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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 computationTue, 21 Dec 2010 19:52:07 +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/21/t12929610081zldbaonu00cg6g.htm/, Retrieved Thu, 09 May 2024 17:08:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113911, Retrieved Thu, 09 May 2024 17:08:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
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]
-    D    [(Partial) Autocorrelation Function] [W9 ACF origineel] [2010-12-03 11:36:39] [56d90b683fcd93137645f9226b43c62b]
-   P       [(Partial) Autocorrelation Function] [Autocorrelatiefun...] [2010-12-07 20:51:20] [608064602fec1c42028cf50c6f981c88]
-   P         [(Partial) Autocorrelation Function] [AF zonder lags] [2010-12-07 21:06:36] [608064602fec1c42028cf50c6f981c88]
-   PD            [(Partial) Autocorrelation Function] [ACF-48 lags] [2010-12-21 19:52:07] [8bf9de033bd61652831a8b7489bc3566] [Current]
-                   [(Partial) Autocorrelation Function] [ACF-D=1] [2010-12-21 20:02:05] [608064602fec1c42028cf50c6f981c88]
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Dataseries X:
8.1
9.9
11.5
23.4
25.4
27.9
26.1
18.8
14.1
11.5
15.8
12.4
4.5
-2.2
-4.2
-9.4
-14.5
-17.9
-15.1
-15.2
-15.7
-18
-18.1
-13.5
-9.9
-4.8
-1.7
-0.1
2.2
10.2
7.6
10.8
3.8
11
10.8
20.1
14.9
13
10.9
9.6
4
-1.1
-7.7
-8.9
-8
-7.1
-5.3
-2.5
-2.4
-2.9
-4.8
-7.2
1.7
2.2
13.4
12.3
13.7
4.4
-2.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113911&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113911&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113911&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9184157.05450
20.8072546.20060
30.6491714.98643e-06
40.5123273.93530.000111
50.3628632.78720.003571
60.2125921.63290.053903
70.0558370.42890.334782
8-0.097922-0.75210.227476
9-0.24951-1.91650.030073
10-0.386274-2.9670.002169
11-0.50757-3.89870.000125
12-0.592977-4.55471.3e-05
13-0.628616-4.82855e-06
14-0.622069-4.77826e-06
15-0.57851-4.44362e-05
16-0.527219-4.04967.6e-05
17-0.447738-3.43910.000538
18-0.358787-2.75590.003887
19-0.245076-1.88250.032354
20-0.150699-1.15750.125858
21-0.05048-0.38770.349801
220.0244770.1880.425756
230.1270230.97570.166604
240.2112951.6230.054962
250.2840952.18220.016545
260.3150482.41990.009311
270.3203882.46090.008401
280.318822.44890.00866
290.3007652.31020.012196
300.2689942.06620.021605
310.2118231.6270.054529
320.1495011.14830.127732
330.0874940.67210.252086
340.0299850.23030.409319
35-0.030852-0.2370.406749
36-0.092839-0.71310.239293
37-0.15334-1.17780.121798
38-0.194812-1.49640.069943
39-0.216284-1.66130.050978
40-0.207374-1.59290.058267
41-0.178402-1.37030.087887
42-0.142131-1.09170.139696
43-0.108536-0.83370.203911
44-0.077053-0.59190.278103
45-0.058538-0.44960.327309
46-0.041861-0.32150.374469
47-0.023534-0.18080.428585
480.0103560.07950.468435

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.918415 & 7.0545 & 0 \tabularnewline
2 & 0.807254 & 6.2006 & 0 \tabularnewline
3 & 0.649171 & 4.9864 & 3e-06 \tabularnewline
4 & 0.512327 & 3.9353 & 0.000111 \tabularnewline
5 & 0.362863 & 2.7872 & 0.003571 \tabularnewline
6 & 0.212592 & 1.6329 & 0.053903 \tabularnewline
7 & 0.055837 & 0.4289 & 0.334782 \tabularnewline
8 & -0.097922 & -0.7521 & 0.227476 \tabularnewline
9 & -0.24951 & -1.9165 & 0.030073 \tabularnewline
10 & -0.386274 & -2.967 & 0.002169 \tabularnewline
11 & -0.50757 & -3.8987 & 0.000125 \tabularnewline
12 & -0.592977 & -4.5547 & 1.3e-05 \tabularnewline
13 & -0.628616 & -4.8285 & 5e-06 \tabularnewline
14 & -0.622069 & -4.7782 & 6e-06 \tabularnewline
15 & -0.57851 & -4.4436 & 2e-05 \tabularnewline
16 & -0.527219 & -4.0496 & 7.6e-05 \tabularnewline
17 & -0.447738 & -3.4391 & 0.000538 \tabularnewline
18 & -0.358787 & -2.7559 & 0.003887 \tabularnewline
19 & -0.245076 & -1.8825 & 0.032354 \tabularnewline
20 & -0.150699 & -1.1575 & 0.125858 \tabularnewline
21 & -0.05048 & -0.3877 & 0.349801 \tabularnewline
22 & 0.024477 & 0.188 & 0.425756 \tabularnewline
23 & 0.127023 & 0.9757 & 0.166604 \tabularnewline
24 & 0.211295 & 1.623 & 0.054962 \tabularnewline
25 & 0.284095 & 2.1822 & 0.016545 \tabularnewline
26 & 0.315048 & 2.4199 & 0.009311 \tabularnewline
27 & 0.320388 & 2.4609 & 0.008401 \tabularnewline
28 & 0.31882 & 2.4489 & 0.00866 \tabularnewline
29 & 0.300765 & 2.3102 & 0.012196 \tabularnewline
30 & 0.268994 & 2.0662 & 0.021605 \tabularnewline
31 & 0.211823 & 1.627 & 0.054529 \tabularnewline
32 & 0.149501 & 1.1483 & 0.127732 \tabularnewline
33 & 0.087494 & 0.6721 & 0.252086 \tabularnewline
34 & 0.029985 & 0.2303 & 0.409319 \tabularnewline
35 & -0.030852 & -0.237 & 0.406749 \tabularnewline
36 & -0.092839 & -0.7131 & 0.239293 \tabularnewline
37 & -0.15334 & -1.1778 & 0.121798 \tabularnewline
38 & -0.194812 & -1.4964 & 0.069943 \tabularnewline
39 & -0.216284 & -1.6613 & 0.050978 \tabularnewline
40 & -0.207374 & -1.5929 & 0.058267 \tabularnewline
41 & -0.178402 & -1.3703 & 0.087887 \tabularnewline
42 & -0.142131 & -1.0917 & 0.139696 \tabularnewline
43 & -0.108536 & -0.8337 & 0.203911 \tabularnewline
44 & -0.077053 & -0.5919 & 0.278103 \tabularnewline
45 & -0.058538 & -0.4496 & 0.327309 \tabularnewline
46 & -0.041861 & -0.3215 & 0.374469 \tabularnewline
47 & -0.023534 & -0.1808 & 0.428585 \tabularnewline
48 & 0.010356 & 0.0795 & 0.468435 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113911&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]0.918415[/C][C]7.0545[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.807254[/C][C]6.2006[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.649171[/C][C]4.9864[/C][C]3e-06[/C][/ROW]
[ROW][C]4[/C][C]0.512327[/C][C]3.9353[/C][C]0.000111[/C][/ROW]
[ROW][C]5[/C][C]0.362863[/C][C]2.7872[/C][C]0.003571[/C][/ROW]
[ROW][C]6[/C][C]0.212592[/C][C]1.6329[/C][C]0.053903[/C][/ROW]
[ROW][C]7[/C][C]0.055837[/C][C]0.4289[/C][C]0.334782[/C][/ROW]
[ROW][C]8[/C][C]-0.097922[/C][C]-0.7521[/C][C]0.227476[/C][/ROW]
[ROW][C]9[/C][C]-0.24951[/C][C]-1.9165[/C][C]0.030073[/C][/ROW]
[ROW][C]10[/C][C]-0.386274[/C][C]-2.967[/C][C]0.002169[/C][/ROW]
[ROW][C]11[/C][C]-0.50757[/C][C]-3.8987[/C][C]0.000125[/C][/ROW]
[ROW][C]12[/C][C]-0.592977[/C][C]-4.5547[/C][C]1.3e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.628616[/C][C]-4.8285[/C][C]5e-06[/C][/ROW]
[ROW][C]14[/C][C]-0.622069[/C][C]-4.7782[/C][C]6e-06[/C][/ROW]
[ROW][C]15[/C][C]-0.57851[/C][C]-4.4436[/C][C]2e-05[/C][/ROW]
[ROW][C]16[/C][C]-0.527219[/C][C]-4.0496[/C][C]7.6e-05[/C][/ROW]
[ROW][C]17[/C][C]-0.447738[/C][C]-3.4391[/C][C]0.000538[/C][/ROW]
[ROW][C]18[/C][C]-0.358787[/C][C]-2.7559[/C][C]0.003887[/C][/ROW]
[ROW][C]19[/C][C]-0.245076[/C][C]-1.8825[/C][C]0.032354[/C][/ROW]
[ROW][C]20[/C][C]-0.150699[/C][C]-1.1575[/C][C]0.125858[/C][/ROW]
[ROW][C]21[/C][C]-0.05048[/C][C]-0.3877[/C][C]0.349801[/C][/ROW]
[ROW][C]22[/C][C]0.024477[/C][C]0.188[/C][C]0.425756[/C][/ROW]
[ROW][C]23[/C][C]0.127023[/C][C]0.9757[/C][C]0.166604[/C][/ROW]
[ROW][C]24[/C][C]0.211295[/C][C]1.623[/C][C]0.054962[/C][/ROW]
[ROW][C]25[/C][C]0.284095[/C][C]2.1822[/C][C]0.016545[/C][/ROW]
[ROW][C]26[/C][C]0.315048[/C][C]2.4199[/C][C]0.009311[/C][/ROW]
[ROW][C]27[/C][C]0.320388[/C][C]2.4609[/C][C]0.008401[/C][/ROW]
[ROW][C]28[/C][C]0.31882[/C][C]2.4489[/C][C]0.00866[/C][/ROW]
[ROW][C]29[/C][C]0.300765[/C][C]2.3102[/C][C]0.012196[/C][/ROW]
[ROW][C]30[/C][C]0.268994[/C][C]2.0662[/C][C]0.021605[/C][/ROW]
[ROW][C]31[/C][C]0.211823[/C][C]1.627[/C][C]0.054529[/C][/ROW]
[ROW][C]32[/C][C]0.149501[/C][C]1.1483[/C][C]0.127732[/C][/ROW]
[ROW][C]33[/C][C]0.087494[/C][C]0.6721[/C][C]0.252086[/C][/ROW]
[ROW][C]34[/C][C]0.029985[/C][C]0.2303[/C][C]0.409319[/C][/ROW]
[ROW][C]35[/C][C]-0.030852[/C][C]-0.237[/C][C]0.406749[/C][/ROW]
[ROW][C]36[/C][C]-0.092839[/C][C]-0.7131[/C][C]0.239293[/C][/ROW]
[ROW][C]37[/C][C]-0.15334[/C][C]-1.1778[/C][C]0.121798[/C][/ROW]
[ROW][C]38[/C][C]-0.194812[/C][C]-1.4964[/C][C]0.069943[/C][/ROW]
[ROW][C]39[/C][C]-0.216284[/C][C]-1.6613[/C][C]0.050978[/C][/ROW]
[ROW][C]40[/C][C]-0.207374[/C][C]-1.5929[/C][C]0.058267[/C][/ROW]
[ROW][C]41[/C][C]-0.178402[/C][C]-1.3703[/C][C]0.087887[/C][/ROW]
[ROW][C]42[/C][C]-0.142131[/C][C]-1.0917[/C][C]0.139696[/C][/ROW]
[ROW][C]43[/C][C]-0.108536[/C][C]-0.8337[/C][C]0.203911[/C][/ROW]
[ROW][C]44[/C][C]-0.077053[/C][C]-0.5919[/C][C]0.278103[/C][/ROW]
[ROW][C]45[/C][C]-0.058538[/C][C]-0.4496[/C][C]0.327309[/C][/ROW]
[ROW][C]46[/C][C]-0.041861[/C][C]-0.3215[/C][C]0.374469[/C][/ROW]
[ROW][C]47[/C][C]-0.023534[/C][C]-0.1808[/C][C]0.428585[/C][/ROW]
[ROW][C]48[/C][C]0.010356[/C][C]0.0795[/C][C]0.468435[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113911&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113911&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
10.9184157.05450
20.8072546.20060
30.6491714.98643e-06
40.5123273.93530.000111
50.3628632.78720.003571
60.2125921.63290.053903
70.0558370.42890.334782
8-0.097922-0.75210.227476
9-0.24951-1.91650.030073
10-0.386274-2.9670.002169
11-0.50757-3.89870.000125
12-0.592977-4.55471.3e-05
13-0.628616-4.82855e-06
14-0.622069-4.77826e-06
15-0.57851-4.44362e-05
16-0.527219-4.04967.6e-05
17-0.447738-3.43910.000538
18-0.358787-2.75590.003887
19-0.245076-1.88250.032354
20-0.150699-1.15750.125858
21-0.05048-0.38770.349801
220.0244770.1880.425756
230.1270230.97570.166604
240.2112951.6230.054962
250.2840952.18220.016545
260.3150482.41990.009311
270.3203882.46090.008401
280.318822.44890.00866
290.3007652.31020.012196
300.2689942.06620.021605
310.2118231.6270.054529
320.1495011.14830.127732
330.0874940.67210.252086
340.0299850.23030.409319
35-0.030852-0.2370.406749
36-0.092839-0.71310.239293
37-0.15334-1.17780.121798
38-0.194812-1.49640.069943
39-0.216284-1.66130.050978
40-0.207374-1.59290.058267
41-0.178402-1.37030.087887
42-0.142131-1.09170.139696
43-0.108536-0.83370.203911
44-0.077053-0.59190.278103
45-0.058538-0.44960.327309
46-0.041861-0.32150.374469
47-0.023534-0.18080.428585
480.0103560.07950.468435







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9184157.05450
2-0.23149-1.77810.040269
3-0.345945-2.65730.00506
40.1443911.10910.135946
5-0.162494-1.24810.108455
6-0.217728-1.67240.04987
7-0.076574-0.58820.279328
8-0.129652-0.99590.161689
9-0.188249-1.4460.076739
10-0.091299-0.70130.242941
11-0.11817-0.90770.18387
12-0.023307-0.1790.429266
130.1370181.05250.14844
140.0012920.00990.496056
150.0171040.13140.447963
16-0.081174-0.62350.267678
170.0819660.62960.265696
18-0.001066-0.00820.496747
190.0123150.09460.46248
20-0.202494-1.55540.062601
210.002060.01580.493715
22-0.113694-0.87330.193019
230.1889011.4510.076041
24-0.01506-0.11570.454149
25-0.122298-0.93940.17568
26-0.022172-0.17030.432675
27-0.034267-0.26320.396653
280.1234310.94810.173475
29-0.063557-0.48820.313613
30-0.066321-0.50940.306179
31-0.086135-0.66160.255396
320.0056890.04370.482645
330.0085750.06590.473852
34-0.03695-0.28380.38877
350.0023980.01840.492684
36-0.070748-0.54340.294441
370.00240.01840.492677
38-0.052782-0.40540.343314
390.1137430.87370.192918
400.1196210.91880.180964
410.1514641.16340.124673
42-0.176106-1.35270.090657
43-0.122427-0.94040.175429
44-0.033745-0.25920.398191
45-0.056844-0.43660.331987
460.0050350.03870.484639
47-0.085299-0.65520.257444
480.0142790.10970.456518

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.918415 & 7.0545 & 0 \tabularnewline
2 & -0.23149 & -1.7781 & 0.040269 \tabularnewline
3 & -0.345945 & -2.6573 & 0.00506 \tabularnewline
4 & 0.144391 & 1.1091 & 0.135946 \tabularnewline
5 & -0.162494 & -1.2481 & 0.108455 \tabularnewline
6 & -0.217728 & -1.6724 & 0.04987 \tabularnewline
7 & -0.076574 & -0.5882 & 0.279328 \tabularnewline
8 & -0.129652 & -0.9959 & 0.161689 \tabularnewline
9 & -0.188249 & -1.446 & 0.076739 \tabularnewline
10 & -0.091299 & -0.7013 & 0.242941 \tabularnewline
11 & -0.11817 & -0.9077 & 0.18387 \tabularnewline
12 & -0.023307 & -0.179 & 0.429266 \tabularnewline
13 & 0.137018 & 1.0525 & 0.14844 \tabularnewline
14 & 0.001292 & 0.0099 & 0.496056 \tabularnewline
15 & 0.017104 & 0.1314 & 0.447963 \tabularnewline
16 & -0.081174 & -0.6235 & 0.267678 \tabularnewline
17 & 0.081966 & 0.6296 & 0.265696 \tabularnewline
18 & -0.001066 & -0.0082 & 0.496747 \tabularnewline
19 & 0.012315 & 0.0946 & 0.46248 \tabularnewline
20 & -0.202494 & -1.5554 & 0.062601 \tabularnewline
21 & 0.00206 & 0.0158 & 0.493715 \tabularnewline
22 & -0.113694 & -0.8733 & 0.193019 \tabularnewline
23 & 0.188901 & 1.451 & 0.076041 \tabularnewline
24 & -0.01506 & -0.1157 & 0.454149 \tabularnewline
25 & -0.122298 & -0.9394 & 0.17568 \tabularnewline
26 & -0.022172 & -0.1703 & 0.432675 \tabularnewline
27 & -0.034267 & -0.2632 & 0.396653 \tabularnewline
28 & 0.123431 & 0.9481 & 0.173475 \tabularnewline
29 & -0.063557 & -0.4882 & 0.313613 \tabularnewline
30 & -0.066321 & -0.5094 & 0.306179 \tabularnewline
31 & -0.086135 & -0.6616 & 0.255396 \tabularnewline
32 & 0.005689 & 0.0437 & 0.482645 \tabularnewline
33 & 0.008575 & 0.0659 & 0.473852 \tabularnewline
34 & -0.03695 & -0.2838 & 0.38877 \tabularnewline
35 & 0.002398 & 0.0184 & 0.492684 \tabularnewline
36 & -0.070748 & -0.5434 & 0.294441 \tabularnewline
37 & 0.0024 & 0.0184 & 0.492677 \tabularnewline
38 & -0.052782 & -0.4054 & 0.343314 \tabularnewline
39 & 0.113743 & 0.8737 & 0.192918 \tabularnewline
40 & 0.119621 & 0.9188 & 0.180964 \tabularnewline
41 & 0.151464 & 1.1634 & 0.124673 \tabularnewline
42 & -0.176106 & -1.3527 & 0.090657 \tabularnewline
43 & -0.122427 & -0.9404 & 0.175429 \tabularnewline
44 & -0.033745 & -0.2592 & 0.398191 \tabularnewline
45 & -0.056844 & -0.4366 & 0.331987 \tabularnewline
46 & 0.005035 & 0.0387 & 0.484639 \tabularnewline
47 & -0.085299 & -0.6552 & 0.257444 \tabularnewline
48 & 0.014279 & 0.1097 & 0.456518 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113911&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]0.918415[/C][C]7.0545[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.23149[/C][C]-1.7781[/C][C]0.040269[/C][/ROW]
[ROW][C]3[/C][C]-0.345945[/C][C]-2.6573[/C][C]0.00506[/C][/ROW]
[ROW][C]4[/C][C]0.144391[/C][C]1.1091[/C][C]0.135946[/C][/ROW]
[ROW][C]5[/C][C]-0.162494[/C][C]-1.2481[/C][C]0.108455[/C][/ROW]
[ROW][C]6[/C][C]-0.217728[/C][C]-1.6724[/C][C]0.04987[/C][/ROW]
[ROW][C]7[/C][C]-0.076574[/C][C]-0.5882[/C][C]0.279328[/C][/ROW]
[ROW][C]8[/C][C]-0.129652[/C][C]-0.9959[/C][C]0.161689[/C][/ROW]
[ROW][C]9[/C][C]-0.188249[/C][C]-1.446[/C][C]0.076739[/C][/ROW]
[ROW][C]10[/C][C]-0.091299[/C][C]-0.7013[/C][C]0.242941[/C][/ROW]
[ROW][C]11[/C][C]-0.11817[/C][C]-0.9077[/C][C]0.18387[/C][/ROW]
[ROW][C]12[/C][C]-0.023307[/C][C]-0.179[/C][C]0.429266[/C][/ROW]
[ROW][C]13[/C][C]0.137018[/C][C]1.0525[/C][C]0.14844[/C][/ROW]
[ROW][C]14[/C][C]0.001292[/C][C]0.0099[/C][C]0.496056[/C][/ROW]
[ROW][C]15[/C][C]0.017104[/C][C]0.1314[/C][C]0.447963[/C][/ROW]
[ROW][C]16[/C][C]-0.081174[/C][C]-0.6235[/C][C]0.267678[/C][/ROW]
[ROW][C]17[/C][C]0.081966[/C][C]0.6296[/C][C]0.265696[/C][/ROW]
[ROW][C]18[/C][C]-0.001066[/C][C]-0.0082[/C][C]0.496747[/C][/ROW]
[ROW][C]19[/C][C]0.012315[/C][C]0.0946[/C][C]0.46248[/C][/ROW]
[ROW][C]20[/C][C]-0.202494[/C][C]-1.5554[/C][C]0.062601[/C][/ROW]
[ROW][C]21[/C][C]0.00206[/C][C]0.0158[/C][C]0.493715[/C][/ROW]
[ROW][C]22[/C][C]-0.113694[/C][C]-0.8733[/C][C]0.193019[/C][/ROW]
[ROW][C]23[/C][C]0.188901[/C][C]1.451[/C][C]0.076041[/C][/ROW]
[ROW][C]24[/C][C]-0.01506[/C][C]-0.1157[/C][C]0.454149[/C][/ROW]
[ROW][C]25[/C][C]-0.122298[/C][C]-0.9394[/C][C]0.17568[/C][/ROW]
[ROW][C]26[/C][C]-0.022172[/C][C]-0.1703[/C][C]0.432675[/C][/ROW]
[ROW][C]27[/C][C]-0.034267[/C][C]-0.2632[/C][C]0.396653[/C][/ROW]
[ROW][C]28[/C][C]0.123431[/C][C]0.9481[/C][C]0.173475[/C][/ROW]
[ROW][C]29[/C][C]-0.063557[/C][C]-0.4882[/C][C]0.313613[/C][/ROW]
[ROW][C]30[/C][C]-0.066321[/C][C]-0.5094[/C][C]0.306179[/C][/ROW]
[ROW][C]31[/C][C]-0.086135[/C][C]-0.6616[/C][C]0.255396[/C][/ROW]
[ROW][C]32[/C][C]0.005689[/C][C]0.0437[/C][C]0.482645[/C][/ROW]
[ROW][C]33[/C][C]0.008575[/C][C]0.0659[/C][C]0.473852[/C][/ROW]
[ROW][C]34[/C][C]-0.03695[/C][C]-0.2838[/C][C]0.38877[/C][/ROW]
[ROW][C]35[/C][C]0.002398[/C][C]0.0184[/C][C]0.492684[/C][/ROW]
[ROW][C]36[/C][C]-0.070748[/C][C]-0.5434[/C][C]0.294441[/C][/ROW]
[ROW][C]37[/C][C]0.0024[/C][C]0.0184[/C][C]0.492677[/C][/ROW]
[ROW][C]38[/C][C]-0.052782[/C][C]-0.4054[/C][C]0.343314[/C][/ROW]
[ROW][C]39[/C][C]0.113743[/C][C]0.8737[/C][C]0.192918[/C][/ROW]
[ROW][C]40[/C][C]0.119621[/C][C]0.9188[/C][C]0.180964[/C][/ROW]
[ROW][C]41[/C][C]0.151464[/C][C]1.1634[/C][C]0.124673[/C][/ROW]
[ROW][C]42[/C][C]-0.176106[/C][C]-1.3527[/C][C]0.090657[/C][/ROW]
[ROW][C]43[/C][C]-0.122427[/C][C]-0.9404[/C][C]0.175429[/C][/ROW]
[ROW][C]44[/C][C]-0.033745[/C][C]-0.2592[/C][C]0.398191[/C][/ROW]
[ROW][C]45[/C][C]-0.056844[/C][C]-0.4366[/C][C]0.331987[/C][/ROW]
[ROW][C]46[/C][C]0.005035[/C][C]0.0387[/C][C]0.484639[/C][/ROW]
[ROW][C]47[/C][C]-0.085299[/C][C]-0.6552[/C][C]0.257444[/C][/ROW]
[ROW][C]48[/C][C]0.014279[/C][C]0.1097[/C][C]0.456518[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113911&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113911&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
10.9184157.05450
2-0.23149-1.77810.040269
3-0.345945-2.65730.00506
40.1443911.10910.135946
5-0.162494-1.24810.108455
6-0.217728-1.67240.04987
7-0.076574-0.58820.279328
8-0.129652-0.99590.161689
9-0.188249-1.4460.076739
10-0.091299-0.70130.242941
11-0.11817-0.90770.18387
12-0.023307-0.1790.429266
130.1370181.05250.14844
140.0012920.00990.496056
150.0171040.13140.447963
16-0.081174-0.62350.267678
170.0819660.62960.265696
18-0.001066-0.00820.496747
190.0123150.09460.46248
20-0.202494-1.55540.062601
210.002060.01580.493715
22-0.113694-0.87330.193019
230.1889011.4510.076041
24-0.01506-0.11570.454149
25-0.122298-0.93940.17568
26-0.022172-0.17030.432675
27-0.034267-0.26320.396653
280.1234310.94810.173475
29-0.063557-0.48820.313613
30-0.066321-0.50940.306179
31-0.086135-0.66160.255396
320.0056890.04370.482645
330.0085750.06590.473852
34-0.03695-0.28380.38877
350.0023980.01840.492684
36-0.070748-0.54340.294441
370.00240.01840.492677
38-0.052782-0.40540.343314
390.1137430.87370.192918
400.1196210.91880.180964
410.1514641.16340.124673
42-0.176106-1.35270.090657
43-0.122427-0.94040.175429
44-0.033745-0.25920.398191
45-0.056844-0.43660.331987
460.0050350.03870.484639
47-0.085299-0.65520.257444
480.0142790.10970.456518



Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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')