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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 20 Dec 2010 14:29:20 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/20/t1292855232gw2osv30ctwgqxy.htm/, Retrieved Fri, 03 May 2024 17:24:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112962, Retrieved Fri, 03 May 2024 17:24:52 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [Test] [2010-12-05 10:22:51] [74be16979710d4c4e7c6647856088456]
-   P       [(Partial) Autocorrelation Function] [W9 - Blog 2] [2010-12-06 15:12:52] [1aa8d85d6b335d32b1f6be940e33a166]
-   PD          [(Partial) Autocorrelation Function] [ACF d=1D=0 Likeur] [2010-12-20 14:29:20] [47bfda5353cd53c1cf7ea7aa9038654a] [Current]
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Dataseries X:
25,00
25,09
25,03
25,21
25,33
25,23
25,13
25,03
25,03
25,15
25,18
24,90
25,18
25,25
25,28
25,32
25,27
25,22
25,14
25,41
25,72
25,66
25,65
25,27
23,90
24,06
24,33
24,39
24,39
24,49
24,83
25,08
25,11
25,13
25,17
25,11
25,35
25,36
25,35
25,34
25,39
25,58
25,71
25,66
25,74
25,73
25,72
25,55
25,71
25,92
25,93
26,00
26,02
26,08
26,17
26,18
26,21
26,28
26,34
26,17
26,38
26,36
26,27
26,26
26,49
26,99
27,14
27,10
27,01
26,93
26,97
26,35
26,93




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=112962&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=112962&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112962&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0612190.51950.302516
2-0.113957-0.9670.168402
3-0.071204-0.60420.273809
4-0.126158-1.07050.143988
5-0.074745-0.63420.26397
6-0.092614-0.78590.217264
7-0.018258-0.15490.438658
80.0217470.18450.427057
9-0.013309-0.11290.4552
100.0192860.16360.435233
110.0214660.18210.427989
12-0.030156-0.25590.399385
130.0278960.23670.406777
14-0.023853-0.20240.420087
15-0.022452-0.19050.424723
160.0836680.70990.240015
170.0154570.13120.448009
18-0.002686-0.02280.49094
190.0307150.26060.397562
20-0.111299-0.94440.174061
21-0.02262-0.19190.424166
220.0470830.39950.345348
230.0675050.57280.284284
240.0637070.54060.295234
25-0.125525-1.06510.145192
26-0.023432-0.19880.42148
27-0.030723-0.26070.397536
280.0224720.19070.424657
290.0119910.10170.459622
30-0.027008-0.22920.409693
31-0.00734-0.06230.475257
320.0047190.040.484086
33-0.017473-0.14830.441275
340.0214140.18170.428163
350.0629810.53440.297352
360.0172760.14660.441931
37-0.027115-0.23010.409342
380.0424950.36060.359734
390.0413970.35130.363208
40-0.06986-0.59280.277591
41-0.176857-1.50070.068906
42-0.087361-0.74130.230467
43-0.021387-0.18150.428252
440.0275740.2340.407835
450.0776070.65850.256154
460.0487910.4140.340051
470.2099611.78160.039517
48-0.121212-1.02850.153574

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.061219 & 0.5195 & 0.302516 \tabularnewline
2 & -0.113957 & -0.967 & 0.168402 \tabularnewline
3 & -0.071204 & -0.6042 & 0.273809 \tabularnewline
4 & -0.126158 & -1.0705 & 0.143988 \tabularnewline
5 & -0.074745 & -0.6342 & 0.26397 \tabularnewline
6 & -0.092614 & -0.7859 & 0.217264 \tabularnewline
7 & -0.018258 & -0.1549 & 0.438658 \tabularnewline
8 & 0.021747 & 0.1845 & 0.427057 \tabularnewline
9 & -0.013309 & -0.1129 & 0.4552 \tabularnewline
10 & 0.019286 & 0.1636 & 0.435233 \tabularnewline
11 & 0.021466 & 0.1821 & 0.427989 \tabularnewline
12 & -0.030156 & -0.2559 & 0.399385 \tabularnewline
13 & 0.027896 & 0.2367 & 0.406777 \tabularnewline
14 & -0.023853 & -0.2024 & 0.420087 \tabularnewline
15 & -0.022452 & -0.1905 & 0.424723 \tabularnewline
16 & 0.083668 & 0.7099 & 0.240015 \tabularnewline
17 & 0.015457 & 0.1312 & 0.448009 \tabularnewline
18 & -0.002686 & -0.0228 & 0.49094 \tabularnewline
19 & 0.030715 & 0.2606 & 0.397562 \tabularnewline
20 & -0.111299 & -0.9444 & 0.174061 \tabularnewline
21 & -0.02262 & -0.1919 & 0.424166 \tabularnewline
22 & 0.047083 & 0.3995 & 0.345348 \tabularnewline
23 & 0.067505 & 0.5728 & 0.284284 \tabularnewline
24 & 0.063707 & 0.5406 & 0.295234 \tabularnewline
25 & -0.125525 & -1.0651 & 0.145192 \tabularnewline
26 & -0.023432 & -0.1988 & 0.42148 \tabularnewline
27 & -0.030723 & -0.2607 & 0.397536 \tabularnewline
28 & 0.022472 & 0.1907 & 0.424657 \tabularnewline
29 & 0.011991 & 0.1017 & 0.459622 \tabularnewline
30 & -0.027008 & -0.2292 & 0.409693 \tabularnewline
31 & -0.00734 & -0.0623 & 0.475257 \tabularnewline
32 & 0.004719 & 0.04 & 0.484086 \tabularnewline
33 & -0.017473 & -0.1483 & 0.441275 \tabularnewline
34 & 0.021414 & 0.1817 & 0.428163 \tabularnewline
35 & 0.062981 & 0.5344 & 0.297352 \tabularnewline
36 & 0.017276 & 0.1466 & 0.441931 \tabularnewline
37 & -0.027115 & -0.2301 & 0.409342 \tabularnewline
38 & 0.042495 & 0.3606 & 0.359734 \tabularnewline
39 & 0.041397 & 0.3513 & 0.363208 \tabularnewline
40 & -0.06986 & -0.5928 & 0.277591 \tabularnewline
41 & -0.176857 & -1.5007 & 0.068906 \tabularnewline
42 & -0.087361 & -0.7413 & 0.230467 \tabularnewline
43 & -0.021387 & -0.1815 & 0.428252 \tabularnewline
44 & 0.027574 & 0.234 & 0.407835 \tabularnewline
45 & 0.077607 & 0.6585 & 0.256154 \tabularnewline
46 & 0.048791 & 0.414 & 0.340051 \tabularnewline
47 & 0.209961 & 1.7816 & 0.039517 \tabularnewline
48 & -0.121212 & -1.0285 & 0.153574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112962&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]0.061219[/C][C]0.5195[/C][C]0.302516[/C][/ROW]
[ROW][C]2[/C][C]-0.113957[/C][C]-0.967[/C][C]0.168402[/C][/ROW]
[ROW][C]3[/C][C]-0.071204[/C][C]-0.6042[/C][C]0.273809[/C][/ROW]
[ROW][C]4[/C][C]-0.126158[/C][C]-1.0705[/C][C]0.143988[/C][/ROW]
[ROW][C]5[/C][C]-0.074745[/C][C]-0.6342[/C][C]0.26397[/C][/ROW]
[ROW][C]6[/C][C]-0.092614[/C][C]-0.7859[/C][C]0.217264[/C][/ROW]
[ROW][C]7[/C][C]-0.018258[/C][C]-0.1549[/C][C]0.438658[/C][/ROW]
[ROW][C]8[/C][C]0.021747[/C][C]0.1845[/C][C]0.427057[/C][/ROW]
[ROW][C]9[/C][C]-0.013309[/C][C]-0.1129[/C][C]0.4552[/C][/ROW]
[ROW][C]10[/C][C]0.019286[/C][C]0.1636[/C][C]0.435233[/C][/ROW]
[ROW][C]11[/C][C]0.021466[/C][C]0.1821[/C][C]0.427989[/C][/ROW]
[ROW][C]12[/C][C]-0.030156[/C][C]-0.2559[/C][C]0.399385[/C][/ROW]
[ROW][C]13[/C][C]0.027896[/C][C]0.2367[/C][C]0.406777[/C][/ROW]
[ROW][C]14[/C][C]-0.023853[/C][C]-0.2024[/C][C]0.420087[/C][/ROW]
[ROW][C]15[/C][C]-0.022452[/C][C]-0.1905[/C][C]0.424723[/C][/ROW]
[ROW][C]16[/C][C]0.083668[/C][C]0.7099[/C][C]0.240015[/C][/ROW]
[ROW][C]17[/C][C]0.015457[/C][C]0.1312[/C][C]0.448009[/C][/ROW]
[ROW][C]18[/C][C]-0.002686[/C][C]-0.0228[/C][C]0.49094[/C][/ROW]
[ROW][C]19[/C][C]0.030715[/C][C]0.2606[/C][C]0.397562[/C][/ROW]
[ROW][C]20[/C][C]-0.111299[/C][C]-0.9444[/C][C]0.174061[/C][/ROW]
[ROW][C]21[/C][C]-0.02262[/C][C]-0.1919[/C][C]0.424166[/C][/ROW]
[ROW][C]22[/C][C]0.047083[/C][C]0.3995[/C][C]0.345348[/C][/ROW]
[ROW][C]23[/C][C]0.067505[/C][C]0.5728[/C][C]0.284284[/C][/ROW]
[ROW][C]24[/C][C]0.063707[/C][C]0.5406[/C][C]0.295234[/C][/ROW]
[ROW][C]25[/C][C]-0.125525[/C][C]-1.0651[/C][C]0.145192[/C][/ROW]
[ROW][C]26[/C][C]-0.023432[/C][C]-0.1988[/C][C]0.42148[/C][/ROW]
[ROW][C]27[/C][C]-0.030723[/C][C]-0.2607[/C][C]0.397536[/C][/ROW]
[ROW][C]28[/C][C]0.022472[/C][C]0.1907[/C][C]0.424657[/C][/ROW]
[ROW][C]29[/C][C]0.011991[/C][C]0.1017[/C][C]0.459622[/C][/ROW]
[ROW][C]30[/C][C]-0.027008[/C][C]-0.2292[/C][C]0.409693[/C][/ROW]
[ROW][C]31[/C][C]-0.00734[/C][C]-0.0623[/C][C]0.475257[/C][/ROW]
[ROW][C]32[/C][C]0.004719[/C][C]0.04[/C][C]0.484086[/C][/ROW]
[ROW][C]33[/C][C]-0.017473[/C][C]-0.1483[/C][C]0.441275[/C][/ROW]
[ROW][C]34[/C][C]0.021414[/C][C]0.1817[/C][C]0.428163[/C][/ROW]
[ROW][C]35[/C][C]0.062981[/C][C]0.5344[/C][C]0.297352[/C][/ROW]
[ROW][C]36[/C][C]0.017276[/C][C]0.1466[/C][C]0.441931[/C][/ROW]
[ROW][C]37[/C][C]-0.027115[/C][C]-0.2301[/C][C]0.409342[/C][/ROW]
[ROW][C]38[/C][C]0.042495[/C][C]0.3606[/C][C]0.359734[/C][/ROW]
[ROW][C]39[/C][C]0.041397[/C][C]0.3513[/C][C]0.363208[/C][/ROW]
[ROW][C]40[/C][C]-0.06986[/C][C]-0.5928[/C][C]0.277591[/C][/ROW]
[ROW][C]41[/C][C]-0.176857[/C][C]-1.5007[/C][C]0.068906[/C][/ROW]
[ROW][C]42[/C][C]-0.087361[/C][C]-0.7413[/C][C]0.230467[/C][/ROW]
[ROW][C]43[/C][C]-0.021387[/C][C]-0.1815[/C][C]0.428252[/C][/ROW]
[ROW][C]44[/C][C]0.027574[/C][C]0.234[/C][C]0.407835[/C][/ROW]
[ROW][C]45[/C][C]0.077607[/C][C]0.6585[/C][C]0.256154[/C][/ROW]
[ROW][C]46[/C][C]0.048791[/C][C]0.414[/C][C]0.340051[/C][/ROW]
[ROW][C]47[/C][C]0.209961[/C][C]1.7816[/C][C]0.039517[/C][/ROW]
[ROW][C]48[/C][C]-0.121212[/C][C]-1.0285[/C][C]0.153574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112962&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112962&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
10.0612190.51950.302516
2-0.113957-0.9670.168402
3-0.071204-0.60420.273809
4-0.126158-1.07050.143988
5-0.074745-0.63420.26397
6-0.092614-0.78590.217264
7-0.018258-0.15490.438658
80.0217470.18450.427057
9-0.013309-0.11290.4552
100.0192860.16360.435233
110.0214660.18210.427989
12-0.030156-0.25590.399385
130.0278960.23670.406777
14-0.023853-0.20240.420087
15-0.022452-0.19050.424723
160.0836680.70990.240015
170.0154570.13120.448009
18-0.002686-0.02280.49094
190.0307150.26060.397562
20-0.111299-0.94440.174061
21-0.02262-0.19190.424166
220.0470830.39950.345348
230.0675050.57280.284284
240.0637070.54060.295234
25-0.125525-1.06510.145192
26-0.023432-0.19880.42148
27-0.030723-0.26070.397536
280.0224720.19070.424657
290.0119910.10170.459622
30-0.027008-0.22920.409693
31-0.00734-0.06230.475257
320.0047190.040.484086
33-0.017473-0.14830.441275
340.0214140.18170.428163
350.0629810.53440.297352
360.0172760.14660.441931
37-0.027115-0.23010.409342
380.0424950.36060.359734
390.0413970.35130.363208
40-0.06986-0.59280.277591
41-0.176857-1.50070.068906
42-0.087361-0.74130.230467
43-0.021387-0.18150.428252
440.0275740.2340.407835
450.0776070.65850.256154
460.0487910.4140.340051
470.2099611.78160.039517
48-0.121212-1.02850.153574







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0612190.51950.302516
2-0.118147-1.00250.159727
3-0.05718-0.48520.314507
4-0.13408-1.13770.129508
5-0.0775-0.65760.256444
6-0.126005-1.06920.144279
7-0.048503-0.41160.340942
8-0.035366-0.30010.382486
9-0.062142-0.52730.299806
10-0.022735-0.19290.423787
11-0.018209-0.15450.438819
12-0.059357-0.50370.30802
130.0126310.10720.457475
14-0.049006-0.41580.339385
15-0.030437-0.25830.398469
160.0692090.58730.279434
17-0.000748-0.00630.497477
180.0015780.01340.494677
190.0411920.34950.363858
20-0.105675-0.89670.186437
210.0004840.00410.498367
220.0449560.38150.351991
230.0644380.54680.293112
240.0525010.44550.328653
25-0.114767-0.97380.166701
26-0.001973-0.01670.493344
27-0.045235-0.38380.351117
280.0488940.41490.339731
29-0.022207-0.18840.425533
30-0.03108-0.26370.396374
31-0.028882-0.24510.40355
32-0.026673-0.22630.410794
33-0.029236-0.24810.402392
340.004820.04090.483744
350.0373880.31720.375986
360.0213550.18120.428357
37-0.028241-0.23960.405648
380.0644660.5470.293031
390.0405550.34410.365879
40-0.072684-0.61670.269676
41-0.154942-1.31470.096388
42-0.080449-0.68260.248516
43-0.049728-0.4220.337156
44-0.002137-0.01810.492791
45-0.023961-0.20330.419732
46-0.033929-0.28790.387127
470.1795951.52390.065955
48-0.163756-1.38950.084479

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.061219 & 0.5195 & 0.302516 \tabularnewline
2 & -0.118147 & -1.0025 & 0.159727 \tabularnewline
3 & -0.05718 & -0.4852 & 0.314507 \tabularnewline
4 & -0.13408 & -1.1377 & 0.129508 \tabularnewline
5 & -0.0775 & -0.6576 & 0.256444 \tabularnewline
6 & -0.126005 & -1.0692 & 0.144279 \tabularnewline
7 & -0.048503 & -0.4116 & 0.340942 \tabularnewline
8 & -0.035366 & -0.3001 & 0.382486 \tabularnewline
9 & -0.062142 & -0.5273 & 0.299806 \tabularnewline
10 & -0.022735 & -0.1929 & 0.423787 \tabularnewline
11 & -0.018209 & -0.1545 & 0.438819 \tabularnewline
12 & -0.059357 & -0.5037 & 0.30802 \tabularnewline
13 & 0.012631 & 0.1072 & 0.457475 \tabularnewline
14 & -0.049006 & -0.4158 & 0.339385 \tabularnewline
15 & -0.030437 & -0.2583 & 0.398469 \tabularnewline
16 & 0.069209 & 0.5873 & 0.279434 \tabularnewline
17 & -0.000748 & -0.0063 & 0.497477 \tabularnewline
18 & 0.001578 & 0.0134 & 0.494677 \tabularnewline
19 & 0.041192 & 0.3495 & 0.363858 \tabularnewline
20 & -0.105675 & -0.8967 & 0.186437 \tabularnewline
21 & 0.000484 & 0.0041 & 0.498367 \tabularnewline
22 & 0.044956 & 0.3815 & 0.351991 \tabularnewline
23 & 0.064438 & 0.5468 & 0.293112 \tabularnewline
24 & 0.052501 & 0.4455 & 0.328653 \tabularnewline
25 & -0.114767 & -0.9738 & 0.166701 \tabularnewline
26 & -0.001973 & -0.0167 & 0.493344 \tabularnewline
27 & -0.045235 & -0.3838 & 0.351117 \tabularnewline
28 & 0.048894 & 0.4149 & 0.339731 \tabularnewline
29 & -0.022207 & -0.1884 & 0.425533 \tabularnewline
30 & -0.03108 & -0.2637 & 0.396374 \tabularnewline
31 & -0.028882 & -0.2451 & 0.40355 \tabularnewline
32 & -0.026673 & -0.2263 & 0.410794 \tabularnewline
33 & -0.029236 & -0.2481 & 0.402392 \tabularnewline
34 & 0.00482 & 0.0409 & 0.483744 \tabularnewline
35 & 0.037388 & 0.3172 & 0.375986 \tabularnewline
36 & 0.021355 & 0.1812 & 0.428357 \tabularnewline
37 & -0.028241 & -0.2396 & 0.405648 \tabularnewline
38 & 0.064466 & 0.547 & 0.293031 \tabularnewline
39 & 0.040555 & 0.3441 & 0.365879 \tabularnewline
40 & -0.072684 & -0.6167 & 0.269676 \tabularnewline
41 & -0.154942 & -1.3147 & 0.096388 \tabularnewline
42 & -0.080449 & -0.6826 & 0.248516 \tabularnewline
43 & -0.049728 & -0.422 & 0.337156 \tabularnewline
44 & -0.002137 & -0.0181 & 0.492791 \tabularnewline
45 & -0.023961 & -0.2033 & 0.419732 \tabularnewline
46 & -0.033929 & -0.2879 & 0.387127 \tabularnewline
47 & 0.179595 & 1.5239 & 0.065955 \tabularnewline
48 & -0.163756 & -1.3895 & 0.084479 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112962&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]0.061219[/C][C]0.5195[/C][C]0.302516[/C][/ROW]
[ROW][C]2[/C][C]-0.118147[/C][C]-1.0025[/C][C]0.159727[/C][/ROW]
[ROW][C]3[/C][C]-0.05718[/C][C]-0.4852[/C][C]0.314507[/C][/ROW]
[ROW][C]4[/C][C]-0.13408[/C][C]-1.1377[/C][C]0.129508[/C][/ROW]
[ROW][C]5[/C][C]-0.0775[/C][C]-0.6576[/C][C]0.256444[/C][/ROW]
[ROW][C]6[/C][C]-0.126005[/C][C]-1.0692[/C][C]0.144279[/C][/ROW]
[ROW][C]7[/C][C]-0.048503[/C][C]-0.4116[/C][C]0.340942[/C][/ROW]
[ROW][C]8[/C][C]-0.035366[/C][C]-0.3001[/C][C]0.382486[/C][/ROW]
[ROW][C]9[/C][C]-0.062142[/C][C]-0.5273[/C][C]0.299806[/C][/ROW]
[ROW][C]10[/C][C]-0.022735[/C][C]-0.1929[/C][C]0.423787[/C][/ROW]
[ROW][C]11[/C][C]-0.018209[/C][C]-0.1545[/C][C]0.438819[/C][/ROW]
[ROW][C]12[/C][C]-0.059357[/C][C]-0.5037[/C][C]0.30802[/C][/ROW]
[ROW][C]13[/C][C]0.012631[/C][C]0.1072[/C][C]0.457475[/C][/ROW]
[ROW][C]14[/C][C]-0.049006[/C][C]-0.4158[/C][C]0.339385[/C][/ROW]
[ROW][C]15[/C][C]-0.030437[/C][C]-0.2583[/C][C]0.398469[/C][/ROW]
[ROW][C]16[/C][C]0.069209[/C][C]0.5873[/C][C]0.279434[/C][/ROW]
[ROW][C]17[/C][C]-0.000748[/C][C]-0.0063[/C][C]0.497477[/C][/ROW]
[ROW][C]18[/C][C]0.001578[/C][C]0.0134[/C][C]0.494677[/C][/ROW]
[ROW][C]19[/C][C]0.041192[/C][C]0.3495[/C][C]0.363858[/C][/ROW]
[ROW][C]20[/C][C]-0.105675[/C][C]-0.8967[/C][C]0.186437[/C][/ROW]
[ROW][C]21[/C][C]0.000484[/C][C]0.0041[/C][C]0.498367[/C][/ROW]
[ROW][C]22[/C][C]0.044956[/C][C]0.3815[/C][C]0.351991[/C][/ROW]
[ROW][C]23[/C][C]0.064438[/C][C]0.5468[/C][C]0.293112[/C][/ROW]
[ROW][C]24[/C][C]0.052501[/C][C]0.4455[/C][C]0.328653[/C][/ROW]
[ROW][C]25[/C][C]-0.114767[/C][C]-0.9738[/C][C]0.166701[/C][/ROW]
[ROW][C]26[/C][C]-0.001973[/C][C]-0.0167[/C][C]0.493344[/C][/ROW]
[ROW][C]27[/C][C]-0.045235[/C][C]-0.3838[/C][C]0.351117[/C][/ROW]
[ROW][C]28[/C][C]0.048894[/C][C]0.4149[/C][C]0.339731[/C][/ROW]
[ROW][C]29[/C][C]-0.022207[/C][C]-0.1884[/C][C]0.425533[/C][/ROW]
[ROW][C]30[/C][C]-0.03108[/C][C]-0.2637[/C][C]0.396374[/C][/ROW]
[ROW][C]31[/C][C]-0.028882[/C][C]-0.2451[/C][C]0.40355[/C][/ROW]
[ROW][C]32[/C][C]-0.026673[/C][C]-0.2263[/C][C]0.410794[/C][/ROW]
[ROW][C]33[/C][C]-0.029236[/C][C]-0.2481[/C][C]0.402392[/C][/ROW]
[ROW][C]34[/C][C]0.00482[/C][C]0.0409[/C][C]0.483744[/C][/ROW]
[ROW][C]35[/C][C]0.037388[/C][C]0.3172[/C][C]0.375986[/C][/ROW]
[ROW][C]36[/C][C]0.021355[/C][C]0.1812[/C][C]0.428357[/C][/ROW]
[ROW][C]37[/C][C]-0.028241[/C][C]-0.2396[/C][C]0.405648[/C][/ROW]
[ROW][C]38[/C][C]0.064466[/C][C]0.547[/C][C]0.293031[/C][/ROW]
[ROW][C]39[/C][C]0.040555[/C][C]0.3441[/C][C]0.365879[/C][/ROW]
[ROW][C]40[/C][C]-0.072684[/C][C]-0.6167[/C][C]0.269676[/C][/ROW]
[ROW][C]41[/C][C]-0.154942[/C][C]-1.3147[/C][C]0.096388[/C][/ROW]
[ROW][C]42[/C][C]-0.080449[/C][C]-0.6826[/C][C]0.248516[/C][/ROW]
[ROW][C]43[/C][C]-0.049728[/C][C]-0.422[/C][C]0.337156[/C][/ROW]
[ROW][C]44[/C][C]-0.002137[/C][C]-0.0181[/C][C]0.492791[/C][/ROW]
[ROW][C]45[/C][C]-0.023961[/C][C]-0.2033[/C][C]0.419732[/C][/ROW]
[ROW][C]46[/C][C]-0.033929[/C][C]-0.2879[/C][C]0.387127[/C][/ROW]
[ROW][C]47[/C][C]0.179595[/C][C]1.5239[/C][C]0.065955[/C][/ROW]
[ROW][C]48[/C][C]-0.163756[/C][C]-1.3895[/C][C]0.084479[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112962&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112962&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
10.0612190.51950.302516
2-0.118147-1.00250.159727
3-0.05718-0.48520.314507
4-0.13408-1.13770.129508
5-0.0775-0.65760.256444
6-0.126005-1.06920.144279
7-0.048503-0.41160.340942
8-0.035366-0.30010.382486
9-0.062142-0.52730.299806
10-0.022735-0.19290.423787
11-0.018209-0.15450.438819
12-0.059357-0.50370.30802
130.0126310.10720.457475
14-0.049006-0.41580.339385
15-0.030437-0.25830.398469
160.0692090.58730.279434
17-0.000748-0.00630.497477
180.0015780.01340.494677
190.0411920.34950.363858
20-0.105675-0.89670.186437
210.0004840.00410.498367
220.0449560.38150.351991
230.0644380.54680.293112
240.0525010.44550.328653
25-0.114767-0.97380.166701
26-0.001973-0.01670.493344
27-0.045235-0.38380.351117
280.0488940.41490.339731
29-0.022207-0.18840.425533
30-0.03108-0.26370.396374
31-0.028882-0.24510.40355
32-0.026673-0.22630.410794
33-0.029236-0.24810.402392
340.004820.04090.483744
350.0373880.31720.375986
360.0213550.18120.428357
37-0.028241-0.23960.405648
380.0644660.5470.293031
390.0405550.34410.365879
40-0.072684-0.61670.269676
41-0.154942-1.31470.096388
42-0.080449-0.68260.248516
43-0.049728-0.4220.337156
44-0.002137-0.01810.492791
45-0.023961-0.20330.419732
46-0.033929-0.28790.387127
470.1795951.52390.065955
48-0.163756-1.38950.084479



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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')