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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 24 Jan 2009 11:00:52 -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/Jan/24/t1232820133zfxiz40t3rph74e.htm/, Retrieved Fri, 01 Nov 2024 01:04:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36945, Retrieved Fri, 01 Nov 2024 01:04:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact249
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [] [] [1970-01-01 00:00:00] [2097edf1f094fab6879a8cb46df74ec2]
- RMPD  [(Partial) Autocorrelation Function] [] [2008-12-17 12:55:33] [2097edf1f094fab6879a8cb46df74ec2]
-   PD      [(Partial) Autocorrelation Function] [Dennis Collin oef...] [2009-01-24 18:00:52] [06e57c0cb32e2f613cf343ab1a0ac99f] [Current]
-   PD        [(Partial) Autocorrelation Function] [Dennis Collin oef...] [2009-01-24 18:07:07] [2097edf1f094fab6879a8cb46df74ec2]
-   P           [(Partial) Autocorrelation Function] [Dennis Collin oef...] [2009-01-24 18:09:37] [2097edf1f094fab6879a8cb46df74ec2]
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Dataseries X:
1,29
1,29
1,3
1,3
1,3
1,3
1,31
1,31
1,31
1,31
1,31
1,32
1,32
1,32
1,32
1,33
1,33
1,33
1,34
1,34
1,34
1,34
1,34
1,34
1,34
1,35
1,36
1,36
1,36
1,37
1,37
1,37
1,37
1,37
1,37
1,37
1,38
1,38
1,38
1,39
1,4
1,4
1,4
1,4
1,41
1,42
1,43
1,43
1,43
1,44
1,45
1,45
1,46
1,46
1,47
1,47
1,47
1,48
1,49
1,49
1,49
1,5
1,51
1,51
1,51
1,52
1,52
1,52
1,52
1,53
1,53
1,53
1,53
1,54
1,54
1,55
1,55
1,55
1,56
1,56
1,58
1,58
1,58
1,58
1,58
1,58
1,59
1,59
1,6
1,6
1,6
1,61
1,62
1,62
1,63
1,63




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=36945&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=36945&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36945&T=0

As an alternative you can also use a QR Code:  

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

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







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.5-4.84772e-06
2-0.053571-0.51940.302353
3-0.017857-0.17310.43146
40.1251.21190.11429
5-0.017857-0.17310.43146
6-0.053571-0.51940.302353
7-0.035714-0.34630.36496
80.1607141.55820.061275
9-0.142857-1.38510.084658
10-0.053571-0.51940.302353
110.1785711.73130.043338
12-0.142857-1.38510.084658
130.0892860.86570.194441
14-0.035714-0.34630.36496
150.0178570.17310.43146
16000.5
17-0.053571-0.51940.302353
180.0178570.17310.43146
190.1071431.03880.150784
20-0.178571-1.73130.043338
210.1785711.73130.043338
22-0.178571-1.73130.043338
230.1607141.55820.061275
24-0.107143-1.03880.150784
250.0357140.34630.36496
260.0714290.69250.245157
27-0.125-1.21190.11429
28000.5
290.1071431.03880.150784
30-0.035714-0.34630.36496
31000.5
32-0.053571-0.51940.302353
33-0.035714-0.34630.36496
340.1785711.73130.043338
35-0.160714-1.55820.061275
360.1071431.03880.150784
37-0.035714-0.34630.36496
38-0.071429-0.69250.245157
390.0535710.51940.302353
400.0714290.69250.245157
41-0.125-1.21190.11429
420.0535710.51940.302353
43-0.017857-0.17310.43146
440.1428571.38510.084658
45-0.214286-2.07760.020238
460.0714290.69250.245157
470.0535710.51940.302353
48000.5

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.5 & -4.8477 & 2e-06 \tabularnewline
2 & -0.053571 & -0.5194 & 0.302353 \tabularnewline
3 & -0.017857 & -0.1731 & 0.43146 \tabularnewline
4 & 0.125 & 1.2119 & 0.11429 \tabularnewline
5 & -0.017857 & -0.1731 & 0.43146 \tabularnewline
6 & -0.053571 & -0.5194 & 0.302353 \tabularnewline
7 & -0.035714 & -0.3463 & 0.36496 \tabularnewline
8 & 0.160714 & 1.5582 & 0.061275 \tabularnewline
9 & -0.142857 & -1.3851 & 0.084658 \tabularnewline
10 & -0.053571 & -0.5194 & 0.302353 \tabularnewline
11 & 0.178571 & 1.7313 & 0.043338 \tabularnewline
12 & -0.142857 & -1.3851 & 0.084658 \tabularnewline
13 & 0.089286 & 0.8657 & 0.194441 \tabularnewline
14 & -0.035714 & -0.3463 & 0.36496 \tabularnewline
15 & 0.017857 & 0.1731 & 0.43146 \tabularnewline
16 & 0 & 0 & 0.5 \tabularnewline
17 & -0.053571 & -0.5194 & 0.302353 \tabularnewline
18 & 0.017857 & 0.1731 & 0.43146 \tabularnewline
19 & 0.107143 & 1.0388 & 0.150784 \tabularnewline
20 & -0.178571 & -1.7313 & 0.043338 \tabularnewline
21 & 0.178571 & 1.7313 & 0.043338 \tabularnewline
22 & -0.178571 & -1.7313 & 0.043338 \tabularnewline
23 & 0.160714 & 1.5582 & 0.061275 \tabularnewline
24 & -0.107143 & -1.0388 & 0.150784 \tabularnewline
25 & 0.035714 & 0.3463 & 0.36496 \tabularnewline
26 & 0.071429 & 0.6925 & 0.245157 \tabularnewline
27 & -0.125 & -1.2119 & 0.11429 \tabularnewline
28 & 0 & 0 & 0.5 \tabularnewline
29 & 0.107143 & 1.0388 & 0.150784 \tabularnewline
30 & -0.035714 & -0.3463 & 0.36496 \tabularnewline
31 & 0 & 0 & 0.5 \tabularnewline
32 & -0.053571 & -0.5194 & 0.302353 \tabularnewline
33 & -0.035714 & -0.3463 & 0.36496 \tabularnewline
34 & 0.178571 & 1.7313 & 0.043338 \tabularnewline
35 & -0.160714 & -1.5582 & 0.061275 \tabularnewline
36 & 0.107143 & 1.0388 & 0.150784 \tabularnewline
37 & -0.035714 & -0.3463 & 0.36496 \tabularnewline
38 & -0.071429 & -0.6925 & 0.245157 \tabularnewline
39 & 0.053571 & 0.5194 & 0.302353 \tabularnewline
40 & 0.071429 & 0.6925 & 0.245157 \tabularnewline
41 & -0.125 & -1.2119 & 0.11429 \tabularnewline
42 & 0.053571 & 0.5194 & 0.302353 \tabularnewline
43 & -0.017857 & -0.1731 & 0.43146 \tabularnewline
44 & 0.142857 & 1.3851 & 0.084658 \tabularnewline
45 & -0.214286 & -2.0776 & 0.020238 \tabularnewline
46 & 0.071429 & 0.6925 & 0.245157 \tabularnewline
47 & 0.053571 & 0.5194 & 0.302353 \tabularnewline
48 & 0 & 0 & 0.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36945&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]-0.5[/C][C]-4.8477[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.053571[/C][C]-0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]3[/C][C]-0.017857[/C][C]-0.1731[/C][C]0.43146[/C][/ROW]
[ROW][C]4[/C][C]0.125[/C][C]1.2119[/C][C]0.11429[/C][/ROW]
[ROW][C]5[/C][C]-0.017857[/C][C]-0.1731[/C][C]0.43146[/C][/ROW]
[ROW][C]6[/C][C]-0.053571[/C][C]-0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]7[/C][C]-0.035714[/C][C]-0.3463[/C][C]0.36496[/C][/ROW]
[ROW][C]8[/C][C]0.160714[/C][C]1.5582[/C][C]0.061275[/C][/ROW]
[ROW][C]9[/C][C]-0.142857[/C][C]-1.3851[/C][C]0.084658[/C][/ROW]
[ROW][C]10[/C][C]-0.053571[/C][C]-0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]11[/C][C]0.178571[/C][C]1.7313[/C][C]0.043338[/C][/ROW]
[ROW][C]12[/C][C]-0.142857[/C][C]-1.3851[/C][C]0.084658[/C][/ROW]
[ROW][C]13[/C][C]0.089286[/C][C]0.8657[/C][C]0.194441[/C][/ROW]
[ROW][C]14[/C][C]-0.035714[/C][C]-0.3463[/C][C]0.36496[/C][/ROW]
[ROW][C]15[/C][C]0.017857[/C][C]0.1731[/C][C]0.43146[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]17[/C][C]-0.053571[/C][C]-0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]18[/C][C]0.017857[/C][C]0.1731[/C][C]0.43146[/C][/ROW]
[ROW][C]19[/C][C]0.107143[/C][C]1.0388[/C][C]0.150784[/C][/ROW]
[ROW][C]20[/C][C]-0.178571[/C][C]-1.7313[/C][C]0.043338[/C][/ROW]
[ROW][C]21[/C][C]0.178571[/C][C]1.7313[/C][C]0.043338[/C][/ROW]
[ROW][C]22[/C][C]-0.178571[/C][C]-1.7313[/C][C]0.043338[/C][/ROW]
[ROW][C]23[/C][C]0.160714[/C][C]1.5582[/C][C]0.061275[/C][/ROW]
[ROW][C]24[/C][C]-0.107143[/C][C]-1.0388[/C][C]0.150784[/C][/ROW]
[ROW][C]25[/C][C]0.035714[/C][C]0.3463[/C][C]0.36496[/C][/ROW]
[ROW][C]26[/C][C]0.071429[/C][C]0.6925[/C][C]0.245157[/C][/ROW]
[ROW][C]27[/C][C]-0.125[/C][C]-1.2119[/C][C]0.11429[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]29[/C][C]0.107143[/C][C]1.0388[/C][C]0.150784[/C][/ROW]
[ROW][C]30[/C][C]-0.035714[/C][C]-0.3463[/C][C]0.36496[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[ROW][C]32[/C][C]-0.053571[/C][C]-0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]33[/C][C]-0.035714[/C][C]-0.3463[/C][C]0.36496[/C][/ROW]
[ROW][C]34[/C][C]0.178571[/C][C]1.7313[/C][C]0.043338[/C][/ROW]
[ROW][C]35[/C][C]-0.160714[/C][C]-1.5582[/C][C]0.061275[/C][/ROW]
[ROW][C]36[/C][C]0.107143[/C][C]1.0388[/C][C]0.150784[/C][/ROW]
[ROW][C]37[/C][C]-0.035714[/C][C]-0.3463[/C][C]0.36496[/C][/ROW]
[ROW][C]38[/C][C]-0.071429[/C][C]-0.6925[/C][C]0.245157[/C][/ROW]
[ROW][C]39[/C][C]0.053571[/C][C]0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]40[/C][C]0.071429[/C][C]0.6925[/C][C]0.245157[/C][/ROW]
[ROW][C]41[/C][C]-0.125[/C][C]-1.2119[/C][C]0.11429[/C][/ROW]
[ROW][C]42[/C][C]0.053571[/C][C]0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]43[/C][C]-0.017857[/C][C]-0.1731[/C][C]0.43146[/C][/ROW]
[ROW][C]44[/C][C]0.142857[/C][C]1.3851[/C][C]0.084658[/C][/ROW]
[ROW][C]45[/C][C]-0.214286[/C][C]-2.0776[/C][C]0.020238[/C][/ROW]
[ROW][C]46[/C][C]0.071429[/C][C]0.6925[/C][C]0.245157[/C][/ROW]
[ROW][C]47[/C][C]0.053571[/C][C]0.5194[/C][C]0.302353[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0[/C][C]0.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36945&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36945&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
1-0.5-4.84772e-06
2-0.053571-0.51940.302353
3-0.017857-0.17310.43146
40.1251.21190.11429
5-0.017857-0.17310.43146
6-0.053571-0.51940.302353
7-0.035714-0.34630.36496
80.1607141.55820.061275
9-0.142857-1.38510.084658
10-0.053571-0.51940.302353
110.1785711.73130.043338
12-0.142857-1.38510.084658
130.0892860.86570.194441
14-0.035714-0.34630.36496
150.0178570.17310.43146
16000.5
17-0.053571-0.51940.302353
180.0178570.17310.43146
190.1071431.03880.150784
20-0.178571-1.73130.043338
210.1785711.73130.043338
22-0.178571-1.73130.043338
230.1607141.55820.061275
24-0.107143-1.03880.150784
250.0357140.34630.36496
260.0714290.69250.245157
27-0.125-1.21190.11429
28000.5
290.1071431.03880.150784
30-0.035714-0.34630.36496
31000.5
32-0.053571-0.51940.302353
33-0.035714-0.34630.36496
340.1785711.73130.043338
35-0.160714-1.55820.061275
360.1071431.03880.150784
37-0.035714-0.34630.36496
38-0.071429-0.69250.245157
390.0535710.51940.302353
400.0714290.69250.245157
41-0.125-1.21190.11429
420.0535710.51940.302353
43-0.017857-0.17310.43146
440.1428571.38510.084658
45-0.214286-2.07760.020238
460.0714290.69250.245157
470.0535710.51940.302353
48000.5







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.5-4.84772e-06
2-0.404762-3.92438.3e-05
3-0.411186-3.98666.6e-05
4-0.255737-2.47950.00747
5-0.150843-1.46250.073473
6-0.1292-1.25260.106721
7-0.19307-1.87190.032166
80.0274310.2660.395428
9-0.041849-0.40570.342929
10-0.211289-2.04850.021648
11-0.021502-0.20850.417657
12-0.190932-1.85120.033644
13-0.10199-0.98880.162642
14-0.025377-0.2460.403093
150.0179160.17370.431236
160.0629480.61030.271567
170.0171350.16610.434205
18-0.032362-0.31380.377199
190.0549460.53270.297741
20-0.097877-0.9490.172538
210.1155671.12050.132685
22-0.106242-1.03010.152813
230.0842260.81660.20811
24-0.01961-0.19010.424811
25-0.020058-0.19450.423113
260.1619521.57020.059866
27-0.05858-0.5680.285709
28-0.092463-0.89650.186148
29-0.075485-0.73190.233039
30-0.06679-0.64750.259428
310.0779750.7560.225771
32-0.036506-0.35390.36209
33-0.107563-1.04290.149844
34-0.05782-0.56060.288208
35-0.106786-1.03530.151585
360.0932480.90410.184135
370.0734260.71190.239147
380.0251320.24370.404012
39-0.009989-0.09690.461526
400.0943780.9150.181258
410.0798690.77440.220331
42-0.093108-0.90270.184493
430.0158030.15320.439279
440.1756161.70270.045968
45-0.011042-0.10710.457487
460.1629941.58030.0587
470.0468880.45460.325225
480.0539060.52260.301229

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.5 & -4.8477 & 2e-06 \tabularnewline
2 & -0.404762 & -3.9243 & 8.3e-05 \tabularnewline
3 & -0.411186 & -3.9866 & 6.6e-05 \tabularnewline
4 & -0.255737 & -2.4795 & 0.00747 \tabularnewline
5 & -0.150843 & -1.4625 & 0.073473 \tabularnewline
6 & -0.1292 & -1.2526 & 0.106721 \tabularnewline
7 & -0.19307 & -1.8719 & 0.032166 \tabularnewline
8 & 0.027431 & 0.266 & 0.395428 \tabularnewline
9 & -0.041849 & -0.4057 & 0.342929 \tabularnewline
10 & -0.211289 & -2.0485 & 0.021648 \tabularnewline
11 & -0.021502 & -0.2085 & 0.417657 \tabularnewline
12 & -0.190932 & -1.8512 & 0.033644 \tabularnewline
13 & -0.10199 & -0.9888 & 0.162642 \tabularnewline
14 & -0.025377 & -0.246 & 0.403093 \tabularnewline
15 & 0.017916 & 0.1737 & 0.431236 \tabularnewline
16 & 0.062948 & 0.6103 & 0.271567 \tabularnewline
17 & 0.017135 & 0.1661 & 0.434205 \tabularnewline
18 & -0.032362 & -0.3138 & 0.377199 \tabularnewline
19 & 0.054946 & 0.5327 & 0.297741 \tabularnewline
20 & -0.097877 & -0.949 & 0.172538 \tabularnewline
21 & 0.115567 & 1.1205 & 0.132685 \tabularnewline
22 & -0.106242 & -1.0301 & 0.152813 \tabularnewline
23 & 0.084226 & 0.8166 & 0.20811 \tabularnewline
24 & -0.01961 & -0.1901 & 0.424811 \tabularnewline
25 & -0.020058 & -0.1945 & 0.423113 \tabularnewline
26 & 0.161952 & 1.5702 & 0.059866 \tabularnewline
27 & -0.05858 & -0.568 & 0.285709 \tabularnewline
28 & -0.092463 & -0.8965 & 0.186148 \tabularnewline
29 & -0.075485 & -0.7319 & 0.233039 \tabularnewline
30 & -0.06679 & -0.6475 & 0.259428 \tabularnewline
31 & 0.077975 & 0.756 & 0.225771 \tabularnewline
32 & -0.036506 & -0.3539 & 0.36209 \tabularnewline
33 & -0.107563 & -1.0429 & 0.149844 \tabularnewline
34 & -0.05782 & -0.5606 & 0.288208 \tabularnewline
35 & -0.106786 & -1.0353 & 0.151585 \tabularnewline
36 & 0.093248 & 0.9041 & 0.184135 \tabularnewline
37 & 0.073426 & 0.7119 & 0.239147 \tabularnewline
38 & 0.025132 & 0.2437 & 0.404012 \tabularnewline
39 & -0.009989 & -0.0969 & 0.461526 \tabularnewline
40 & 0.094378 & 0.915 & 0.181258 \tabularnewline
41 & 0.079869 & 0.7744 & 0.220331 \tabularnewline
42 & -0.093108 & -0.9027 & 0.184493 \tabularnewline
43 & 0.015803 & 0.1532 & 0.439279 \tabularnewline
44 & 0.175616 & 1.7027 & 0.045968 \tabularnewline
45 & -0.011042 & -0.1071 & 0.457487 \tabularnewline
46 & 0.162994 & 1.5803 & 0.0587 \tabularnewline
47 & 0.046888 & 0.4546 & 0.325225 \tabularnewline
48 & 0.053906 & 0.5226 & 0.301229 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36945&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]-0.5[/C][C]-4.8477[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.404762[/C][C]-3.9243[/C][C]8.3e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.411186[/C][C]-3.9866[/C][C]6.6e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.255737[/C][C]-2.4795[/C][C]0.00747[/C][/ROW]
[ROW][C]5[/C][C]-0.150843[/C][C]-1.4625[/C][C]0.073473[/C][/ROW]
[ROW][C]6[/C][C]-0.1292[/C][C]-1.2526[/C][C]0.106721[/C][/ROW]
[ROW][C]7[/C][C]-0.19307[/C][C]-1.8719[/C][C]0.032166[/C][/ROW]
[ROW][C]8[/C][C]0.027431[/C][C]0.266[/C][C]0.395428[/C][/ROW]
[ROW][C]9[/C][C]-0.041849[/C][C]-0.4057[/C][C]0.342929[/C][/ROW]
[ROW][C]10[/C][C]-0.211289[/C][C]-2.0485[/C][C]0.021648[/C][/ROW]
[ROW][C]11[/C][C]-0.021502[/C][C]-0.2085[/C][C]0.417657[/C][/ROW]
[ROW][C]12[/C][C]-0.190932[/C][C]-1.8512[/C][C]0.033644[/C][/ROW]
[ROW][C]13[/C][C]-0.10199[/C][C]-0.9888[/C][C]0.162642[/C][/ROW]
[ROW][C]14[/C][C]-0.025377[/C][C]-0.246[/C][C]0.403093[/C][/ROW]
[ROW][C]15[/C][C]0.017916[/C][C]0.1737[/C][C]0.431236[/C][/ROW]
[ROW][C]16[/C][C]0.062948[/C][C]0.6103[/C][C]0.271567[/C][/ROW]
[ROW][C]17[/C][C]0.017135[/C][C]0.1661[/C][C]0.434205[/C][/ROW]
[ROW][C]18[/C][C]-0.032362[/C][C]-0.3138[/C][C]0.377199[/C][/ROW]
[ROW][C]19[/C][C]0.054946[/C][C]0.5327[/C][C]0.297741[/C][/ROW]
[ROW][C]20[/C][C]-0.097877[/C][C]-0.949[/C][C]0.172538[/C][/ROW]
[ROW][C]21[/C][C]0.115567[/C][C]1.1205[/C][C]0.132685[/C][/ROW]
[ROW][C]22[/C][C]-0.106242[/C][C]-1.0301[/C][C]0.152813[/C][/ROW]
[ROW][C]23[/C][C]0.084226[/C][C]0.8166[/C][C]0.20811[/C][/ROW]
[ROW][C]24[/C][C]-0.01961[/C][C]-0.1901[/C][C]0.424811[/C][/ROW]
[ROW][C]25[/C][C]-0.020058[/C][C]-0.1945[/C][C]0.423113[/C][/ROW]
[ROW][C]26[/C][C]0.161952[/C][C]1.5702[/C][C]0.059866[/C][/ROW]
[ROW][C]27[/C][C]-0.05858[/C][C]-0.568[/C][C]0.285709[/C][/ROW]
[ROW][C]28[/C][C]-0.092463[/C][C]-0.8965[/C][C]0.186148[/C][/ROW]
[ROW][C]29[/C][C]-0.075485[/C][C]-0.7319[/C][C]0.233039[/C][/ROW]
[ROW][C]30[/C][C]-0.06679[/C][C]-0.6475[/C][C]0.259428[/C][/ROW]
[ROW][C]31[/C][C]0.077975[/C][C]0.756[/C][C]0.225771[/C][/ROW]
[ROW][C]32[/C][C]-0.036506[/C][C]-0.3539[/C][C]0.36209[/C][/ROW]
[ROW][C]33[/C][C]-0.107563[/C][C]-1.0429[/C][C]0.149844[/C][/ROW]
[ROW][C]34[/C][C]-0.05782[/C][C]-0.5606[/C][C]0.288208[/C][/ROW]
[ROW][C]35[/C][C]-0.106786[/C][C]-1.0353[/C][C]0.151585[/C][/ROW]
[ROW][C]36[/C][C]0.093248[/C][C]0.9041[/C][C]0.184135[/C][/ROW]
[ROW][C]37[/C][C]0.073426[/C][C]0.7119[/C][C]0.239147[/C][/ROW]
[ROW][C]38[/C][C]0.025132[/C][C]0.2437[/C][C]0.404012[/C][/ROW]
[ROW][C]39[/C][C]-0.009989[/C][C]-0.0969[/C][C]0.461526[/C][/ROW]
[ROW][C]40[/C][C]0.094378[/C][C]0.915[/C][C]0.181258[/C][/ROW]
[ROW][C]41[/C][C]0.079869[/C][C]0.7744[/C][C]0.220331[/C][/ROW]
[ROW][C]42[/C][C]-0.093108[/C][C]-0.9027[/C][C]0.184493[/C][/ROW]
[ROW][C]43[/C][C]0.015803[/C][C]0.1532[/C][C]0.439279[/C][/ROW]
[ROW][C]44[/C][C]0.175616[/C][C]1.7027[/C][C]0.045968[/C][/ROW]
[ROW][C]45[/C][C]-0.011042[/C][C]-0.1071[/C][C]0.457487[/C][/ROW]
[ROW][C]46[/C][C]0.162994[/C][C]1.5803[/C][C]0.0587[/C][/ROW]
[ROW][C]47[/C][C]0.046888[/C][C]0.4546[/C][C]0.325225[/C][/ROW]
[ROW][C]48[/C][C]0.053906[/C][C]0.5226[/C][C]0.301229[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36945&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36945&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
1-0.5-4.84772e-06
2-0.404762-3.92438.3e-05
3-0.411186-3.98666.6e-05
4-0.255737-2.47950.00747
5-0.150843-1.46250.073473
6-0.1292-1.25260.106721
7-0.19307-1.87190.032166
80.0274310.2660.395428
9-0.041849-0.40570.342929
10-0.211289-2.04850.021648
11-0.021502-0.20850.417657
12-0.190932-1.85120.033644
13-0.10199-0.98880.162642
14-0.025377-0.2460.403093
150.0179160.17370.431236
160.0629480.61030.271567
170.0171350.16610.434205
18-0.032362-0.31380.377199
190.0549460.53270.297741
20-0.097877-0.9490.172538
210.1155671.12050.132685
22-0.106242-1.03010.152813
230.0842260.81660.20811
24-0.01961-0.19010.424811
25-0.020058-0.19450.423113
260.1619521.57020.059866
27-0.05858-0.5680.285709
28-0.092463-0.89650.186148
29-0.075485-0.73190.233039
30-0.06679-0.64750.259428
310.0779750.7560.225771
32-0.036506-0.35390.36209
33-0.107563-1.04290.149844
34-0.05782-0.56060.288208
35-0.106786-1.03530.151585
360.0932480.90410.184135
370.0734260.71190.239147
380.0251320.24370.404012
39-0.009989-0.09690.461526
400.0943780.9150.181258
410.0798690.77440.220331
42-0.093108-0.90270.184493
430.0158030.15320.439279
440.1756161.70270.045968
45-0.011042-0.10710.457487
460.1629941.58030.0587
470.0468880.45460.325225
480.0539060.52260.301229



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')