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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 computationFri, 24 Dec 2010 10:17:12 +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/24/t1293185716xqomj392j89jxnz.htm/, Retrieved Tue, 30 Apr 2024 07:58:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114700, Retrieved Tue, 30 Apr 2024 07:58:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-    D                [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-17 16:51:16] [7773f496f69461f4a67891f0ef752622]
-   PD                  [(Partial) Autocorrelation Function] [ACFKoffie] [2010-12-20 13:05:39] [3fb95cad3bbcce10c72dbbcc5bec5662]
-   PD                      [(Partial) Autocorrelation Function] [ACFKoffie2] [2010-12-24 10:17:12] [9be3691a9b6ce074cb51fd18377fce28] [Current]
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Dataseries X:
7,14
7,24
7,33
7,61
7,66
7,69
7,7
7,68
7,71
7,71
7,72
7,68
7,72
7,74
7,76
7,9
7,97
7,96
7,95
7,97
7,93
7,99
7,96
7,92
7,97
7,98
8
8,04
8,17
8,29
8,26
8,3
8,32
8,28
8,27
8,32
8,31
8,34
8,32
8,36
8,33
8,35
8,34
8,37
8,31
8,33
8,34
8,25
8,27
8,31
8,25
8,3
8,3
8,35
8,78
8,9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114700&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114700&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114700&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.851676.37330
20.7128055.33411e-06
30.6325314.73348e-06
40.5887664.40592.4e-05
50.5546424.15065.7e-05
60.5303913.96910.000104
70.4970383.71950.000232
80.470093.51780.000436
90.4512353.37670.00067
100.4185673.13230.001379
110.3886082.90810.002602
120.3504342.62240.005612
130.3015472.25660.013978
140.2493021.86560.033669
150.1926751.44180.077457
160.1566551.17230.123021
170.1249020.93470.176982
180.0958130.7170.238177
190.0633010.47370.318778
200.0367090.27470.392278
210.0018780.01410.49442
22-0.016416-0.12280.451336
23-0.042814-0.32040.374931
24-0.085254-0.6380.263042
25-0.123088-0.92110.180473
26-0.169992-1.27210.104296
27-0.234951-1.75820.042088
28-0.288959-2.16240.017438
29-0.312776-2.34060.01142
30-0.315582-2.36160.01085
31-0.323533-2.42110.00937
32-0.32152-2.4060.009726
33-0.3073-2.29960.01261
34-0.308426-2.3080.012357
35-0.314945-2.35680.010977
36-0.30601-2.290.012906
37-0.30624-2.29170.012853
38-0.2988-2.2360.014677
39-0.301421-2.25560.01401
40-0.309959-2.31950.012019
41-0.3188-2.38570.010227
42-0.306963-2.29710.012687
43-0.296419-2.21820.015307
44-0.277025-2.07310.02139
45-0.25751-1.9270.029528
46-0.240601-1.80050.038585
47-0.223207-1.67030.050217
48-0.21632-1.61880.055556

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.85167 & 6.3733 & 0 \tabularnewline
2 & 0.712805 & 5.3341 & 1e-06 \tabularnewline
3 & 0.632531 & 4.7334 & 8e-06 \tabularnewline
4 & 0.588766 & 4.4059 & 2.4e-05 \tabularnewline
5 & 0.554642 & 4.1506 & 5.7e-05 \tabularnewline
6 & 0.530391 & 3.9691 & 0.000104 \tabularnewline
7 & 0.497038 & 3.7195 & 0.000232 \tabularnewline
8 & 0.47009 & 3.5178 & 0.000436 \tabularnewline
9 & 0.451235 & 3.3767 & 0.00067 \tabularnewline
10 & 0.418567 & 3.1323 & 0.001379 \tabularnewline
11 & 0.388608 & 2.9081 & 0.002602 \tabularnewline
12 & 0.350434 & 2.6224 & 0.005612 \tabularnewline
13 & 0.301547 & 2.2566 & 0.013978 \tabularnewline
14 & 0.249302 & 1.8656 & 0.033669 \tabularnewline
15 & 0.192675 & 1.4418 & 0.077457 \tabularnewline
16 & 0.156655 & 1.1723 & 0.123021 \tabularnewline
17 & 0.124902 & 0.9347 & 0.176982 \tabularnewline
18 & 0.095813 & 0.717 & 0.238177 \tabularnewline
19 & 0.063301 & 0.4737 & 0.318778 \tabularnewline
20 & 0.036709 & 0.2747 & 0.392278 \tabularnewline
21 & 0.001878 & 0.0141 & 0.49442 \tabularnewline
22 & -0.016416 & -0.1228 & 0.451336 \tabularnewline
23 & -0.042814 & -0.3204 & 0.374931 \tabularnewline
24 & -0.085254 & -0.638 & 0.263042 \tabularnewline
25 & -0.123088 & -0.9211 & 0.180473 \tabularnewline
26 & -0.169992 & -1.2721 & 0.104296 \tabularnewline
27 & -0.234951 & -1.7582 & 0.042088 \tabularnewline
28 & -0.288959 & -2.1624 & 0.017438 \tabularnewline
29 & -0.312776 & -2.3406 & 0.01142 \tabularnewline
30 & -0.315582 & -2.3616 & 0.01085 \tabularnewline
31 & -0.323533 & -2.4211 & 0.00937 \tabularnewline
32 & -0.32152 & -2.406 & 0.009726 \tabularnewline
33 & -0.3073 & -2.2996 & 0.01261 \tabularnewline
34 & -0.308426 & -2.308 & 0.012357 \tabularnewline
35 & -0.314945 & -2.3568 & 0.010977 \tabularnewline
36 & -0.30601 & -2.29 & 0.012906 \tabularnewline
37 & -0.30624 & -2.2917 & 0.012853 \tabularnewline
38 & -0.2988 & -2.236 & 0.014677 \tabularnewline
39 & -0.301421 & -2.2556 & 0.01401 \tabularnewline
40 & -0.309959 & -2.3195 & 0.012019 \tabularnewline
41 & -0.3188 & -2.3857 & 0.010227 \tabularnewline
42 & -0.306963 & -2.2971 & 0.012687 \tabularnewline
43 & -0.296419 & -2.2182 & 0.015307 \tabularnewline
44 & -0.277025 & -2.0731 & 0.02139 \tabularnewline
45 & -0.25751 & -1.927 & 0.029528 \tabularnewline
46 & -0.240601 & -1.8005 & 0.038585 \tabularnewline
47 & -0.223207 & -1.6703 & 0.050217 \tabularnewline
48 & -0.21632 & -1.6188 & 0.055556 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114700&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]0.85167[/C][C]6.3733[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.712805[/C][C]5.3341[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.632531[/C][C]4.7334[/C][C]8e-06[/C][/ROW]
[ROW][C]4[/C][C]0.588766[/C][C]4.4059[/C][C]2.4e-05[/C][/ROW]
[ROW][C]5[/C][C]0.554642[/C][C]4.1506[/C][C]5.7e-05[/C][/ROW]
[ROW][C]6[/C][C]0.530391[/C][C]3.9691[/C][C]0.000104[/C][/ROW]
[ROW][C]7[/C][C]0.497038[/C][C]3.7195[/C][C]0.000232[/C][/ROW]
[ROW][C]8[/C][C]0.47009[/C][C]3.5178[/C][C]0.000436[/C][/ROW]
[ROW][C]9[/C][C]0.451235[/C][C]3.3767[/C][C]0.00067[/C][/ROW]
[ROW][C]10[/C][C]0.418567[/C][C]3.1323[/C][C]0.001379[/C][/ROW]
[ROW][C]11[/C][C]0.388608[/C][C]2.9081[/C][C]0.002602[/C][/ROW]
[ROW][C]12[/C][C]0.350434[/C][C]2.6224[/C][C]0.005612[/C][/ROW]
[ROW][C]13[/C][C]0.301547[/C][C]2.2566[/C][C]0.013978[/C][/ROW]
[ROW][C]14[/C][C]0.249302[/C][C]1.8656[/C][C]0.033669[/C][/ROW]
[ROW][C]15[/C][C]0.192675[/C][C]1.4418[/C][C]0.077457[/C][/ROW]
[ROW][C]16[/C][C]0.156655[/C][C]1.1723[/C][C]0.123021[/C][/ROW]
[ROW][C]17[/C][C]0.124902[/C][C]0.9347[/C][C]0.176982[/C][/ROW]
[ROW][C]18[/C][C]0.095813[/C][C]0.717[/C][C]0.238177[/C][/ROW]
[ROW][C]19[/C][C]0.063301[/C][C]0.4737[/C][C]0.318778[/C][/ROW]
[ROW][C]20[/C][C]0.036709[/C][C]0.2747[/C][C]0.392278[/C][/ROW]
[ROW][C]21[/C][C]0.001878[/C][C]0.0141[/C][C]0.49442[/C][/ROW]
[ROW][C]22[/C][C]-0.016416[/C][C]-0.1228[/C][C]0.451336[/C][/ROW]
[ROW][C]23[/C][C]-0.042814[/C][C]-0.3204[/C][C]0.374931[/C][/ROW]
[ROW][C]24[/C][C]-0.085254[/C][C]-0.638[/C][C]0.263042[/C][/ROW]
[ROW][C]25[/C][C]-0.123088[/C][C]-0.9211[/C][C]0.180473[/C][/ROW]
[ROW][C]26[/C][C]-0.169992[/C][C]-1.2721[/C][C]0.104296[/C][/ROW]
[ROW][C]27[/C][C]-0.234951[/C][C]-1.7582[/C][C]0.042088[/C][/ROW]
[ROW][C]28[/C][C]-0.288959[/C][C]-2.1624[/C][C]0.017438[/C][/ROW]
[ROW][C]29[/C][C]-0.312776[/C][C]-2.3406[/C][C]0.01142[/C][/ROW]
[ROW][C]30[/C][C]-0.315582[/C][C]-2.3616[/C][C]0.01085[/C][/ROW]
[ROW][C]31[/C][C]-0.323533[/C][C]-2.4211[/C][C]0.00937[/C][/ROW]
[ROW][C]32[/C][C]-0.32152[/C][C]-2.406[/C][C]0.009726[/C][/ROW]
[ROW][C]33[/C][C]-0.3073[/C][C]-2.2996[/C][C]0.01261[/C][/ROW]
[ROW][C]34[/C][C]-0.308426[/C][C]-2.308[/C][C]0.012357[/C][/ROW]
[ROW][C]35[/C][C]-0.314945[/C][C]-2.3568[/C][C]0.010977[/C][/ROW]
[ROW][C]36[/C][C]-0.30601[/C][C]-2.29[/C][C]0.012906[/C][/ROW]
[ROW][C]37[/C][C]-0.30624[/C][C]-2.2917[/C][C]0.012853[/C][/ROW]
[ROW][C]38[/C][C]-0.2988[/C][C]-2.236[/C][C]0.014677[/C][/ROW]
[ROW][C]39[/C][C]-0.301421[/C][C]-2.2556[/C][C]0.01401[/C][/ROW]
[ROW][C]40[/C][C]-0.309959[/C][C]-2.3195[/C][C]0.012019[/C][/ROW]
[ROW][C]41[/C][C]-0.3188[/C][C]-2.3857[/C][C]0.010227[/C][/ROW]
[ROW][C]42[/C][C]-0.306963[/C][C]-2.2971[/C][C]0.012687[/C][/ROW]
[ROW][C]43[/C][C]-0.296419[/C][C]-2.2182[/C][C]0.015307[/C][/ROW]
[ROW][C]44[/C][C]-0.277025[/C][C]-2.0731[/C][C]0.02139[/C][/ROW]
[ROW][C]45[/C][C]-0.25751[/C][C]-1.927[/C][C]0.029528[/C][/ROW]
[ROW][C]46[/C][C]-0.240601[/C][C]-1.8005[/C][C]0.038585[/C][/ROW]
[ROW][C]47[/C][C]-0.223207[/C][C]-1.6703[/C][C]0.050217[/C][/ROW]
[ROW][C]48[/C][C]-0.21632[/C][C]-1.6188[/C][C]0.055556[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114700&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114700&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
10.851676.37330
20.7128055.33411e-06
30.6325314.73348e-06
40.5887664.40592.4e-05
50.5546424.15065.7e-05
60.5303913.96910.000104
70.4970383.71950.000232
80.470093.51780.000436
90.4512353.37670.00067
100.4185673.13230.001379
110.3886082.90810.002602
120.3504342.62240.005612
130.3015472.25660.013978
140.2493021.86560.033669
150.1926751.44180.077457
160.1566551.17230.123021
170.1249020.93470.176982
180.0958130.7170.238177
190.0633010.47370.318778
200.0367090.27470.392278
210.0018780.01410.49442
22-0.016416-0.12280.451336
23-0.042814-0.32040.374931
24-0.085254-0.6380.263042
25-0.123088-0.92110.180473
26-0.169992-1.27210.104296
27-0.234951-1.75820.042088
28-0.288959-2.16240.017438
29-0.312776-2.34060.01142
30-0.315582-2.36160.01085
31-0.323533-2.42110.00937
32-0.32152-2.4060.009726
33-0.3073-2.29960.01261
34-0.308426-2.3080.012357
35-0.314945-2.35680.010977
36-0.30601-2.290.012906
37-0.30624-2.29170.012853
38-0.2988-2.2360.014677
39-0.301421-2.25560.01401
40-0.309959-2.31950.012019
41-0.3188-2.38570.010227
42-0.306963-2.29710.012687
43-0.296419-2.21820.015307
44-0.277025-2.07310.02139
45-0.25751-1.9270.029528
46-0.240601-1.80050.038585
47-0.223207-1.67030.050217
48-0.21632-1.61880.055556







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.851676.37330
2-0.045647-0.34160.366968
30.1336140.99990.160836
40.0934980.69970.243512
50.0501090.3750.354545
60.0675490.50550.307599
7-0.00589-0.04410.482499
80.0429340.32130.374593
90.0336830.25210.400957
10-0.040059-0.29980.382729
110.0153970.11520.45434
12-0.051077-0.38220.351872
13-0.062613-0.46860.320603
14-0.058872-0.44060.330613
15-0.086546-0.64770.259927
160.0110040.08230.467332
17-0.046054-0.34460.365829
18-0.018377-0.13750.445557
19-0.031709-0.23730.406649
20-0.00928-0.06940.472441
21-0.04894-0.36620.357785
220.0341180.25530.399707
23-0.049417-0.36980.356461
24-0.064431-0.48220.315785
25-0.023463-0.17560.430627
26-0.094115-0.70430.242084
27-0.131172-0.98160.16526
28-0.066939-0.50090.309193
29-0.004882-0.03650.485492
300.0185620.13890.445011
31-0.038019-0.28450.388537
320.0494180.36980.356459
330.0652310.48810.313678
34-0.03402-0.25460.399989
350.0200380.150.440671
360.0615370.46050.32347
37-0.011983-0.08970.464433
380.0485390.36320.358899
39-0.044938-0.33630.368956
40-0.025904-0.19380.423499
41-0.048382-0.36210.359337
42-0.003302-0.02470.490187
43-0.033903-0.25370.400326
440.0144620.10820.457102
45-0.007537-0.05640.47761
460.0071740.05370.47869
470.0095810.07170.471549
48-0.035162-0.26310.396708

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.85167 & 6.3733 & 0 \tabularnewline
2 & -0.045647 & -0.3416 & 0.366968 \tabularnewline
3 & 0.133614 & 0.9999 & 0.160836 \tabularnewline
4 & 0.093498 & 0.6997 & 0.243512 \tabularnewline
5 & 0.050109 & 0.375 & 0.354545 \tabularnewline
6 & 0.067549 & 0.5055 & 0.307599 \tabularnewline
7 & -0.00589 & -0.0441 & 0.482499 \tabularnewline
8 & 0.042934 & 0.3213 & 0.374593 \tabularnewline
9 & 0.033683 & 0.2521 & 0.400957 \tabularnewline
10 & -0.040059 & -0.2998 & 0.382729 \tabularnewline
11 & 0.015397 & 0.1152 & 0.45434 \tabularnewline
12 & -0.051077 & -0.3822 & 0.351872 \tabularnewline
13 & -0.062613 & -0.4686 & 0.320603 \tabularnewline
14 & -0.058872 & -0.4406 & 0.330613 \tabularnewline
15 & -0.086546 & -0.6477 & 0.259927 \tabularnewline
16 & 0.011004 & 0.0823 & 0.467332 \tabularnewline
17 & -0.046054 & -0.3446 & 0.365829 \tabularnewline
18 & -0.018377 & -0.1375 & 0.445557 \tabularnewline
19 & -0.031709 & -0.2373 & 0.406649 \tabularnewline
20 & -0.00928 & -0.0694 & 0.472441 \tabularnewline
21 & -0.04894 & -0.3662 & 0.357785 \tabularnewline
22 & 0.034118 & 0.2553 & 0.399707 \tabularnewline
23 & -0.049417 & -0.3698 & 0.356461 \tabularnewline
24 & -0.064431 & -0.4822 & 0.315785 \tabularnewline
25 & -0.023463 & -0.1756 & 0.430627 \tabularnewline
26 & -0.094115 & -0.7043 & 0.242084 \tabularnewline
27 & -0.131172 & -0.9816 & 0.16526 \tabularnewline
28 & -0.066939 & -0.5009 & 0.309193 \tabularnewline
29 & -0.004882 & -0.0365 & 0.485492 \tabularnewline
30 & 0.018562 & 0.1389 & 0.445011 \tabularnewline
31 & -0.038019 & -0.2845 & 0.388537 \tabularnewline
32 & 0.049418 & 0.3698 & 0.356459 \tabularnewline
33 & 0.065231 & 0.4881 & 0.313678 \tabularnewline
34 & -0.03402 & -0.2546 & 0.399989 \tabularnewline
35 & 0.020038 & 0.15 & 0.440671 \tabularnewline
36 & 0.061537 & 0.4605 & 0.32347 \tabularnewline
37 & -0.011983 & -0.0897 & 0.464433 \tabularnewline
38 & 0.048539 & 0.3632 & 0.358899 \tabularnewline
39 & -0.044938 & -0.3363 & 0.368956 \tabularnewline
40 & -0.025904 & -0.1938 & 0.423499 \tabularnewline
41 & -0.048382 & -0.3621 & 0.359337 \tabularnewline
42 & -0.003302 & -0.0247 & 0.490187 \tabularnewline
43 & -0.033903 & -0.2537 & 0.400326 \tabularnewline
44 & 0.014462 & 0.1082 & 0.457102 \tabularnewline
45 & -0.007537 & -0.0564 & 0.47761 \tabularnewline
46 & 0.007174 & 0.0537 & 0.47869 \tabularnewline
47 & 0.009581 & 0.0717 & 0.471549 \tabularnewline
48 & -0.035162 & -0.2631 & 0.396708 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114700&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]0.85167[/C][C]6.3733[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.045647[/C][C]-0.3416[/C][C]0.366968[/C][/ROW]
[ROW][C]3[/C][C]0.133614[/C][C]0.9999[/C][C]0.160836[/C][/ROW]
[ROW][C]4[/C][C]0.093498[/C][C]0.6997[/C][C]0.243512[/C][/ROW]
[ROW][C]5[/C][C]0.050109[/C][C]0.375[/C][C]0.354545[/C][/ROW]
[ROW][C]6[/C][C]0.067549[/C][C]0.5055[/C][C]0.307599[/C][/ROW]
[ROW][C]7[/C][C]-0.00589[/C][C]-0.0441[/C][C]0.482499[/C][/ROW]
[ROW][C]8[/C][C]0.042934[/C][C]0.3213[/C][C]0.374593[/C][/ROW]
[ROW][C]9[/C][C]0.033683[/C][C]0.2521[/C][C]0.400957[/C][/ROW]
[ROW][C]10[/C][C]-0.040059[/C][C]-0.2998[/C][C]0.382729[/C][/ROW]
[ROW][C]11[/C][C]0.015397[/C][C]0.1152[/C][C]0.45434[/C][/ROW]
[ROW][C]12[/C][C]-0.051077[/C][C]-0.3822[/C][C]0.351872[/C][/ROW]
[ROW][C]13[/C][C]-0.062613[/C][C]-0.4686[/C][C]0.320603[/C][/ROW]
[ROW][C]14[/C][C]-0.058872[/C][C]-0.4406[/C][C]0.330613[/C][/ROW]
[ROW][C]15[/C][C]-0.086546[/C][C]-0.6477[/C][C]0.259927[/C][/ROW]
[ROW][C]16[/C][C]0.011004[/C][C]0.0823[/C][C]0.467332[/C][/ROW]
[ROW][C]17[/C][C]-0.046054[/C][C]-0.3446[/C][C]0.365829[/C][/ROW]
[ROW][C]18[/C][C]-0.018377[/C][C]-0.1375[/C][C]0.445557[/C][/ROW]
[ROW][C]19[/C][C]-0.031709[/C][C]-0.2373[/C][C]0.406649[/C][/ROW]
[ROW][C]20[/C][C]-0.00928[/C][C]-0.0694[/C][C]0.472441[/C][/ROW]
[ROW][C]21[/C][C]-0.04894[/C][C]-0.3662[/C][C]0.357785[/C][/ROW]
[ROW][C]22[/C][C]0.034118[/C][C]0.2553[/C][C]0.399707[/C][/ROW]
[ROW][C]23[/C][C]-0.049417[/C][C]-0.3698[/C][C]0.356461[/C][/ROW]
[ROW][C]24[/C][C]-0.064431[/C][C]-0.4822[/C][C]0.315785[/C][/ROW]
[ROW][C]25[/C][C]-0.023463[/C][C]-0.1756[/C][C]0.430627[/C][/ROW]
[ROW][C]26[/C][C]-0.094115[/C][C]-0.7043[/C][C]0.242084[/C][/ROW]
[ROW][C]27[/C][C]-0.131172[/C][C]-0.9816[/C][C]0.16526[/C][/ROW]
[ROW][C]28[/C][C]-0.066939[/C][C]-0.5009[/C][C]0.309193[/C][/ROW]
[ROW][C]29[/C][C]-0.004882[/C][C]-0.0365[/C][C]0.485492[/C][/ROW]
[ROW][C]30[/C][C]0.018562[/C][C]0.1389[/C][C]0.445011[/C][/ROW]
[ROW][C]31[/C][C]-0.038019[/C][C]-0.2845[/C][C]0.388537[/C][/ROW]
[ROW][C]32[/C][C]0.049418[/C][C]0.3698[/C][C]0.356459[/C][/ROW]
[ROW][C]33[/C][C]0.065231[/C][C]0.4881[/C][C]0.313678[/C][/ROW]
[ROW][C]34[/C][C]-0.03402[/C][C]-0.2546[/C][C]0.399989[/C][/ROW]
[ROW][C]35[/C][C]0.020038[/C][C]0.15[/C][C]0.440671[/C][/ROW]
[ROW][C]36[/C][C]0.061537[/C][C]0.4605[/C][C]0.32347[/C][/ROW]
[ROW][C]37[/C][C]-0.011983[/C][C]-0.0897[/C][C]0.464433[/C][/ROW]
[ROW][C]38[/C][C]0.048539[/C][C]0.3632[/C][C]0.358899[/C][/ROW]
[ROW][C]39[/C][C]-0.044938[/C][C]-0.3363[/C][C]0.368956[/C][/ROW]
[ROW][C]40[/C][C]-0.025904[/C][C]-0.1938[/C][C]0.423499[/C][/ROW]
[ROW][C]41[/C][C]-0.048382[/C][C]-0.3621[/C][C]0.359337[/C][/ROW]
[ROW][C]42[/C][C]-0.003302[/C][C]-0.0247[/C][C]0.490187[/C][/ROW]
[ROW][C]43[/C][C]-0.033903[/C][C]-0.2537[/C][C]0.400326[/C][/ROW]
[ROW][C]44[/C][C]0.014462[/C][C]0.1082[/C][C]0.457102[/C][/ROW]
[ROW][C]45[/C][C]-0.007537[/C][C]-0.0564[/C][C]0.47761[/C][/ROW]
[ROW][C]46[/C][C]0.007174[/C][C]0.0537[/C][C]0.47869[/C][/ROW]
[ROW][C]47[/C][C]0.009581[/C][C]0.0717[/C][C]0.471549[/C][/ROW]
[ROW][C]48[/C][C]-0.035162[/C][C]-0.2631[/C][C]0.396708[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114700&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114700&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
10.851676.37330
2-0.045647-0.34160.366968
30.1336140.99990.160836
40.0934980.69970.243512
50.0501090.3750.354545
60.0675490.50550.307599
7-0.00589-0.04410.482499
80.0429340.32130.374593
90.0336830.25210.400957
10-0.040059-0.29980.382729
110.0153970.11520.45434
12-0.051077-0.38220.351872
13-0.062613-0.46860.320603
14-0.058872-0.44060.330613
15-0.086546-0.64770.259927
160.0110040.08230.467332
17-0.046054-0.34460.365829
18-0.018377-0.13750.445557
19-0.031709-0.23730.406649
20-0.00928-0.06940.472441
21-0.04894-0.36620.357785
220.0341180.25530.399707
23-0.049417-0.36980.356461
24-0.064431-0.48220.315785
25-0.023463-0.17560.430627
26-0.094115-0.70430.242084
27-0.131172-0.98160.16526
28-0.066939-0.50090.309193
29-0.004882-0.03650.485492
300.0185620.13890.445011
31-0.038019-0.28450.388537
320.0494180.36980.356459
330.0652310.48810.313678
34-0.03402-0.25460.399989
350.0200380.150.440671
360.0615370.46050.32347
37-0.011983-0.08970.464433
380.0485390.36320.358899
39-0.044938-0.33630.368956
40-0.025904-0.19380.423499
41-0.048382-0.36210.359337
42-0.003302-0.02470.490187
43-0.033903-0.25370.400326
440.0144620.10820.457102
45-0.007537-0.05640.47761
460.0071740.05370.47869
470.0095810.07170.471549
48-0.035162-0.26310.396708



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