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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 09 Dec 2008 06:37:42 -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/09/t12288299479rdlwvlf41ucqkw.htm/, Retrieved Sun, 19 May 2024 09:18:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31380, Retrieved Sun, 19 May 2024 09:18:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222
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]
- RMPD    [(Partial) Autocorrelation Function] [] [2008-12-09 13:37:42] [86e877ba38171644c8ca01af8044e645] [Current]
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Dataseries X:
75
38
20
6
11
38
54
44
37
39
4
49
45
29
20
9
16
3
56
53
35
49
11
54
47
31
21
14
9
16
61
57
40
42
7
43
56
29
34
14
25
39
53
39
32
40
1
47
39
39
20
7
43
43
21
39
35
38
12
37
34




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=31380&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=31380&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31380&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
1-0.009966-0.06980.472333
2-0.130082-0.91060.183488
30.027550.19290.423936
4-0.057121-0.39980.345503
50.1016760.71170.240003
60.0278720.19510.423058
7-0.110933-0.77650.220584
80.0159690.11180.455725
90.0332230.23260.408537
10-0.141447-0.99010.163488
110.261721.8320.036513
12-0.055208-0.38650.350417
13-0.138645-0.97050.168278
14-0.122783-0.85950.197131
150.0122880.0860.465903
160.0257670.18040.428802
170.0454940.31850.375746
18-0.005515-0.03860.48468
19-0.088289-0.6180.26971
200.0741690.51920.302984
21-0.093445-0.65410.258049
220.0469350.32850.371951
23-0.07922-0.55450.290865
24-0.213045-1.49130.071144
25-0.031871-0.22310.412195
260.0842330.58960.279073
27-0.047242-0.33070.371142
28-0.111565-0.7810.219292
29-0.104185-0.72930.234647
300.0016670.01170.495369
310.1713341.19930.118082
32-0.080387-0.56270.2881
330.0544760.38130.352304
340.0645560.45190.326671
35-0.142677-0.99870.161413
360.032070.22450.411656
370.1508221.05580.148129
380.015540.10880.456911
39-0.021145-0.1480.441469
40-0.089842-0.62890.26617
41-0.052931-0.37050.356296
420.1862991.30410.099148
430.0103960.07280.471143
44-0.022911-0.16040.436622
45-0.013391-0.09370.462849
46-0.04116-0.28810.387235
470.0436070.30530.380734
480.0173440.12140.451932
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 & -0.009966 & -0.0698 & 0.472333 \tabularnewline
2 & -0.130082 & -0.9106 & 0.183488 \tabularnewline
3 & 0.02755 & 0.1929 & 0.423936 \tabularnewline
4 & -0.057121 & -0.3998 & 0.345503 \tabularnewline
5 & 0.101676 & 0.7117 & 0.240003 \tabularnewline
6 & 0.027872 & 0.1951 & 0.423058 \tabularnewline
7 & -0.110933 & -0.7765 & 0.220584 \tabularnewline
8 & 0.015969 & 0.1118 & 0.455725 \tabularnewline
9 & 0.033223 & 0.2326 & 0.408537 \tabularnewline
10 & -0.141447 & -0.9901 & 0.163488 \tabularnewline
11 & 0.26172 & 1.832 & 0.036513 \tabularnewline
12 & -0.055208 & -0.3865 & 0.350417 \tabularnewline
13 & -0.138645 & -0.9705 & 0.168278 \tabularnewline
14 & -0.122783 & -0.8595 & 0.197131 \tabularnewline
15 & 0.012288 & 0.086 & 0.465903 \tabularnewline
16 & 0.025767 & 0.1804 & 0.428802 \tabularnewline
17 & 0.045494 & 0.3185 & 0.375746 \tabularnewline
18 & -0.005515 & -0.0386 & 0.48468 \tabularnewline
19 & -0.088289 & -0.618 & 0.26971 \tabularnewline
20 & 0.074169 & 0.5192 & 0.302984 \tabularnewline
21 & -0.093445 & -0.6541 & 0.258049 \tabularnewline
22 & 0.046935 & 0.3285 & 0.371951 \tabularnewline
23 & -0.07922 & -0.5545 & 0.290865 \tabularnewline
24 & -0.213045 & -1.4913 & 0.071144 \tabularnewline
25 & -0.031871 & -0.2231 & 0.412195 \tabularnewline
26 & 0.084233 & 0.5896 & 0.279073 \tabularnewline
27 & -0.047242 & -0.3307 & 0.371142 \tabularnewline
28 & -0.111565 & -0.781 & 0.219292 \tabularnewline
29 & -0.104185 & -0.7293 & 0.234647 \tabularnewline
30 & 0.001667 & 0.0117 & 0.495369 \tabularnewline
31 & 0.171334 & 1.1993 & 0.118082 \tabularnewline
32 & -0.080387 & -0.5627 & 0.2881 \tabularnewline
33 & 0.054476 & 0.3813 & 0.352304 \tabularnewline
34 & 0.064556 & 0.4519 & 0.326671 \tabularnewline
35 & -0.142677 & -0.9987 & 0.161413 \tabularnewline
36 & 0.03207 & 0.2245 & 0.411656 \tabularnewline
37 & 0.150822 & 1.0558 & 0.148129 \tabularnewline
38 & 0.01554 & 0.1088 & 0.456911 \tabularnewline
39 & -0.021145 & -0.148 & 0.441469 \tabularnewline
40 & -0.089842 & -0.6289 & 0.26617 \tabularnewline
41 & -0.052931 & -0.3705 & 0.356296 \tabularnewline
42 & 0.186299 & 1.3041 & 0.099148 \tabularnewline
43 & 0.010396 & 0.0728 & 0.471143 \tabularnewline
44 & -0.022911 & -0.1604 & 0.436622 \tabularnewline
45 & -0.013391 & -0.0937 & 0.462849 \tabularnewline
46 & -0.04116 & -0.2881 & 0.387235 \tabularnewline
47 & 0.043607 & 0.3053 & 0.380734 \tabularnewline
48 & 0.017344 & 0.1214 & 0.451932 \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=31380&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]-0.009966[/C][C]-0.0698[/C][C]0.472333[/C][/ROW]
[ROW][C]2[/C][C]-0.130082[/C][C]-0.9106[/C][C]0.183488[/C][/ROW]
[ROW][C]3[/C][C]0.02755[/C][C]0.1929[/C][C]0.423936[/C][/ROW]
[ROW][C]4[/C][C]-0.057121[/C][C]-0.3998[/C][C]0.345503[/C][/ROW]
[ROW][C]5[/C][C]0.101676[/C][C]0.7117[/C][C]0.240003[/C][/ROW]
[ROW][C]6[/C][C]0.027872[/C][C]0.1951[/C][C]0.423058[/C][/ROW]
[ROW][C]7[/C][C]-0.110933[/C][C]-0.7765[/C][C]0.220584[/C][/ROW]
[ROW][C]8[/C][C]0.015969[/C][C]0.1118[/C][C]0.455725[/C][/ROW]
[ROW][C]9[/C][C]0.033223[/C][C]0.2326[/C][C]0.408537[/C][/ROW]
[ROW][C]10[/C][C]-0.141447[/C][C]-0.9901[/C][C]0.163488[/C][/ROW]
[ROW][C]11[/C][C]0.26172[/C][C]1.832[/C][C]0.036513[/C][/ROW]
[ROW][C]12[/C][C]-0.055208[/C][C]-0.3865[/C][C]0.350417[/C][/ROW]
[ROW][C]13[/C][C]-0.138645[/C][C]-0.9705[/C][C]0.168278[/C][/ROW]
[ROW][C]14[/C][C]-0.122783[/C][C]-0.8595[/C][C]0.197131[/C][/ROW]
[ROW][C]15[/C][C]0.012288[/C][C]0.086[/C][C]0.465903[/C][/ROW]
[ROW][C]16[/C][C]0.025767[/C][C]0.1804[/C][C]0.428802[/C][/ROW]
[ROW][C]17[/C][C]0.045494[/C][C]0.3185[/C][C]0.375746[/C][/ROW]
[ROW][C]18[/C][C]-0.005515[/C][C]-0.0386[/C][C]0.48468[/C][/ROW]
[ROW][C]19[/C][C]-0.088289[/C][C]-0.618[/C][C]0.26971[/C][/ROW]
[ROW][C]20[/C][C]0.074169[/C][C]0.5192[/C][C]0.302984[/C][/ROW]
[ROW][C]21[/C][C]-0.093445[/C][C]-0.6541[/C][C]0.258049[/C][/ROW]
[ROW][C]22[/C][C]0.046935[/C][C]0.3285[/C][C]0.371951[/C][/ROW]
[ROW][C]23[/C][C]-0.07922[/C][C]-0.5545[/C][C]0.290865[/C][/ROW]
[ROW][C]24[/C][C]-0.213045[/C][C]-1.4913[/C][C]0.071144[/C][/ROW]
[ROW][C]25[/C][C]-0.031871[/C][C]-0.2231[/C][C]0.412195[/C][/ROW]
[ROW][C]26[/C][C]0.084233[/C][C]0.5896[/C][C]0.279073[/C][/ROW]
[ROW][C]27[/C][C]-0.047242[/C][C]-0.3307[/C][C]0.371142[/C][/ROW]
[ROW][C]28[/C][C]-0.111565[/C][C]-0.781[/C][C]0.219292[/C][/ROW]
[ROW][C]29[/C][C]-0.104185[/C][C]-0.7293[/C][C]0.234647[/C][/ROW]
[ROW][C]30[/C][C]0.001667[/C][C]0.0117[/C][C]0.495369[/C][/ROW]
[ROW][C]31[/C][C]0.171334[/C][C]1.1993[/C][C]0.118082[/C][/ROW]
[ROW][C]32[/C][C]-0.080387[/C][C]-0.5627[/C][C]0.2881[/C][/ROW]
[ROW][C]33[/C][C]0.054476[/C][C]0.3813[/C][C]0.352304[/C][/ROW]
[ROW][C]34[/C][C]0.064556[/C][C]0.4519[/C][C]0.326671[/C][/ROW]
[ROW][C]35[/C][C]-0.142677[/C][C]-0.9987[/C][C]0.161413[/C][/ROW]
[ROW][C]36[/C][C]0.03207[/C][C]0.2245[/C][C]0.411656[/C][/ROW]
[ROW][C]37[/C][C]0.150822[/C][C]1.0558[/C][C]0.148129[/C][/ROW]
[ROW][C]38[/C][C]0.01554[/C][C]0.1088[/C][C]0.456911[/C][/ROW]
[ROW][C]39[/C][C]-0.021145[/C][C]-0.148[/C][C]0.441469[/C][/ROW]
[ROW][C]40[/C][C]-0.089842[/C][C]-0.6289[/C][C]0.26617[/C][/ROW]
[ROW][C]41[/C][C]-0.052931[/C][C]-0.3705[/C][C]0.356296[/C][/ROW]
[ROW][C]42[/C][C]0.186299[/C][C]1.3041[/C][C]0.099148[/C][/ROW]
[ROW][C]43[/C][C]0.010396[/C][C]0.0728[/C][C]0.471143[/C][/ROW]
[ROW][C]44[/C][C]-0.022911[/C][C]-0.1604[/C][C]0.436622[/C][/ROW]
[ROW][C]45[/C][C]-0.013391[/C][C]-0.0937[/C][C]0.462849[/C][/ROW]
[ROW][C]46[/C][C]-0.04116[/C][C]-0.2881[/C][C]0.387235[/C][/ROW]
[ROW][C]47[/C][C]0.043607[/C][C]0.3053[/C][C]0.380734[/C][/ROW]
[ROW][C]48[/C][C]0.017344[/C][C]0.1214[/C][C]0.451932[/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=31380&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31380&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
1-0.009966-0.06980.472333
2-0.130082-0.91060.183488
30.027550.19290.423936
4-0.057121-0.39980.345503
50.1016760.71170.240003
60.0278720.19510.423058
7-0.110933-0.77650.220584
80.0159690.11180.455725
90.0332230.23260.408537
10-0.141447-0.99010.163488
110.261721.8320.036513
12-0.055208-0.38650.350417
13-0.138645-0.97050.168278
14-0.122783-0.85950.197131
150.0122880.0860.465903
160.0257670.18040.428802
170.0454940.31850.375746
18-0.005515-0.03860.48468
19-0.088289-0.6180.26971
200.0741690.51920.302984
21-0.093445-0.65410.258049
220.0469350.32850.371951
23-0.07922-0.55450.290865
24-0.213045-1.49130.071144
25-0.031871-0.22310.412195
260.0842330.58960.279073
27-0.047242-0.33070.371142
28-0.111565-0.7810.219292
29-0.104185-0.72930.234647
300.0016670.01170.495369
310.1713341.19930.118082
32-0.080387-0.56270.2881
330.0544760.38130.352304
340.0645560.45190.326671
35-0.142677-0.99870.161413
360.032070.22450.411656
370.1508221.05580.148129
380.015540.10880.456911
39-0.021145-0.1480.441469
40-0.089842-0.62890.26617
41-0.052931-0.37050.356296
420.1862991.30410.099148
430.0103960.07280.471143
44-0.022911-0.16040.436622
45-0.013391-0.09370.462849
46-0.04116-0.28810.387235
470.0436070.30530.380734
480.0173440.12140.451932
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.009966-0.06980.472333
2-0.130194-0.91140.183283
30.0252170.17650.430306
4-0.074872-0.52410.301284
50.1101850.77130.222117
60.0102240.07160.471619
7-0.080703-0.56490.287353
80.0107330.07510.470208
90.0202760.14190.443859
10-0.145746-1.02020.156316
110.2695931.88720.032535
12-0.098642-0.69050.246571
13-0.057637-0.40350.344183
14-0.204408-1.43090.079409
150.0794590.55620.290299
16-0.089734-0.62810.266415
170.0713450.49940.309862
180.0192710.13490.446623
19-0.039895-0.27930.390608
200.0013320.00930.496301
21-0.053434-0.3740.354996
22-0.014576-0.1020.459574
23-0.112137-0.7850.218129
24-0.208131-1.45690.075759
250.0287470.20120.420677
26-0.027301-0.19110.424616
27-0.05863-0.41040.341648
28-0.189857-1.3290.095002
29-0.121376-0.84960.199831
300.0128320.08980.464397
310.0762520.53380.29796
32-0.043498-0.30450.381025
330.0699310.48950.313329
340.0354220.2480.402602
35-0.127074-0.88950.189035
36-0.014282-0.10.460387
370.0665430.46580.321711
38-0.045487-0.31840.375763
390.0066560.04660.481515
40-0.068002-0.4760.318091
41-0.052308-0.36620.357913
42-0.02685-0.1880.425845
430.0188160.13170.447876
440.0301770.21120.416789
45-0.064622-0.45240.326505
460.0225180.15760.4377
470.0085990.06020.476124
48-0.141127-0.98790.16403
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 & -0.009966 & -0.0698 & 0.472333 \tabularnewline
2 & -0.130194 & -0.9114 & 0.183283 \tabularnewline
3 & 0.025217 & 0.1765 & 0.430306 \tabularnewline
4 & -0.074872 & -0.5241 & 0.301284 \tabularnewline
5 & 0.110185 & 0.7713 & 0.222117 \tabularnewline
6 & 0.010224 & 0.0716 & 0.471619 \tabularnewline
7 & -0.080703 & -0.5649 & 0.287353 \tabularnewline
8 & 0.010733 & 0.0751 & 0.470208 \tabularnewline
9 & 0.020276 & 0.1419 & 0.443859 \tabularnewline
10 & -0.145746 & -1.0202 & 0.156316 \tabularnewline
11 & 0.269593 & 1.8872 & 0.032535 \tabularnewline
12 & -0.098642 & -0.6905 & 0.246571 \tabularnewline
13 & -0.057637 & -0.4035 & 0.344183 \tabularnewline
14 & -0.204408 & -1.4309 & 0.079409 \tabularnewline
15 & 0.079459 & 0.5562 & 0.290299 \tabularnewline
16 & -0.089734 & -0.6281 & 0.266415 \tabularnewline
17 & 0.071345 & 0.4994 & 0.309862 \tabularnewline
18 & 0.019271 & 0.1349 & 0.446623 \tabularnewline
19 & -0.039895 & -0.2793 & 0.390608 \tabularnewline
20 & 0.001332 & 0.0093 & 0.496301 \tabularnewline
21 & -0.053434 & -0.374 & 0.354996 \tabularnewline
22 & -0.014576 & -0.102 & 0.459574 \tabularnewline
23 & -0.112137 & -0.785 & 0.218129 \tabularnewline
24 & -0.208131 & -1.4569 & 0.075759 \tabularnewline
25 & 0.028747 & 0.2012 & 0.420677 \tabularnewline
26 & -0.027301 & -0.1911 & 0.424616 \tabularnewline
27 & -0.05863 & -0.4104 & 0.341648 \tabularnewline
28 & -0.189857 & -1.329 & 0.095002 \tabularnewline
29 & -0.121376 & -0.8496 & 0.199831 \tabularnewline
30 & 0.012832 & 0.0898 & 0.464397 \tabularnewline
31 & 0.076252 & 0.5338 & 0.29796 \tabularnewline
32 & -0.043498 & -0.3045 & 0.381025 \tabularnewline
33 & 0.069931 & 0.4895 & 0.313329 \tabularnewline
34 & 0.035422 & 0.248 & 0.402602 \tabularnewline
35 & -0.127074 & -0.8895 & 0.189035 \tabularnewline
36 & -0.014282 & -0.1 & 0.460387 \tabularnewline
37 & 0.066543 & 0.4658 & 0.321711 \tabularnewline
38 & -0.045487 & -0.3184 & 0.375763 \tabularnewline
39 & 0.006656 & 0.0466 & 0.481515 \tabularnewline
40 & -0.068002 & -0.476 & 0.318091 \tabularnewline
41 & -0.052308 & -0.3662 & 0.357913 \tabularnewline
42 & -0.02685 & -0.188 & 0.425845 \tabularnewline
43 & 0.018816 & 0.1317 & 0.447876 \tabularnewline
44 & 0.030177 & 0.2112 & 0.416789 \tabularnewline
45 & -0.064622 & -0.4524 & 0.326505 \tabularnewline
46 & 0.022518 & 0.1576 & 0.4377 \tabularnewline
47 & 0.008599 & 0.0602 & 0.476124 \tabularnewline
48 & -0.141127 & -0.9879 & 0.16403 \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=31380&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]-0.009966[/C][C]-0.0698[/C][C]0.472333[/C][/ROW]
[ROW][C]2[/C][C]-0.130194[/C][C]-0.9114[/C][C]0.183283[/C][/ROW]
[ROW][C]3[/C][C]0.025217[/C][C]0.1765[/C][C]0.430306[/C][/ROW]
[ROW][C]4[/C][C]-0.074872[/C][C]-0.5241[/C][C]0.301284[/C][/ROW]
[ROW][C]5[/C][C]0.110185[/C][C]0.7713[/C][C]0.222117[/C][/ROW]
[ROW][C]6[/C][C]0.010224[/C][C]0.0716[/C][C]0.471619[/C][/ROW]
[ROW][C]7[/C][C]-0.080703[/C][C]-0.5649[/C][C]0.287353[/C][/ROW]
[ROW][C]8[/C][C]0.010733[/C][C]0.0751[/C][C]0.470208[/C][/ROW]
[ROW][C]9[/C][C]0.020276[/C][C]0.1419[/C][C]0.443859[/C][/ROW]
[ROW][C]10[/C][C]-0.145746[/C][C]-1.0202[/C][C]0.156316[/C][/ROW]
[ROW][C]11[/C][C]0.269593[/C][C]1.8872[/C][C]0.032535[/C][/ROW]
[ROW][C]12[/C][C]-0.098642[/C][C]-0.6905[/C][C]0.246571[/C][/ROW]
[ROW][C]13[/C][C]-0.057637[/C][C]-0.4035[/C][C]0.344183[/C][/ROW]
[ROW][C]14[/C][C]-0.204408[/C][C]-1.4309[/C][C]0.079409[/C][/ROW]
[ROW][C]15[/C][C]0.079459[/C][C]0.5562[/C][C]0.290299[/C][/ROW]
[ROW][C]16[/C][C]-0.089734[/C][C]-0.6281[/C][C]0.266415[/C][/ROW]
[ROW][C]17[/C][C]0.071345[/C][C]0.4994[/C][C]0.309862[/C][/ROW]
[ROW][C]18[/C][C]0.019271[/C][C]0.1349[/C][C]0.446623[/C][/ROW]
[ROW][C]19[/C][C]-0.039895[/C][C]-0.2793[/C][C]0.390608[/C][/ROW]
[ROW][C]20[/C][C]0.001332[/C][C]0.0093[/C][C]0.496301[/C][/ROW]
[ROW][C]21[/C][C]-0.053434[/C][C]-0.374[/C][C]0.354996[/C][/ROW]
[ROW][C]22[/C][C]-0.014576[/C][C]-0.102[/C][C]0.459574[/C][/ROW]
[ROW][C]23[/C][C]-0.112137[/C][C]-0.785[/C][C]0.218129[/C][/ROW]
[ROW][C]24[/C][C]-0.208131[/C][C]-1.4569[/C][C]0.075759[/C][/ROW]
[ROW][C]25[/C][C]0.028747[/C][C]0.2012[/C][C]0.420677[/C][/ROW]
[ROW][C]26[/C][C]-0.027301[/C][C]-0.1911[/C][C]0.424616[/C][/ROW]
[ROW][C]27[/C][C]-0.05863[/C][C]-0.4104[/C][C]0.341648[/C][/ROW]
[ROW][C]28[/C][C]-0.189857[/C][C]-1.329[/C][C]0.095002[/C][/ROW]
[ROW][C]29[/C][C]-0.121376[/C][C]-0.8496[/C][C]0.199831[/C][/ROW]
[ROW][C]30[/C][C]0.012832[/C][C]0.0898[/C][C]0.464397[/C][/ROW]
[ROW][C]31[/C][C]0.076252[/C][C]0.5338[/C][C]0.29796[/C][/ROW]
[ROW][C]32[/C][C]-0.043498[/C][C]-0.3045[/C][C]0.381025[/C][/ROW]
[ROW][C]33[/C][C]0.069931[/C][C]0.4895[/C][C]0.313329[/C][/ROW]
[ROW][C]34[/C][C]0.035422[/C][C]0.248[/C][C]0.402602[/C][/ROW]
[ROW][C]35[/C][C]-0.127074[/C][C]-0.8895[/C][C]0.189035[/C][/ROW]
[ROW][C]36[/C][C]-0.014282[/C][C]-0.1[/C][C]0.460387[/C][/ROW]
[ROW][C]37[/C][C]0.066543[/C][C]0.4658[/C][C]0.321711[/C][/ROW]
[ROW][C]38[/C][C]-0.045487[/C][C]-0.3184[/C][C]0.375763[/C][/ROW]
[ROW][C]39[/C][C]0.006656[/C][C]0.0466[/C][C]0.481515[/C][/ROW]
[ROW][C]40[/C][C]-0.068002[/C][C]-0.476[/C][C]0.318091[/C][/ROW]
[ROW][C]41[/C][C]-0.052308[/C][C]-0.3662[/C][C]0.357913[/C][/ROW]
[ROW][C]42[/C][C]-0.02685[/C][C]-0.188[/C][C]0.425845[/C][/ROW]
[ROW][C]43[/C][C]0.018816[/C][C]0.1317[/C][C]0.447876[/C][/ROW]
[ROW][C]44[/C][C]0.030177[/C][C]0.2112[/C][C]0.416789[/C][/ROW]
[ROW][C]45[/C][C]-0.064622[/C][C]-0.4524[/C][C]0.326505[/C][/ROW]
[ROW][C]46[/C][C]0.022518[/C][C]0.1576[/C][C]0.4377[/C][/ROW]
[ROW][C]47[/C][C]0.008599[/C][C]0.0602[/C][C]0.476124[/C][/ROW]
[ROW][C]48[/C][C]-0.141127[/C][C]-0.9879[/C][C]0.16403[/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=31380&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31380&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
1-0.009966-0.06980.472333
2-0.130194-0.91140.183283
30.0252170.17650.430306
4-0.074872-0.52410.301284
50.1101850.77130.222117
60.0102240.07160.471619
7-0.080703-0.56490.287353
80.0107330.07510.470208
90.0202760.14190.443859
10-0.145746-1.02020.156316
110.2695931.88720.032535
12-0.098642-0.69050.246571
13-0.057637-0.40350.344183
14-0.204408-1.43090.079409
150.0794590.55620.290299
16-0.089734-0.62810.266415
170.0713450.49940.309862
180.0192710.13490.446623
19-0.039895-0.27930.390608
200.0013320.00930.496301
21-0.053434-0.3740.354996
22-0.014576-0.1020.459574
23-0.112137-0.7850.218129
24-0.208131-1.45690.075759
250.0287470.20120.420677
26-0.027301-0.19110.424616
27-0.05863-0.41040.341648
28-0.189857-1.3290.095002
29-0.121376-0.84960.199831
300.0128320.08980.464397
310.0762520.53380.29796
32-0.043498-0.30450.381025
330.0699310.48950.313329
340.0354220.2480.402602
35-0.127074-0.88950.189035
36-0.014282-0.10.460387
370.0665430.46580.321711
38-0.045487-0.31840.375763
390.0066560.04660.481515
40-0.068002-0.4760.318091
41-0.052308-0.36620.357913
42-0.02685-0.1880.425845
430.0188160.13170.447876
440.0301770.21120.416789
45-0.064622-0.45240.326505
460.0225180.15760.4377
470.0085990.06020.476124
48-0.141127-0.98790.16403
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; 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')