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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 computationThu, 18 Dec 2008 06:25:56 -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/18/t1229606798vlyl09co70p2okz.htm/, Retrieved Sun, 12 May 2024 11:52:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34741, Retrieved Sun, 12 May 2024 11:52:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cross Correlation Function] [Cross correlation...] [2008-12-15 23:19:44] [abc1badd8768b83426be5031c0f123a6]
- RMPD    [(Partial) Autocorrelation Function] [PACF d=1 D=1] [2008-12-18 13:25:56] [0bb3b56b7083c5944c3818446f605d68] [Current]
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Dataseries X:
7.6
7.7
7.6
8.2
8
8.1
8.3
8.2
8.1
7.7
7.6
7.7
8.2
8.4
8.4
8.6
8.4
8.5
8.7
8.7
8.6
7.4
7.3
7.4
9
9.2
9.2
8.5
8.3
8.3
8.6
8.6
8.5
8.1
8.1
8
8.6
8.7
8.7
8.6
8.4
8.4
8.7
8.7
8.5
8.3
8.3
8.3
8.1
8.2
8.1
8.1
7.9
7.7
8.1
8
7.7
7.8
7.6
7.4
7.7




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=34741&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=34741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34741&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
10.0010190.00710.497199
2-0.072251-0.50060.30948
3-0.539298-3.73640.000248
4-0.061567-0.42650.335809
50.0106080.07350.470859
60.1628591.12830.132396
7-0.027461-0.19030.424956
80.0401520.27820.391035
90.083660.57960.282444
100.0456610.31640.376554
11-0.019437-0.13470.446719
12-0.212822-1.47450.073442
13-0.022235-0.1540.439109
140.0182090.12620.450068
150.1486711.030.154082
16-0.013868-0.09610.461928
170.0112550.0780.469085
18-0.142772-0.98920.163774
190.0107730.07460.470407
20-0.026885-0.18630.426511
210.2350621.62860.054977
22-0.009255-0.06410.474571
230.0420160.29110.386117
24-0.261542-1.8120.038121
25-0.038883-0.26940.394391
26-0.003955-0.02740.489127
270.1798911.24630.109348
280.0055040.03810.48487
29-0.017446-0.12090.45215
30-0.045298-0.31380.377503
314.8e-053e-040.499867
320.0333420.2310.409147
330.0178830.12390.450958
34-0.037956-0.2630.396852
35-0.028562-0.19790.421987
360.0427280.2960.384243
370.022570.15640.4382
380.0440840.30540.380683
39-0.080527-0.55790.289749
400.0022020.01530.493947
410.0158850.11010.456412
42-0.022453-0.15560.438516
430.0170370.1180.453265
440.0156730.10860.456993
45-0.039349-0.27260.393159
460.0067470.04670.481456
470.0102850.07130.471746
48NANANA
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 & 0.001019 & 0.0071 & 0.497199 \tabularnewline
2 & -0.072251 & -0.5006 & 0.30948 \tabularnewline
3 & -0.539298 & -3.7364 & 0.000248 \tabularnewline
4 & -0.061567 & -0.4265 & 0.335809 \tabularnewline
5 & 0.010608 & 0.0735 & 0.470859 \tabularnewline
6 & 0.162859 & 1.1283 & 0.132396 \tabularnewline
7 & -0.027461 & -0.1903 & 0.424956 \tabularnewline
8 & 0.040152 & 0.2782 & 0.391035 \tabularnewline
9 & 0.08366 & 0.5796 & 0.282444 \tabularnewline
10 & 0.045661 & 0.3164 & 0.376554 \tabularnewline
11 & -0.019437 & -0.1347 & 0.446719 \tabularnewline
12 & -0.212822 & -1.4745 & 0.073442 \tabularnewline
13 & -0.022235 & -0.154 & 0.439109 \tabularnewline
14 & 0.018209 & 0.1262 & 0.450068 \tabularnewline
15 & 0.148671 & 1.03 & 0.154082 \tabularnewline
16 & -0.013868 & -0.0961 & 0.461928 \tabularnewline
17 & 0.011255 & 0.078 & 0.469085 \tabularnewline
18 & -0.142772 & -0.9892 & 0.163774 \tabularnewline
19 & 0.010773 & 0.0746 & 0.470407 \tabularnewline
20 & -0.026885 & -0.1863 & 0.426511 \tabularnewline
21 & 0.235062 & 1.6286 & 0.054977 \tabularnewline
22 & -0.009255 & -0.0641 & 0.474571 \tabularnewline
23 & 0.042016 & 0.2911 & 0.386117 \tabularnewline
24 & -0.261542 & -1.812 & 0.038121 \tabularnewline
25 & -0.038883 & -0.2694 & 0.394391 \tabularnewline
26 & -0.003955 & -0.0274 & 0.489127 \tabularnewline
27 & 0.179891 & 1.2463 & 0.109348 \tabularnewline
28 & 0.005504 & 0.0381 & 0.48487 \tabularnewline
29 & -0.017446 & -0.1209 & 0.45215 \tabularnewline
30 & -0.045298 & -0.3138 & 0.377503 \tabularnewline
31 & 4.8e-05 & 3e-04 & 0.499867 \tabularnewline
32 & 0.033342 & 0.231 & 0.409147 \tabularnewline
33 & 0.017883 & 0.1239 & 0.450958 \tabularnewline
34 & -0.037956 & -0.263 & 0.396852 \tabularnewline
35 & -0.028562 & -0.1979 & 0.421987 \tabularnewline
36 & 0.042728 & 0.296 & 0.384243 \tabularnewline
37 & 0.02257 & 0.1564 & 0.4382 \tabularnewline
38 & 0.044084 & 0.3054 & 0.380683 \tabularnewline
39 & -0.080527 & -0.5579 & 0.289749 \tabularnewline
40 & 0.002202 & 0.0153 & 0.493947 \tabularnewline
41 & 0.015885 & 0.1101 & 0.456412 \tabularnewline
42 & -0.022453 & -0.1556 & 0.438516 \tabularnewline
43 & 0.017037 & 0.118 & 0.453265 \tabularnewline
44 & 0.015673 & 0.1086 & 0.456993 \tabularnewline
45 & -0.039349 & -0.2726 & 0.393159 \tabularnewline
46 & 0.006747 & 0.0467 & 0.481456 \tabularnewline
47 & 0.010285 & 0.0713 & 0.471746 \tabularnewline
48 & NA & NA & NA \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=34741&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]0.001019[/C][C]0.0071[/C][C]0.497199[/C][/ROW]
[ROW][C]2[/C][C]-0.072251[/C][C]-0.5006[/C][C]0.30948[/C][/ROW]
[ROW][C]3[/C][C]-0.539298[/C][C]-3.7364[/C][C]0.000248[/C][/ROW]
[ROW][C]4[/C][C]-0.061567[/C][C]-0.4265[/C][C]0.335809[/C][/ROW]
[ROW][C]5[/C][C]0.010608[/C][C]0.0735[/C][C]0.470859[/C][/ROW]
[ROW][C]6[/C][C]0.162859[/C][C]1.1283[/C][C]0.132396[/C][/ROW]
[ROW][C]7[/C][C]-0.027461[/C][C]-0.1903[/C][C]0.424956[/C][/ROW]
[ROW][C]8[/C][C]0.040152[/C][C]0.2782[/C][C]0.391035[/C][/ROW]
[ROW][C]9[/C][C]0.08366[/C][C]0.5796[/C][C]0.282444[/C][/ROW]
[ROW][C]10[/C][C]0.045661[/C][C]0.3164[/C][C]0.376554[/C][/ROW]
[ROW][C]11[/C][C]-0.019437[/C][C]-0.1347[/C][C]0.446719[/C][/ROW]
[ROW][C]12[/C][C]-0.212822[/C][C]-1.4745[/C][C]0.073442[/C][/ROW]
[ROW][C]13[/C][C]-0.022235[/C][C]-0.154[/C][C]0.439109[/C][/ROW]
[ROW][C]14[/C][C]0.018209[/C][C]0.1262[/C][C]0.450068[/C][/ROW]
[ROW][C]15[/C][C]0.148671[/C][C]1.03[/C][C]0.154082[/C][/ROW]
[ROW][C]16[/C][C]-0.013868[/C][C]-0.0961[/C][C]0.461928[/C][/ROW]
[ROW][C]17[/C][C]0.011255[/C][C]0.078[/C][C]0.469085[/C][/ROW]
[ROW][C]18[/C][C]-0.142772[/C][C]-0.9892[/C][C]0.163774[/C][/ROW]
[ROW][C]19[/C][C]0.010773[/C][C]0.0746[/C][C]0.470407[/C][/ROW]
[ROW][C]20[/C][C]-0.026885[/C][C]-0.1863[/C][C]0.426511[/C][/ROW]
[ROW][C]21[/C][C]0.235062[/C][C]1.6286[/C][C]0.054977[/C][/ROW]
[ROW][C]22[/C][C]-0.009255[/C][C]-0.0641[/C][C]0.474571[/C][/ROW]
[ROW][C]23[/C][C]0.042016[/C][C]0.2911[/C][C]0.386117[/C][/ROW]
[ROW][C]24[/C][C]-0.261542[/C][C]-1.812[/C][C]0.038121[/C][/ROW]
[ROW][C]25[/C][C]-0.038883[/C][C]-0.2694[/C][C]0.394391[/C][/ROW]
[ROW][C]26[/C][C]-0.003955[/C][C]-0.0274[/C][C]0.489127[/C][/ROW]
[ROW][C]27[/C][C]0.179891[/C][C]1.2463[/C][C]0.109348[/C][/ROW]
[ROW][C]28[/C][C]0.005504[/C][C]0.0381[/C][C]0.48487[/C][/ROW]
[ROW][C]29[/C][C]-0.017446[/C][C]-0.1209[/C][C]0.45215[/C][/ROW]
[ROW][C]30[/C][C]-0.045298[/C][C]-0.3138[/C][C]0.377503[/C][/ROW]
[ROW][C]31[/C][C]4.8e-05[/C][C]3e-04[/C][C]0.499867[/C][/ROW]
[ROW][C]32[/C][C]0.033342[/C][C]0.231[/C][C]0.409147[/C][/ROW]
[ROW][C]33[/C][C]0.017883[/C][C]0.1239[/C][C]0.450958[/C][/ROW]
[ROW][C]34[/C][C]-0.037956[/C][C]-0.263[/C][C]0.396852[/C][/ROW]
[ROW][C]35[/C][C]-0.028562[/C][C]-0.1979[/C][C]0.421987[/C][/ROW]
[ROW][C]36[/C][C]0.042728[/C][C]0.296[/C][C]0.384243[/C][/ROW]
[ROW][C]37[/C][C]0.02257[/C][C]0.1564[/C][C]0.4382[/C][/ROW]
[ROW][C]38[/C][C]0.044084[/C][C]0.3054[/C][C]0.380683[/C][/ROW]
[ROW][C]39[/C][C]-0.080527[/C][C]-0.5579[/C][C]0.289749[/C][/ROW]
[ROW][C]40[/C][C]0.002202[/C][C]0.0153[/C][C]0.493947[/C][/ROW]
[ROW][C]41[/C][C]0.015885[/C][C]0.1101[/C][C]0.456412[/C][/ROW]
[ROW][C]42[/C][C]-0.022453[/C][C]-0.1556[/C][C]0.438516[/C][/ROW]
[ROW][C]43[/C][C]0.017037[/C][C]0.118[/C][C]0.453265[/C][/ROW]
[ROW][C]44[/C][C]0.015673[/C][C]0.1086[/C][C]0.456993[/C][/ROW]
[ROW][C]45[/C][C]-0.039349[/C][C]-0.2726[/C][C]0.393159[/C][/ROW]
[ROW][C]46[/C][C]0.006747[/C][C]0.0467[/C][C]0.481456[/C][/ROW]
[ROW][C]47[/C][C]0.010285[/C][C]0.0713[/C][C]0.471746[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/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=34741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34741&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
10.0010190.00710.497199
2-0.072251-0.50060.30948
3-0.539298-3.73640.000248
4-0.061567-0.42650.335809
50.0106080.07350.470859
60.1628591.12830.132396
7-0.027461-0.19030.424956
80.0401520.27820.391035
90.083660.57960.282444
100.0456610.31640.376554
11-0.019437-0.13470.446719
12-0.212822-1.47450.073442
13-0.022235-0.1540.439109
140.0182090.12620.450068
150.1486711.030.154082
16-0.013868-0.09610.461928
170.0112550.0780.469085
18-0.142772-0.98920.163774
190.0107730.07460.470407
20-0.026885-0.18630.426511
210.2350621.62860.054977
22-0.009255-0.06410.474571
230.0420160.29110.386117
24-0.261542-1.8120.038121
25-0.038883-0.26940.394391
26-0.003955-0.02740.489127
270.1798911.24630.109348
280.0055040.03810.48487
29-0.017446-0.12090.45215
30-0.045298-0.31380.377503
314.8e-053e-040.499867
320.0333420.2310.409147
330.0178830.12390.450958
34-0.037956-0.2630.396852
35-0.028562-0.19790.421987
360.0427280.2960.384243
370.022570.15640.4382
380.0440840.30540.380683
39-0.080527-0.55790.289749
400.0022020.01530.493947
410.0158850.11010.456412
42-0.022453-0.15560.438516
430.0170370.1180.453265
440.0156730.10860.456993
45-0.039349-0.27260.393159
460.0067470.04670.481456
470.0102850.07130.471746
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0010190.00710.497199
2-0.072252-0.50060.309477
3-0.541975-3.75490.000234
4-0.123434-0.85520.198352
5-0.113667-0.78750.217428
6-0.225616-1.56310.062298
7-0.22261-1.54230.064785
8-0.095611-0.66240.255437
90.0448790.31090.378599
10-0.059024-0.40890.342204
110.006250.04330.482822
12-0.137988-0.9560.171929
13-0.010488-0.07270.471187
14-0.018535-0.12840.449178
15-0.061452-0.42580.336096
16-0.071977-0.49870.310145
17-0.01713-0.11870.453012
18-0.170694-1.18260.121395
19-0.148899-1.03160.153714
20-0.140419-0.97290.167751
210.1387310.96120.170646
22-0.039343-0.27260.393173
230.039160.27130.393658
24-0.114051-0.79020.216657
25-0.067619-0.46850.320782
26-0.007097-0.04920.480495
27-0.027256-0.18880.425509
28-0.102745-0.71180.240006
29-0.093522-0.64790.260057
30-0.071496-0.49530.311312
31-0.151982-1.0530.148815
32-0.119347-0.82690.206203
330.0798410.55320.291362
34-0.076223-0.52810.299935
35-0.039579-0.27420.39255
36-0.007338-0.05080.479832
37-0.017817-0.12340.451138
380.036150.25050.401652
39-0.002254-0.01560.493803
400.0156520.10840.457048
410.0874270.60570.27378
42-0.170419-1.18070.121771
43-0.007463-0.05170.479489
440.0137240.09510.462324
45-0.030191-0.20920.417602
46-0.00574-0.03980.484223
470.0542760.3760.354273
48NANANA
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 & 0.001019 & 0.0071 & 0.497199 \tabularnewline
2 & -0.072252 & -0.5006 & 0.309477 \tabularnewline
3 & -0.541975 & -3.7549 & 0.000234 \tabularnewline
4 & -0.123434 & -0.8552 & 0.198352 \tabularnewline
5 & -0.113667 & -0.7875 & 0.217428 \tabularnewline
6 & -0.225616 & -1.5631 & 0.062298 \tabularnewline
7 & -0.22261 & -1.5423 & 0.064785 \tabularnewline
8 & -0.095611 & -0.6624 & 0.255437 \tabularnewline
9 & 0.044879 & 0.3109 & 0.378599 \tabularnewline
10 & -0.059024 & -0.4089 & 0.342204 \tabularnewline
11 & 0.00625 & 0.0433 & 0.482822 \tabularnewline
12 & -0.137988 & -0.956 & 0.171929 \tabularnewline
13 & -0.010488 & -0.0727 & 0.471187 \tabularnewline
14 & -0.018535 & -0.1284 & 0.449178 \tabularnewline
15 & -0.061452 & -0.4258 & 0.336096 \tabularnewline
16 & -0.071977 & -0.4987 & 0.310145 \tabularnewline
17 & -0.01713 & -0.1187 & 0.453012 \tabularnewline
18 & -0.170694 & -1.1826 & 0.121395 \tabularnewline
19 & -0.148899 & -1.0316 & 0.153714 \tabularnewline
20 & -0.140419 & -0.9729 & 0.167751 \tabularnewline
21 & 0.138731 & 0.9612 & 0.170646 \tabularnewline
22 & -0.039343 & -0.2726 & 0.393173 \tabularnewline
23 & 0.03916 & 0.2713 & 0.393658 \tabularnewline
24 & -0.114051 & -0.7902 & 0.216657 \tabularnewline
25 & -0.067619 & -0.4685 & 0.320782 \tabularnewline
26 & -0.007097 & -0.0492 & 0.480495 \tabularnewline
27 & -0.027256 & -0.1888 & 0.425509 \tabularnewline
28 & -0.102745 & -0.7118 & 0.240006 \tabularnewline
29 & -0.093522 & -0.6479 & 0.260057 \tabularnewline
30 & -0.071496 & -0.4953 & 0.311312 \tabularnewline
31 & -0.151982 & -1.053 & 0.148815 \tabularnewline
32 & -0.119347 & -0.8269 & 0.206203 \tabularnewline
33 & 0.079841 & 0.5532 & 0.291362 \tabularnewline
34 & -0.076223 & -0.5281 & 0.299935 \tabularnewline
35 & -0.039579 & -0.2742 & 0.39255 \tabularnewline
36 & -0.007338 & -0.0508 & 0.479832 \tabularnewline
37 & -0.017817 & -0.1234 & 0.451138 \tabularnewline
38 & 0.03615 & 0.2505 & 0.401652 \tabularnewline
39 & -0.002254 & -0.0156 & 0.493803 \tabularnewline
40 & 0.015652 & 0.1084 & 0.457048 \tabularnewline
41 & 0.087427 & 0.6057 & 0.27378 \tabularnewline
42 & -0.170419 & -1.1807 & 0.121771 \tabularnewline
43 & -0.007463 & -0.0517 & 0.479489 \tabularnewline
44 & 0.013724 & 0.0951 & 0.462324 \tabularnewline
45 & -0.030191 & -0.2092 & 0.417602 \tabularnewline
46 & -0.00574 & -0.0398 & 0.484223 \tabularnewline
47 & 0.054276 & 0.376 & 0.354273 \tabularnewline
48 & NA & NA & NA \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=34741&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]0.001019[/C][C]0.0071[/C][C]0.497199[/C][/ROW]
[ROW][C]2[/C][C]-0.072252[/C][C]-0.5006[/C][C]0.309477[/C][/ROW]
[ROW][C]3[/C][C]-0.541975[/C][C]-3.7549[/C][C]0.000234[/C][/ROW]
[ROW][C]4[/C][C]-0.123434[/C][C]-0.8552[/C][C]0.198352[/C][/ROW]
[ROW][C]5[/C][C]-0.113667[/C][C]-0.7875[/C][C]0.217428[/C][/ROW]
[ROW][C]6[/C][C]-0.225616[/C][C]-1.5631[/C][C]0.062298[/C][/ROW]
[ROW][C]7[/C][C]-0.22261[/C][C]-1.5423[/C][C]0.064785[/C][/ROW]
[ROW][C]8[/C][C]-0.095611[/C][C]-0.6624[/C][C]0.255437[/C][/ROW]
[ROW][C]9[/C][C]0.044879[/C][C]0.3109[/C][C]0.378599[/C][/ROW]
[ROW][C]10[/C][C]-0.059024[/C][C]-0.4089[/C][C]0.342204[/C][/ROW]
[ROW][C]11[/C][C]0.00625[/C][C]0.0433[/C][C]0.482822[/C][/ROW]
[ROW][C]12[/C][C]-0.137988[/C][C]-0.956[/C][C]0.171929[/C][/ROW]
[ROW][C]13[/C][C]-0.010488[/C][C]-0.0727[/C][C]0.471187[/C][/ROW]
[ROW][C]14[/C][C]-0.018535[/C][C]-0.1284[/C][C]0.449178[/C][/ROW]
[ROW][C]15[/C][C]-0.061452[/C][C]-0.4258[/C][C]0.336096[/C][/ROW]
[ROW][C]16[/C][C]-0.071977[/C][C]-0.4987[/C][C]0.310145[/C][/ROW]
[ROW][C]17[/C][C]-0.01713[/C][C]-0.1187[/C][C]0.453012[/C][/ROW]
[ROW][C]18[/C][C]-0.170694[/C][C]-1.1826[/C][C]0.121395[/C][/ROW]
[ROW][C]19[/C][C]-0.148899[/C][C]-1.0316[/C][C]0.153714[/C][/ROW]
[ROW][C]20[/C][C]-0.140419[/C][C]-0.9729[/C][C]0.167751[/C][/ROW]
[ROW][C]21[/C][C]0.138731[/C][C]0.9612[/C][C]0.170646[/C][/ROW]
[ROW][C]22[/C][C]-0.039343[/C][C]-0.2726[/C][C]0.393173[/C][/ROW]
[ROW][C]23[/C][C]0.03916[/C][C]0.2713[/C][C]0.393658[/C][/ROW]
[ROW][C]24[/C][C]-0.114051[/C][C]-0.7902[/C][C]0.216657[/C][/ROW]
[ROW][C]25[/C][C]-0.067619[/C][C]-0.4685[/C][C]0.320782[/C][/ROW]
[ROW][C]26[/C][C]-0.007097[/C][C]-0.0492[/C][C]0.480495[/C][/ROW]
[ROW][C]27[/C][C]-0.027256[/C][C]-0.1888[/C][C]0.425509[/C][/ROW]
[ROW][C]28[/C][C]-0.102745[/C][C]-0.7118[/C][C]0.240006[/C][/ROW]
[ROW][C]29[/C][C]-0.093522[/C][C]-0.6479[/C][C]0.260057[/C][/ROW]
[ROW][C]30[/C][C]-0.071496[/C][C]-0.4953[/C][C]0.311312[/C][/ROW]
[ROW][C]31[/C][C]-0.151982[/C][C]-1.053[/C][C]0.148815[/C][/ROW]
[ROW][C]32[/C][C]-0.119347[/C][C]-0.8269[/C][C]0.206203[/C][/ROW]
[ROW][C]33[/C][C]0.079841[/C][C]0.5532[/C][C]0.291362[/C][/ROW]
[ROW][C]34[/C][C]-0.076223[/C][C]-0.5281[/C][C]0.299935[/C][/ROW]
[ROW][C]35[/C][C]-0.039579[/C][C]-0.2742[/C][C]0.39255[/C][/ROW]
[ROW][C]36[/C][C]-0.007338[/C][C]-0.0508[/C][C]0.479832[/C][/ROW]
[ROW][C]37[/C][C]-0.017817[/C][C]-0.1234[/C][C]0.451138[/C][/ROW]
[ROW][C]38[/C][C]0.03615[/C][C]0.2505[/C][C]0.401652[/C][/ROW]
[ROW][C]39[/C][C]-0.002254[/C][C]-0.0156[/C][C]0.493803[/C][/ROW]
[ROW][C]40[/C][C]0.015652[/C][C]0.1084[/C][C]0.457048[/C][/ROW]
[ROW][C]41[/C][C]0.087427[/C][C]0.6057[/C][C]0.27378[/C][/ROW]
[ROW][C]42[/C][C]-0.170419[/C][C]-1.1807[/C][C]0.121771[/C][/ROW]
[ROW][C]43[/C][C]-0.007463[/C][C]-0.0517[/C][C]0.479489[/C][/ROW]
[ROW][C]44[/C][C]0.013724[/C][C]0.0951[/C][C]0.462324[/C][/ROW]
[ROW][C]45[/C][C]-0.030191[/C][C]-0.2092[/C][C]0.417602[/C][/ROW]
[ROW][C]46[/C][C]-0.00574[/C][C]-0.0398[/C][C]0.484223[/C][/ROW]
[ROW][C]47[/C][C]0.054276[/C][C]0.376[/C][C]0.354273[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/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=34741&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34741&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
10.0010190.00710.497199
2-0.072252-0.50060.309477
3-0.541975-3.75490.000234
4-0.123434-0.85520.198352
5-0.113667-0.78750.217428
6-0.225616-1.56310.062298
7-0.22261-1.54230.064785
8-0.095611-0.66240.255437
90.0448790.31090.378599
10-0.059024-0.40890.342204
110.006250.04330.482822
12-0.137988-0.9560.171929
13-0.010488-0.07270.471187
14-0.018535-0.12840.449178
15-0.061452-0.42580.336096
16-0.071977-0.49870.310145
17-0.01713-0.11870.453012
18-0.170694-1.18260.121395
19-0.148899-1.03160.153714
20-0.140419-0.97290.167751
210.1387310.96120.170646
22-0.039343-0.27260.393173
230.039160.27130.393658
24-0.114051-0.79020.216657
25-0.067619-0.46850.320782
26-0.007097-0.04920.480495
27-0.027256-0.18880.425509
28-0.102745-0.71180.240006
29-0.093522-0.64790.260057
30-0.071496-0.49530.311312
31-0.151982-1.0530.148815
32-0.119347-0.82690.206203
330.0798410.55320.291362
34-0.076223-0.52810.299935
35-0.039579-0.27420.39255
36-0.007338-0.05080.479832
37-0.017817-0.12340.451138
380.036150.25050.401652
39-0.002254-0.01560.493803
400.0156520.10840.457048
410.0874270.60570.27378
42-0.170419-1.18070.121771
43-0.007463-0.05170.479489
440.0137240.09510.462324
45-0.030191-0.20920.417602
46-0.00574-0.03980.484223
470.0542760.3760.354273
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')