840.279498
14-0.084149-0.5890.27927
15-0.014036-0.09830.461067
16-0.174243-1.21970.114208
17-0.044852-0.3140.377439
180.1117120.7820.218993
190.0085280.05970.476319
200.0743030.52010.302662
210.0417830.29250.385576
22-0.035903-0.25130.401309
230.1085370.75980.225519
24-0.181039-1.26730.105523
25-0.002424-0.0170.493266
26-0.01223-0.08560.466063
27-0.046035-0.32220.374319
280.0490280.34320.366458
29-0.016205-0.11340.455074
30-0.121131-0.84790.200304
310.0206620.14460.442798
32-0.146225-1.02360.155531
33-0.112536-0.78780.217317
34-0.246175-1.72320.045577
35-0.178933-1.25250.108161
36-0.090045-0.63030.265708
37-0.091242-0.63870.262997
38-0.114756-0.80330.212842
39-0.127847-0.89490.1876
40-0.093406-0.65380.258134
41-0.02162-0.15130.440165
42-0.026287-0.1840.427382
43-0.016172-0.11320.455166
44-0.010367-0.07260.471221
450.0362440.25370.40039
460.1006420.70450.242231
470.0559470.39160.348515
480.0510240.35720.361249
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2517571.76230.042128
20.233161.63210.054533
30.0507340.35510.362006
4-0.096252-0.67380.251814
50.1314720.92030.180961
6-0.095265-0.66690.253997
7-0.144951-1.01470.157627
80.2123321.48630.0718
90.0231950.16240.435844
100.1228220.85980.197055
11-0.0978-0.68460.24841
12-0.167417-1.17190.123448
13-0.125313-0.87720.192331
140.0604030.42280.337138
150.087570.6130.271358
16-0.189974-1.32980.094868
170.119690.83780.203098
180.1775181.24260.109959
19-0.119601-0.83720.20327
20-0.062001-0.4340.333093
210.1721671.20520.116963
22-0.058496-0.40950.34199
230.0115710.0810.467886
24-0.169373-1.18560.120747
250.0320570.22440.411691
260.0898070.62860.266249
270.0035810.02510.490051
28-0.137708-0.9640.169901
290.0077710.05440.478419
30-0.047791-0.33450.3697
31-0.008118-0.05680.477458
32-0.117043-0.81930.20829
33-0.095539-0.66880.253389
34-0.043308-0.30320.381528
350.0028240.01980.492154
36-0.07754-0.54280.29487
37-0.047874-0.33510.369483
380.0022490.01570.493752
39-0.055519-0.38860.349616
40-0.10087-0.70610.241738
410.0149450.10460.458555
420.1810451.26730.105517
43-0.017291-0.1210.452079
44-0.027036-0.18920.42534
450.0686170.48030.316569
46-0.035752-0.25030.401716
470.0255380.17880.429428
480.0023720.01660.493409
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.251757 & 1.7623 & 0.042128 \tabularnewline
2 & 0.23316 & 1.6321 & 0.054533 \tabularnewline
3 & 0.050734 & 0.3551 & 0.362006 \tabularnewline
4 & -0.096252 & -0.6738 & 0.251814 \tabularnewline
5 & 0.131472 & 0.9203 & 0.180961 \tabularnewline
6 & -0.095265 & -0.6669 & 0.253997 \tabularnewline
7 & -0.144951 & -1.0147 & 0.157627 \tabularnewline
8 & 0.212332 & 1.4863 & 0.0718 \tabularnewline
9 & 0.023195 & 0.1624 & 0.435844 \tabularnewline
10 & 0.122822 & 0.8598 & 0.197055 \tabularnewline
11 & -0.0978 & -0.6846 & 0.24841 \tabularnewline
12 & -0.167417 & -1.1719 & 0.123448 \tabularnewline
13 & -0.125313 & -0.8772 & 0.192331 \tabularnewline
14 & 0.060403 & 0.4228 & 0.337138 \tabularnewline
15 & 0.08757 & 0.613 & 0.271358 \tabularnewline
16 & -0.189974 & -1.3298 & 0.094868 \tabularnewline
17 & 0.11969 & 0.8378 & 0.203098 \tabularnewline
18 & 0.177518 & 1.2426 & 0.109959 \tabularnewline
19 & -0.119601 & -0.8372 & 0.20327 \tabularnewline
20 & -0.062001 & -0.434 & 0.333093 \tabularnewline
21 & 0.172167 & 1.2052 & 0.116963 \tabularnewline
22 & -0.058496 & -0.4095 & 0.34199 \tabularnewline
23 & 0.011571 & 0.081 & 0.467886 \tabularnewline
24 & -0.169373 & -1.1856 & 0.120747 \tabularnewline
25 & 0.032057 & 0.2244 & 0.411691 \tabularnewline
26 & 0.089807 & 0.6286 & 0.266249 \tabularnewline
27 & 0.003581 & 0.0251 & 0.490051 \tabularnewline
28 & -0.137708 & -0.964 & 0.169901 \tabularnewline
29 & 0.007771 & 0.0544 & 0.478419 \tabularnewline
30 & -0.047791 & -0.3345 & 0.3697 \tabularnewline
31 & -0.008118 & -0.0568 & 0.477458 \tabularnewline
32 & -0.117043 & -0.8193 & 0.20829 \tabularnewline
33 & -0.095539 & -0.6688 & 0.253389 \tabularnewline
34 & -0.043308 & -0.3032 & 0.381528 \tabularnewline
35 & 0.002824 & 0.0198 & 0.492154 \tabularnewline
36 & -0.07754 & -0.5428 & 0.29487 \tabularnewline
37 & -0.047874 & -0.3351 & 0.369483 \tabularnewline
38 & 0.002249 & 0.0157 & 0.493752 \tabularnewline
39 & -0.055519 & -0.3886 & 0.349616 \tabularnewline
40 & -0.10087 & -0.7061 & 0.241738 \tabularnewline
41 & 0.014945 & 0.1046 & 0.458555 \tabularnewline
42 & 0.181045 & 1.2673 & 0.105517 \tabularnewline
43 & -0.017291 & -0.121 & 0.452079 \tabularnewline
44 & -0.027036 & -0.1892 & 0.42534 \tabularnewline
45 & 0.068617 & 0.4803 & 0.316569 \tabularnewline
46 & -0.035752 & -0.2503 & 0.401716 \tabularnewline
47 & 0.025538 & 0.1788 & 0.429428 \tabularnewline
48 & 0.002372 & 0.0166 & 0.493409 \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71330&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]0.251757[/C][C]1.7623[/C][C]0.042128[/C][/ROW]
[ROW][C]2[/C][C]0.23316[/C][C]1.6321[/C][C]0.054533[/C][/ROW]
[ROW][C]3[/C][C]0.050734[/C][C]0.3551[/C][C]0.362006[/C][/ROW]
[ROW][C]4[/C][C]-0.096252[/C][C]-0.6738[/C][C]0.251814[/C][/ROW]
[ROW][C]5[/C][C]0.131472[/C][C]0.9203[/C][C]0.180961[/C][/ROW]
[ROW][C]6[/C][C]-0.095265[/C][C]-0.6669[/C][C]0.253997[/C][/ROW]
[ROW][C]7[/C][C]-0.144951[/C][C]-1.0147[/C][C]0.157627[/C][/ROW]
[ROW][C]8[/C][C]0.212332[/C][C]1.4863[/C][C]0.0718[/C][/ROW]
[ROW][C]9[/C][C]0.023195[/C][C]0.1624[/C][C]0.435844[/C][/ROW]
[ROW][C]10[/C][C]0.122822[/C][C]0.8598[/C][C]0.197055[/C][/ROW]
[ROW][C]11[/C][C]-0.0978[/C][C]-0.6846[/C][C]0.24841[/C][/ROW]
[ROW][C]12[/C][C]-0.167417[/C][C]-1.1719[/C][C]0.123448[/C][/ROW]
[ROW][C]13[/C][C]-0.125313[/C][C]-0.8772[/C][C]0.192331[/C][/ROW]
[ROW][C]14[/C][C]0.060403[/C][C]0.4228[/C][C]0.337138[/C][/ROW]
[ROW][C]15[/C][C]0.08757[/C][C]0.613[/C][C]0.271358[/C][/ROW]
[ROW][C]16[/C][C]-0.189974[/C][C]-1.3298[/C][C]0.094868[/C][/ROW]
[ROW][C]17[/C][C]0.11969[/C][C]0.8378[/C][C]0.203098[/C][/ROW]
[ROW][C]18[/C][C]0.177518[/C][C]1.2426[/C][C]0.109959[/C][/ROW]
[ROW][C]19[/C][C]-0.119601[/C][C]-0.8372[/C][C]0.20327[/C][/ROW]
[ROW][C]20[/C][C]-0.062001[/C][C]-0.434[/C][C]0.333093[/C][/ROW]
[ROW][C]21[/C][C]0.172167[/C][C]1.2052[/C][C]0.116963[/C][/ROW]
[ROW][C]22[/C][C]-0.058496[/C][C]-0.4095[/C][C]0.34199[/C][/ROW]
[ROW][C]23[/C][C]0.011571[/C][C]0.081[/C][C]0.467886[/C][/ROW]
[ROW][C]24[/C][C]-0.169373[/C][C]-1.1856[/C][C]0.120747[/C][/ROW]
[ROW][C]25[/C][C]0.032057[/C][C]0.2244[/C][C]0.411691[/C][/ROW]
[ROW][C]26[/C][C]0.089807[/C][C]0.6286[/C][C]0.266249[/C][/ROW]
[ROW][C]27[/C][C]0.003581[/C][C]0.0251[/C][C]0.490051[/C][/ROW]
[ROW][C]28[/C][C]-0.137708[/C][C]-0.964[/C][C]0.169901[/C][/ROW]
[ROW][C]29[/C][C]0.007771[/C][C]0.0544[/C][C]0.478419[/C][/ROW]
[ROW][C]30[/C][C]-0.047791[/C][C]-0.3345[/C][C]0.3697[/C][/ROW]
[ROW][C]31[/C][C]-0.008118[/C][C]-0.0568[/C][C]0.477458[/C][/ROW]
[ROW][C]32[/C][C]-0.117043[/C][C]-0.8193[/C][C]0.20829[/C][/ROW]
[ROW][C]33[/C][C]-0.095539[/C][C]-0.6688[/C][C]0.253389[/C][/ROW]
[ROW][C]34[/C][C]-0.043308[/C][C]-0.3032[/C][C]0.381528[/C][/ROW]
[ROW][C]35[/C][C]0.002824[/C][C]0.0198[/C][C]0.492154[/C][/ROW]
[ROW][C]36[/C][C]-0.07754[/C][C]-0.5428[/C][C]0.29487[/C][/ROW]
[ROW][C]37[/C][C]-0.047874[/C][C]-0.3351[/C][C]0.369483[/C][/ROW]
[ROW][C]38[/C][C]0.002249[/C][C]0.0157[/C][C]0.493752[/C][/ROW]
[ROW][C]39[/C][C]-0.055519[/C][C]-0.3886[/C][C]0.349616[/C][/ROW]
[ROW][C]40[/C][C]-0.10087[/C][C]-0.7061[/C][C]0.241738[/C][/ROW]
[ROW][C]41[/C][C]0.014945[/C][C]0.1046[/C][C]0.458555[/C][/ROW]
[ROW][C]42[/C][C]0.181045[/C][C]1.2673[/C][C]0.105517[/C][/ROW]
[ROW][C]43[/C][C]-0.017291[/C][C]-0.121[/C][C]0.452079[/C][/ROW]
[ROW][C]44[/C][C]-0.027036[/C][C]-0.1892[/C][C]0.42534[/C][/ROW]
[ROW][C]45[/C][C]0.068617[/C][C]0.4803[/C][C]0.316569[/C][/ROW]
[ROW][C]46[/C][C]-0.035752[/C][C]-0.2503[/C][C]0.401716[/C][/ROW]
[ROW][C]47[/C][C]0.025538[/C][C]0.1788[/C][C]0.429428[/C][/ROW]
[ROW][C]48[/C][C]0.002372[/C][C]0.0166[/C][C]0.493409[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/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=71330&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71330&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
10.2517571.76230.042128
20.233161.63210.054533
30.0507340.35510.362006
4-0.096252-0.67380.251814
50.1314720.92030.180961
6-0.095265-0.66690.253997
7-0.144951-1.01470.157627
80.2123321.48630.0718
90.0231950.16240.435844
100.1228220.85980.197055
11-0.0978-0.68460.24841
12-0.167417-1.17190.123448
13-0.125313-0.87720.192331
140.0604030.42280.337138
150.087570.6130.271358
16-0.189974-1.32980.094868
170.119690.83780.203098
180.1775181.24260.109959
19-0.119601-0.83720.20327
20-0.062001-0.4340.333093
210.1721671.20520.116963
22-0.058496-0.40950.34199
230.0115710.0810.467886
24-0.169373-1.18560.120747
250.0320570.22440.411691
260.0898070.62860.266249
270.0035810.02510.490051
28-0.137708-0.9640.169901
290.0077710.05440.478419
30-0.047791-0.33450.3697
31-0.008118-0.05680.477458
32-0.117043-0.81930.20829
33-0.095539-0.66880.253389
34-0.043308-0.30320.381528
350.0028240.01980.492154
36-0.07754-0.54280.29487
37-0.047874-0.33510.369483
380.0022490.01570.493752
39-0.055519-0.38860.349616
40-0.10087-0.70610.241738
410.0149450.10460.458555
420.1810451.26730.105517
43-0.017291-0.1210.452079
44-0.027036-0.18920.42534
450.0686170.48030.316569
46-0.035752-0.25030.401716
470.0255380.17880.429428
480.0023720.01660.493409
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



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