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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, 10 Dec 2009 15:51:31 -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/10/t1260485533af9199kf0aqu88z.htm/, Retrieved Thu, 18 Apr 2024 03:05:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65841, Retrieved Thu, 18 Apr 2024 03:05:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsverbetering 4
Estimated Impact181
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Paper statistiek:...] [2009-12-04 15:31:04] [3cb427d596a5d2eb77fa64560dc91319]
-   P     [(Partial) Autocorrelation Function] [Workshop 9] [2009-12-10 22:51:31] [682632737e024f9e62885141c5f654cd] [Current]
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Dataseries X:
1.43
1.43
1.43
1.43
1.43
1.43
1.44
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.57
1.58
1.58
1.58
1.58
1.59
1.6
1.6
1.61
1.61
1.61
1.62
1.63
1.63
1.64
1.64
1.64
1.64
1.64
1.65
1.65
1.65
1.65




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=65841&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=65841&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65841&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
1-0.428571-3.26390.000923
2-0.076923-0.58580.280132
30.0109890.08370.466796
4-0.06044-0.46030.323513
50.0549450.41840.338582
60.0494510.37660.353921
7-0.093407-0.71140.239855
80.0989010.75320.227186
9-0.054945-0.41840.338582
10-0.054945-0.41840.338582
110.0659340.50210.308735
120.0274730.20920.417503
13-0.082418-0.62770.266341
140.0989010.75320.227186
15-0.054945-0.41840.338582
16000.5
17-0.005495-0.04180.483383
18-0.038462-0.29290.385317
190.0934070.71140.239855
20-0.049451-0.37660.353921
21000.5
22000.5
23000.5
24000.5
25000.5
26000.5
27000.5
28000.5
29-0.197802-1.50640.068694
300.3241762.46880.008261
31-0.06044-0.46030.323513
32-0.06044-0.46030.323513
33-0.005495-0.04180.483383
34-0.021978-0.16740.433827
350.0164840.12550.450267
360.0274730.20920.417503
37-0.038462-0.29290.385317
380.0329670.25110.401324
39-0.010989-0.08370.466796
40-0.027473-0.20920.417503
410.0164840.12550.450267
420.0274730.20920.417503
43-0.038462-0.29290.385317
440.0329670.25110.401324
45-0.010989-0.08370.466796
46-0.005495-0.04180.483383
47000.5
48-0.021978-0.16740.433827
490.0384620.29290.385317
50-0.010989-0.08370.466796
51-0.005495-0.04180.483383
52000.5
53000.5
54000.5
55000.5
56000.5
57000.5
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.428571 & -3.2639 & 0.000923 \tabularnewline
2 & -0.076923 & -0.5858 & 0.280132 \tabularnewline
3 & 0.010989 & 0.0837 & 0.466796 \tabularnewline
4 & -0.06044 & -0.4603 & 0.323513 \tabularnewline
5 & 0.054945 & 0.4184 & 0.338582 \tabularnewline
6 & 0.049451 & 0.3766 & 0.353921 \tabularnewline
7 & -0.093407 & -0.7114 & 0.239855 \tabularnewline
8 & 0.098901 & 0.7532 & 0.227186 \tabularnewline
9 & -0.054945 & -0.4184 & 0.338582 \tabularnewline
10 & -0.054945 & -0.4184 & 0.338582 \tabularnewline
11 & 0.065934 & 0.5021 & 0.308735 \tabularnewline
12 & 0.027473 & 0.2092 & 0.417503 \tabularnewline
13 & -0.082418 & -0.6277 & 0.266341 \tabularnewline
14 & 0.098901 & 0.7532 & 0.227186 \tabularnewline
15 & -0.054945 & -0.4184 & 0.338582 \tabularnewline
16 & 0 & 0 & 0.5 \tabularnewline
17 & -0.005495 & -0.0418 & 0.483383 \tabularnewline
18 & -0.038462 & -0.2929 & 0.385317 \tabularnewline
19 & 0.093407 & 0.7114 & 0.239855 \tabularnewline
20 & -0.049451 & -0.3766 & 0.353921 \tabularnewline
21 & 0 & 0 & 0.5 \tabularnewline
22 & 0 & 0 & 0.5 \tabularnewline
23 & 0 & 0 & 0.5 \tabularnewline
24 & 0 & 0 & 0.5 \tabularnewline
25 & 0 & 0 & 0.5 \tabularnewline
26 & 0 & 0 & 0.5 \tabularnewline
27 & 0 & 0 & 0.5 \tabularnewline
28 & 0 & 0 & 0.5 \tabularnewline
29 & -0.197802 & -1.5064 & 0.068694 \tabularnewline
30 & 0.324176 & 2.4688 & 0.008261 \tabularnewline
31 & -0.06044 & -0.4603 & 0.323513 \tabularnewline
32 & -0.06044 & -0.4603 & 0.323513 \tabularnewline
33 & -0.005495 & -0.0418 & 0.483383 \tabularnewline
34 & -0.021978 & -0.1674 & 0.433827 \tabularnewline
35 & 0.016484 & 0.1255 & 0.450267 \tabularnewline
36 & 0.027473 & 0.2092 & 0.417503 \tabularnewline
37 & -0.038462 & -0.2929 & 0.385317 \tabularnewline
38 & 0.032967 & 0.2511 & 0.401324 \tabularnewline
39 & -0.010989 & -0.0837 & 0.466796 \tabularnewline
40 & -0.027473 & -0.2092 & 0.417503 \tabularnewline
41 & 0.016484 & 0.1255 & 0.450267 \tabularnewline
42 & 0.027473 & 0.2092 & 0.417503 \tabularnewline
43 & -0.038462 & -0.2929 & 0.385317 \tabularnewline
44 & 0.032967 & 0.2511 & 0.401324 \tabularnewline
45 & -0.010989 & -0.0837 & 0.466796 \tabularnewline
46 & -0.005495 & -0.0418 & 0.483383 \tabularnewline
47 & 0 & 0 & 0.5 \tabularnewline
48 & -0.021978 & -0.1674 & 0.433827 \tabularnewline
49 & 0.038462 & 0.2929 & 0.385317 \tabularnewline
50 & -0.010989 & -0.0837 & 0.466796 \tabularnewline
51 & -0.005495 & -0.0418 & 0.483383 \tabularnewline
52 & 0 & 0 & 0.5 \tabularnewline
53 & 0 & 0 & 0.5 \tabularnewline
54 & 0 & 0 & 0.5 \tabularnewline
55 & 0 & 0 & 0.5 \tabularnewline
56 & 0 & 0 & 0.5 \tabularnewline
57 & 0 & 0 & 0.5 \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=65841&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]-0.428571[/C][C]-3.2639[/C][C]0.000923[/C][/ROW]
[ROW][C]2[/C][C]-0.076923[/C][C]-0.5858[/C][C]0.280132[/C][/ROW]
[ROW][C]3[/C][C]0.010989[/C][C]0.0837[/C][C]0.466796[/C][/ROW]
[ROW][C]4[/C][C]-0.06044[/C][C]-0.4603[/C][C]0.323513[/C][/ROW]
[ROW][C]5[/C][C]0.054945[/C][C]0.4184[/C][C]0.338582[/C][/ROW]
[ROW][C]6[/C][C]0.049451[/C][C]0.3766[/C][C]0.353921[/C][/ROW]
[ROW][C]7[/C][C]-0.093407[/C][C]-0.7114[/C][C]0.239855[/C][/ROW]
[ROW][C]8[/C][C]0.098901[/C][C]0.7532[/C][C]0.227186[/C][/ROW]
[ROW][C]9[/C][C]-0.054945[/C][C]-0.4184[/C][C]0.338582[/C][/ROW]
[ROW][C]10[/C][C]-0.054945[/C][C]-0.4184[/C][C]0.338582[/C][/ROW]
[ROW][C]11[/C][C]0.065934[/C][C]0.5021[/C][C]0.308735[/C][/ROW]
[ROW][C]12[/C][C]0.027473[/C][C]0.2092[/C][C]0.417503[/C][/ROW]
[ROW][C]13[/C][C]-0.082418[/C][C]-0.6277[/C][C]0.266341[/C][/ROW]
[ROW][C]14[/C][C]0.098901[/C][C]0.7532[/C][C]0.227186[/C][/ROW]
[ROW][C]15[/C][C]-0.054945[/C][C]-0.4184[/C][C]0.338582[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]17[/C][C]-0.005495[/C][C]-0.0418[/C][C]0.483383[/C][/ROW]
[ROW][C]18[/C][C]-0.038462[/C][C]-0.2929[/C][C]0.385317[/C][/ROW]
[ROW][C]19[/C][C]0.093407[/C][C]0.7114[/C][C]0.239855[/C][/ROW]
[ROW][C]20[/C][C]-0.049451[/C][C]-0.3766[/C][C]0.353921[/C][/ROW]
[ROW][C]21[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]22[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]23[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]24[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]25[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]26[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]27[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]29[/C][C]-0.197802[/C][C]-1.5064[/C][C]0.068694[/C][/ROW]
[ROW][C]30[/C][C]0.324176[/C][C]2.4688[/C][C]0.008261[/C][/ROW]
[ROW][C]31[/C][C]-0.06044[/C][C]-0.4603[/C][C]0.323513[/C][/ROW]
[ROW][C]32[/C][C]-0.06044[/C][C]-0.4603[/C][C]0.323513[/C][/ROW]
[ROW][C]33[/C][C]-0.005495[/C][C]-0.0418[/C][C]0.483383[/C][/ROW]
[ROW][C]34[/C][C]-0.021978[/C][C]-0.1674[/C][C]0.433827[/C][/ROW]
[ROW][C]35[/C][C]0.016484[/C][C]0.1255[/C][C]0.450267[/C][/ROW]
[ROW][C]36[/C][C]0.027473[/C][C]0.2092[/C][C]0.417503[/C][/ROW]
[ROW][C]37[/C][C]-0.038462[/C][C]-0.2929[/C][C]0.385317[/C][/ROW]
[ROW][C]38[/C][C]0.032967[/C][C]0.2511[/C][C]0.401324[/C][/ROW]
[ROW][C]39[/C][C]-0.010989[/C][C]-0.0837[/C][C]0.466796[/C][/ROW]
[ROW][C]40[/C][C]-0.027473[/C][C]-0.2092[/C][C]0.417503[/C][/ROW]
[ROW][C]41[/C][C]0.016484[/C][C]0.1255[/C][C]0.450267[/C][/ROW]
[ROW][C]42[/C][C]0.027473[/C][C]0.2092[/C][C]0.417503[/C][/ROW]
[ROW][C]43[/C][C]-0.038462[/C][C]-0.2929[/C][C]0.385317[/C][/ROW]
[ROW][C]44[/C][C]0.032967[/C][C]0.2511[/C][C]0.401324[/C][/ROW]
[ROW][C]45[/C][C]-0.010989[/C][C]-0.0837[/C][C]0.466796[/C][/ROW]
[ROW][C]46[/C][C]-0.005495[/C][C]-0.0418[/C][C]0.483383[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]48[/C][C]-0.021978[/C][C]-0.1674[/C][C]0.433827[/C][/ROW]
[ROW][C]49[/C][C]0.038462[/C][C]0.2929[/C][C]0.385317[/C][/ROW]
[ROW][C]50[/C][C]-0.010989[/C][C]-0.0837[/C][C]0.466796[/C][/ROW]
[ROW][C]51[/C][C]-0.005495[/C][C]-0.0418[/C][C]0.483383[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]55[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]56[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]0[/C][C]0.5[/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=65841&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65841&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
1-0.428571-3.26390.000923
2-0.076923-0.58580.280132
30.0109890.08370.466796
4-0.06044-0.46030.323513
50.0549450.41840.338582
60.0494510.37660.353921
7-0.093407-0.71140.239855
80.0989010.75320.227186
9-0.054945-0.41840.338582
10-0.054945-0.41840.338582
110.0659340.50210.308735
120.0274730.20920.417503
13-0.082418-0.62770.266341
140.0989010.75320.227186
15-0.054945-0.41840.338582
16000.5
17-0.005495-0.04180.483383
18-0.038462-0.29290.385317
190.0934070.71140.239855
20-0.049451-0.37660.353921
21000.5
22000.5
23000.5
24000.5
25000.5
26000.5
27000.5
28000.5
29-0.197802-1.50640.068694
300.3241762.46880.008261
31-0.06044-0.46030.323513
32-0.06044-0.46030.323513
33-0.005495-0.04180.483383
34-0.021978-0.16740.433827
350.0164840.12550.450267
360.0274730.20920.417503
37-0.038462-0.29290.385317
380.0329670.25110.401324
39-0.010989-0.08370.466796
40-0.027473-0.20920.417503
410.0164840.12550.450267
420.0274730.20920.417503
43-0.038462-0.29290.385317
440.0329670.25110.401324
45-0.010989-0.08370.466796
46-0.005495-0.04180.483383
47000.5
48-0.021978-0.16740.433827
490.0384620.29290.385317
50-0.010989-0.08370.466796
51-0.005495-0.04180.483383
52000.5
53000.5
54000.5
55000.5
56000.5
57000.5
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.428571-3.26390.000923
2-0.319231-2.43120.00908
3-0.230947-1.75880.04194
4-0.269431-2.05190.02235
5-0.198321-1.51040.068189
6-0.095687-0.72870.23455
7-0.176395-1.34340.09219
8-0.044556-0.33930.367793
9-0.064261-0.48940.313204
10-0.139123-1.05950.146875
11-0.098559-0.75060.227963
12-0.023037-0.17540.43067
13-0.119234-0.90810.183802
14-0.010854-0.08270.467204
15-0.011629-0.08860.464865
16-0.009952-0.07580.469922
17-0.038561-0.29370.385028
18-0.087236-0.66440.254544
190.0116430.08870.464824
20-0.046992-0.35790.360865
21-0.008318-0.06330.474855
22-0.028423-0.21650.414694
23-0.016189-0.12330.45115
24-0.013642-0.10390.458805
25-0.02567-0.19550.422843
26-0.023733-0.18070.428599
27-0.035755-0.27230.39318
28-0.032056-0.24410.403997
29-0.377638-2.8760.002813
30-0.050805-0.38690.350117
31-0.012796-0.09740.461353
320.0043270.0330.486913
33-0.021389-0.16290.435584
340.0193320.14720.441732
350.014880.11330.455082
36-0.012407-0.09450.462522
370.024520.18670.426258
38-0.0221-0.16830.433463
39-0.006029-0.04590.481767
40-0.000419-0.00320.498732
410.0137470.10470.45849
42-0.017908-0.13640.445995
430.0160530.12230.451558
44-0.010751-0.08190.467513
45-0.031172-0.23740.406591
46-0.017942-0.13660.445893
47-0.023872-0.18180.428186
48-0.004286-0.03260.487037
49-0.024653-0.18780.425862
50-0.003329-0.02540.489929
51-0.032376-0.24660.403056
52-0.01152-0.08770.465196
53-0.023377-0.1780.429657
54-0.031216-0.23770.406462
55-0.01655-0.1260.450067
56-0.011591-0.08830.464982
57-0.003859-0.02940.488327
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.428571 & -3.2639 & 0.000923 \tabularnewline
2 & -0.319231 & -2.4312 & 0.00908 \tabularnewline
3 & -0.230947 & -1.7588 & 0.04194 \tabularnewline
4 & -0.269431 & -2.0519 & 0.02235 \tabularnewline
5 & -0.198321 & -1.5104 & 0.068189 \tabularnewline
6 & -0.095687 & -0.7287 & 0.23455 \tabularnewline
7 & -0.176395 & -1.3434 & 0.09219 \tabularnewline
8 & -0.044556 & -0.3393 & 0.367793 \tabularnewline
9 & -0.064261 & -0.4894 & 0.313204 \tabularnewline
10 & -0.139123 & -1.0595 & 0.146875 \tabularnewline
11 & -0.098559 & -0.7506 & 0.227963 \tabularnewline
12 & -0.023037 & -0.1754 & 0.43067 \tabularnewline
13 & -0.119234 & -0.9081 & 0.183802 \tabularnewline
14 & -0.010854 & -0.0827 & 0.467204 \tabularnewline
15 & -0.011629 & -0.0886 & 0.464865 \tabularnewline
16 & -0.009952 & -0.0758 & 0.469922 \tabularnewline
17 & -0.038561 & -0.2937 & 0.385028 \tabularnewline
18 & -0.087236 & -0.6644 & 0.254544 \tabularnewline
19 & 0.011643 & 0.0887 & 0.464824 \tabularnewline
20 & -0.046992 & -0.3579 & 0.360865 \tabularnewline
21 & -0.008318 & -0.0633 & 0.474855 \tabularnewline
22 & -0.028423 & -0.2165 & 0.414694 \tabularnewline
23 & -0.016189 & -0.1233 & 0.45115 \tabularnewline
24 & -0.013642 & -0.1039 & 0.458805 \tabularnewline
25 & -0.02567 & -0.1955 & 0.422843 \tabularnewline
26 & -0.023733 & -0.1807 & 0.428599 \tabularnewline
27 & -0.035755 & -0.2723 & 0.39318 \tabularnewline
28 & -0.032056 & -0.2441 & 0.403997 \tabularnewline
29 & -0.377638 & -2.876 & 0.002813 \tabularnewline
30 & -0.050805 & -0.3869 & 0.350117 \tabularnewline
31 & -0.012796 & -0.0974 & 0.461353 \tabularnewline
32 & 0.004327 & 0.033 & 0.486913 \tabularnewline
33 & -0.021389 & -0.1629 & 0.435584 \tabularnewline
34 & 0.019332 & 0.1472 & 0.441732 \tabularnewline
35 & 0.01488 & 0.1133 & 0.455082 \tabularnewline
36 & -0.012407 & -0.0945 & 0.462522 \tabularnewline
37 & 0.02452 & 0.1867 & 0.426258 \tabularnewline
38 & -0.0221 & -0.1683 & 0.433463 \tabularnewline
39 & -0.006029 & -0.0459 & 0.481767 \tabularnewline
40 & -0.000419 & -0.0032 & 0.498732 \tabularnewline
41 & 0.013747 & 0.1047 & 0.45849 \tabularnewline
42 & -0.017908 & -0.1364 & 0.445995 \tabularnewline
43 & 0.016053 & 0.1223 & 0.451558 \tabularnewline
44 & -0.010751 & -0.0819 & 0.467513 \tabularnewline
45 & -0.031172 & -0.2374 & 0.406591 \tabularnewline
46 & -0.017942 & -0.1366 & 0.445893 \tabularnewline
47 & -0.023872 & -0.1818 & 0.428186 \tabularnewline
48 & -0.004286 & -0.0326 & 0.487037 \tabularnewline
49 & -0.024653 & -0.1878 & 0.425862 \tabularnewline
50 & -0.003329 & -0.0254 & 0.489929 \tabularnewline
51 & -0.032376 & -0.2466 & 0.403056 \tabularnewline
52 & -0.01152 & -0.0877 & 0.465196 \tabularnewline
53 & -0.023377 & -0.178 & 0.429657 \tabularnewline
54 & -0.031216 & -0.2377 & 0.406462 \tabularnewline
55 & -0.01655 & -0.126 & 0.450067 \tabularnewline
56 & -0.011591 & -0.0883 & 0.464982 \tabularnewline
57 & -0.003859 & -0.0294 & 0.488327 \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=65841&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]-0.428571[/C][C]-3.2639[/C][C]0.000923[/C][/ROW]
[ROW][C]2[/C][C]-0.319231[/C][C]-2.4312[/C][C]0.00908[/C][/ROW]
[ROW][C]3[/C][C]-0.230947[/C][C]-1.7588[/C][C]0.04194[/C][/ROW]
[ROW][C]4[/C][C]-0.269431[/C][C]-2.0519[/C][C]0.02235[/C][/ROW]
[ROW][C]5[/C][C]-0.198321[/C][C]-1.5104[/C][C]0.068189[/C][/ROW]
[ROW][C]6[/C][C]-0.095687[/C][C]-0.7287[/C][C]0.23455[/C][/ROW]
[ROW][C]7[/C][C]-0.176395[/C][C]-1.3434[/C][C]0.09219[/C][/ROW]
[ROW][C]8[/C][C]-0.044556[/C][C]-0.3393[/C][C]0.367793[/C][/ROW]
[ROW][C]9[/C][C]-0.064261[/C][C]-0.4894[/C][C]0.313204[/C][/ROW]
[ROW][C]10[/C][C]-0.139123[/C][C]-1.0595[/C][C]0.146875[/C][/ROW]
[ROW][C]11[/C][C]-0.098559[/C][C]-0.7506[/C][C]0.227963[/C][/ROW]
[ROW][C]12[/C][C]-0.023037[/C][C]-0.1754[/C][C]0.43067[/C][/ROW]
[ROW][C]13[/C][C]-0.119234[/C][C]-0.9081[/C][C]0.183802[/C][/ROW]
[ROW][C]14[/C][C]-0.010854[/C][C]-0.0827[/C][C]0.467204[/C][/ROW]
[ROW][C]15[/C][C]-0.011629[/C][C]-0.0886[/C][C]0.464865[/C][/ROW]
[ROW][C]16[/C][C]-0.009952[/C][C]-0.0758[/C][C]0.469922[/C][/ROW]
[ROW][C]17[/C][C]-0.038561[/C][C]-0.2937[/C][C]0.385028[/C][/ROW]
[ROW][C]18[/C][C]-0.087236[/C][C]-0.6644[/C][C]0.254544[/C][/ROW]
[ROW][C]19[/C][C]0.011643[/C][C]0.0887[/C][C]0.464824[/C][/ROW]
[ROW][C]20[/C][C]-0.046992[/C][C]-0.3579[/C][C]0.360865[/C][/ROW]
[ROW][C]21[/C][C]-0.008318[/C][C]-0.0633[/C][C]0.474855[/C][/ROW]
[ROW][C]22[/C][C]-0.028423[/C][C]-0.2165[/C][C]0.414694[/C][/ROW]
[ROW][C]23[/C][C]-0.016189[/C][C]-0.1233[/C][C]0.45115[/C][/ROW]
[ROW][C]24[/C][C]-0.013642[/C][C]-0.1039[/C][C]0.458805[/C][/ROW]
[ROW][C]25[/C][C]-0.02567[/C][C]-0.1955[/C][C]0.422843[/C][/ROW]
[ROW][C]26[/C][C]-0.023733[/C][C]-0.1807[/C][C]0.428599[/C][/ROW]
[ROW][C]27[/C][C]-0.035755[/C][C]-0.2723[/C][C]0.39318[/C][/ROW]
[ROW][C]28[/C][C]-0.032056[/C][C]-0.2441[/C][C]0.403997[/C][/ROW]
[ROW][C]29[/C][C]-0.377638[/C][C]-2.876[/C][C]0.002813[/C][/ROW]
[ROW][C]30[/C][C]-0.050805[/C][C]-0.3869[/C][C]0.350117[/C][/ROW]
[ROW][C]31[/C][C]-0.012796[/C][C]-0.0974[/C][C]0.461353[/C][/ROW]
[ROW][C]32[/C][C]0.004327[/C][C]0.033[/C][C]0.486913[/C][/ROW]
[ROW][C]33[/C][C]-0.021389[/C][C]-0.1629[/C][C]0.435584[/C][/ROW]
[ROW][C]34[/C][C]0.019332[/C][C]0.1472[/C][C]0.441732[/C][/ROW]
[ROW][C]35[/C][C]0.01488[/C][C]0.1133[/C][C]0.455082[/C][/ROW]
[ROW][C]36[/C][C]-0.012407[/C][C]-0.0945[/C][C]0.462522[/C][/ROW]
[ROW][C]37[/C][C]0.02452[/C][C]0.1867[/C][C]0.426258[/C][/ROW]
[ROW][C]38[/C][C]-0.0221[/C][C]-0.1683[/C][C]0.433463[/C][/ROW]
[ROW][C]39[/C][C]-0.006029[/C][C]-0.0459[/C][C]0.481767[/C][/ROW]
[ROW][C]40[/C][C]-0.000419[/C][C]-0.0032[/C][C]0.498732[/C][/ROW]
[ROW][C]41[/C][C]0.013747[/C][C]0.1047[/C][C]0.45849[/C][/ROW]
[ROW][C]42[/C][C]-0.017908[/C][C]-0.1364[/C][C]0.445995[/C][/ROW]
[ROW][C]43[/C][C]0.016053[/C][C]0.1223[/C][C]0.451558[/C][/ROW]
[ROW][C]44[/C][C]-0.010751[/C][C]-0.0819[/C][C]0.467513[/C][/ROW]
[ROW][C]45[/C][C]-0.031172[/C][C]-0.2374[/C][C]0.406591[/C][/ROW]
[ROW][C]46[/C][C]-0.017942[/C][C]-0.1366[/C][C]0.445893[/C][/ROW]
[ROW][C]47[/C][C]-0.023872[/C][C]-0.1818[/C][C]0.428186[/C][/ROW]
[ROW][C]48[/C][C]-0.004286[/C][C]-0.0326[/C][C]0.487037[/C][/ROW]
[ROW][C]49[/C][C]-0.024653[/C][C]-0.1878[/C][C]0.425862[/C][/ROW]
[ROW][C]50[/C][C]-0.003329[/C][C]-0.0254[/C][C]0.489929[/C][/ROW]
[ROW][C]51[/C][C]-0.032376[/C][C]-0.2466[/C][C]0.403056[/C][/ROW]
[ROW][C]52[/C][C]-0.01152[/C][C]-0.0877[/C][C]0.465196[/C][/ROW]
[ROW][C]53[/C][C]-0.023377[/C][C]-0.178[/C][C]0.429657[/C][/ROW]
[ROW][C]54[/C][C]-0.031216[/C][C]-0.2377[/C][C]0.406462[/C][/ROW]
[ROW][C]55[/C][C]-0.01655[/C][C]-0.126[/C][C]0.450067[/C][/ROW]
[ROW][C]56[/C][C]-0.011591[/C][C]-0.0883[/C][C]0.464982[/C][/ROW]
[ROW][C]57[/C][C]-0.003859[/C][C]-0.0294[/C][C]0.488327[/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=65841&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65841&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
1-0.428571-3.26390.000923
2-0.319231-2.43120.00908
3-0.230947-1.75880.04194
4-0.269431-2.05190.02235
5-0.198321-1.51040.068189
6-0.095687-0.72870.23455
7-0.176395-1.34340.09219
8-0.044556-0.33930.367793
9-0.064261-0.48940.313204
10-0.139123-1.05950.146875
11-0.098559-0.75060.227963
12-0.023037-0.17540.43067
13-0.119234-0.90810.183802
14-0.010854-0.08270.467204
15-0.011629-0.08860.464865
16-0.009952-0.07580.469922
17-0.038561-0.29370.385028
18-0.087236-0.66440.254544
190.0116430.08870.464824
20-0.046992-0.35790.360865
21-0.008318-0.06330.474855
22-0.028423-0.21650.414694
23-0.016189-0.12330.45115
24-0.013642-0.10390.458805
25-0.02567-0.19550.422843
26-0.023733-0.18070.428599
27-0.035755-0.27230.39318
28-0.032056-0.24410.403997
29-0.377638-2.8760.002813
30-0.050805-0.38690.350117
31-0.012796-0.09740.461353
320.0043270.0330.486913
33-0.021389-0.16290.435584
340.0193320.14720.441732
350.014880.11330.455082
36-0.012407-0.09450.462522
370.024520.18670.426258
38-0.0221-0.16830.433463
39-0.006029-0.04590.481767
40-0.000419-0.00320.498732
410.0137470.10470.45849
42-0.017908-0.13640.445995
430.0160530.12230.451558
44-0.010751-0.08190.467513
45-0.031172-0.23740.406591
46-0.017942-0.13660.445893
47-0.023872-0.18180.428186
48-0.004286-0.03260.487037
49-0.024653-0.18780.425862
50-0.003329-0.02540.489929
51-0.032376-0.24660.403056
52-0.01152-0.08770.465196
53-0.023377-0.1780.429657
54-0.031216-0.23770.406462
55-0.01655-0.1260.450067
56-0.011591-0.08830.464982
57-0.003859-0.02940.488327
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')