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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 03 Dec 2009 09:14:25 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t1259857024f8mlvhxq2199yhn.htm/, Retrieved Thu, 28 Mar 2024 15:32:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62876, Retrieved Thu, 28 Mar 2024 15:32:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146
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] [] [2009-11-27 14:47:30] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [] [2009-12-03 16:14:25] [bcaf453a09027aa0f995cb78bdc3c98a] [Current]
-   PD        [(Partial) Autocorrelation Function] [Autocorrelatie ] [2009-12-04 19:50:26] [3dd791303389e75e672968b227170a72]
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Dataseries X:
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8
8.1
8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62876&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62876&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62876&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4963393.43870.000609
2-0.061079-0.42320.337031
3-0.482081-3.340.000814
4-0.45395-3.14510.001424
5-0.122351-0.84770.200414
60.2421971.6780.049925
70.2957612.04910.02297
80.1412330.97850.166369
9-0.115029-0.79690.214704
10-0.199037-1.3790.087149
11-0.125819-0.87170.193856
12-0.06763-0.46860.320754
130.0512520.35510.36204
140.1048170.72620.235623
150.0306360.21230.416405
16-0.125626-0.87040.194217
17-0.184778-1.28020.103317
18-0.06185-0.42850.335099
190.1055880.73150.234005
200.2851641.97570.026978
210.2682081.85820.03464
220.0408480.2830.389196
23-0.266281-1.84490.035617
24-0.356647-2.47090.008539
25-0.166089-1.15070.127779
260.0730250.50590.30761
270.173411.20140.117741
280.1252410.86770.19494
290.0100190.06940.472474
30-0.162428-1.12530.133022
31-0.133141-0.92240.18046
32-0.08131-0.56330.287915
330.0156070.10810.457172
340.0125240.08680.465608
350.0574180.39780.346269
360.041040.28430.388688
370.0194610.13480.446656
380.0146440.10150.459807
390.0312140.21630.414852
400.0472060.32710.372525
410.053950.37380.355108
420.0034680.0240.490465
43-0.013487-0.09340.46297
44-0.039114-0.2710.393781
45-0.049133-0.34040.367519
460.005010.03470.486228
470.021580.14950.440889
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.496339 & 3.4387 & 0.000609 \tabularnewline
2 & -0.061079 & -0.4232 & 0.337031 \tabularnewline
3 & -0.482081 & -3.34 & 0.000814 \tabularnewline
4 & -0.45395 & -3.1451 & 0.001424 \tabularnewline
5 & -0.122351 & -0.8477 & 0.200414 \tabularnewline
6 & 0.242197 & 1.678 & 0.049925 \tabularnewline
7 & 0.295761 & 2.0491 & 0.02297 \tabularnewline
8 & 0.141233 & 0.9785 & 0.166369 \tabularnewline
9 & -0.115029 & -0.7969 & 0.214704 \tabularnewline
10 & -0.199037 & -1.379 & 0.087149 \tabularnewline
11 & -0.125819 & -0.8717 & 0.193856 \tabularnewline
12 & -0.06763 & -0.4686 & 0.320754 \tabularnewline
13 & 0.051252 & 0.3551 & 0.36204 \tabularnewline
14 & 0.104817 & 0.7262 & 0.235623 \tabularnewline
15 & 0.030636 & 0.2123 & 0.416405 \tabularnewline
16 & -0.125626 & -0.8704 & 0.194217 \tabularnewline
17 & -0.184778 & -1.2802 & 0.103317 \tabularnewline
18 & -0.06185 & -0.4285 & 0.335099 \tabularnewline
19 & 0.105588 & 0.7315 & 0.234005 \tabularnewline
20 & 0.285164 & 1.9757 & 0.026978 \tabularnewline
21 & 0.268208 & 1.8582 & 0.03464 \tabularnewline
22 & 0.040848 & 0.283 & 0.389196 \tabularnewline
23 & -0.266281 & -1.8449 & 0.035617 \tabularnewline
24 & -0.356647 & -2.4709 & 0.008539 \tabularnewline
25 & -0.166089 & -1.1507 & 0.127779 \tabularnewline
26 & 0.073025 & 0.5059 & 0.30761 \tabularnewline
27 & 0.17341 & 1.2014 & 0.117741 \tabularnewline
28 & 0.125241 & 0.8677 & 0.19494 \tabularnewline
29 & 0.010019 & 0.0694 & 0.472474 \tabularnewline
30 & -0.162428 & -1.1253 & 0.133022 \tabularnewline
31 & -0.133141 & -0.9224 & 0.18046 \tabularnewline
32 & -0.08131 & -0.5633 & 0.287915 \tabularnewline
33 & 0.015607 & 0.1081 & 0.457172 \tabularnewline
34 & 0.012524 & 0.0868 & 0.465608 \tabularnewline
35 & 0.057418 & 0.3978 & 0.346269 \tabularnewline
36 & 0.04104 & 0.2843 & 0.388688 \tabularnewline
37 & 0.019461 & 0.1348 & 0.446656 \tabularnewline
38 & 0.014644 & 0.1015 & 0.459807 \tabularnewline
39 & 0.031214 & 0.2163 & 0.414852 \tabularnewline
40 & 0.047206 & 0.3271 & 0.372525 \tabularnewline
41 & 0.05395 & 0.3738 & 0.355108 \tabularnewline
42 & 0.003468 & 0.024 & 0.490465 \tabularnewline
43 & -0.013487 & -0.0934 & 0.46297 \tabularnewline
44 & -0.039114 & -0.271 & 0.393781 \tabularnewline
45 & -0.049133 & -0.3404 & 0.367519 \tabularnewline
46 & 0.00501 & 0.0347 & 0.486228 \tabularnewline
47 & 0.02158 & 0.1495 & 0.440889 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62876&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]0.496339[/C][C]3.4387[/C][C]0.000609[/C][/ROW]
[ROW][C]2[/C][C]-0.061079[/C][C]-0.4232[/C][C]0.337031[/C][/ROW]
[ROW][C]3[/C][C]-0.482081[/C][C]-3.34[/C][C]0.000814[/C][/ROW]
[ROW][C]4[/C][C]-0.45395[/C][C]-3.1451[/C][C]0.001424[/C][/ROW]
[ROW][C]5[/C][C]-0.122351[/C][C]-0.8477[/C][C]0.200414[/C][/ROW]
[ROW][C]6[/C][C]0.242197[/C][C]1.678[/C][C]0.049925[/C][/ROW]
[ROW][C]7[/C][C]0.295761[/C][C]2.0491[/C][C]0.02297[/C][/ROW]
[ROW][C]8[/C][C]0.141233[/C][C]0.9785[/C][C]0.166369[/C][/ROW]
[ROW][C]9[/C][C]-0.115029[/C][C]-0.7969[/C][C]0.214704[/C][/ROW]
[ROW][C]10[/C][C]-0.199037[/C][C]-1.379[/C][C]0.087149[/C][/ROW]
[ROW][C]11[/C][C]-0.125819[/C][C]-0.8717[/C][C]0.193856[/C][/ROW]
[ROW][C]12[/C][C]-0.06763[/C][C]-0.4686[/C][C]0.320754[/C][/ROW]
[ROW][C]13[/C][C]0.051252[/C][C]0.3551[/C][C]0.36204[/C][/ROW]
[ROW][C]14[/C][C]0.104817[/C][C]0.7262[/C][C]0.235623[/C][/ROW]
[ROW][C]15[/C][C]0.030636[/C][C]0.2123[/C][C]0.416405[/C][/ROW]
[ROW][C]16[/C][C]-0.125626[/C][C]-0.8704[/C][C]0.194217[/C][/ROW]
[ROW][C]17[/C][C]-0.184778[/C][C]-1.2802[/C][C]0.103317[/C][/ROW]
[ROW][C]18[/C][C]-0.06185[/C][C]-0.4285[/C][C]0.335099[/C][/ROW]
[ROW][C]19[/C][C]0.105588[/C][C]0.7315[/C][C]0.234005[/C][/ROW]
[ROW][C]20[/C][C]0.285164[/C][C]1.9757[/C][C]0.026978[/C][/ROW]
[ROW][C]21[/C][C]0.268208[/C][C]1.8582[/C][C]0.03464[/C][/ROW]
[ROW][C]22[/C][C]0.040848[/C][C]0.283[/C][C]0.389196[/C][/ROW]
[ROW][C]23[/C][C]-0.266281[/C][C]-1.8449[/C][C]0.035617[/C][/ROW]
[ROW][C]24[/C][C]-0.356647[/C][C]-2.4709[/C][C]0.008539[/C][/ROW]
[ROW][C]25[/C][C]-0.166089[/C][C]-1.1507[/C][C]0.127779[/C][/ROW]
[ROW][C]26[/C][C]0.073025[/C][C]0.5059[/C][C]0.30761[/C][/ROW]
[ROW][C]27[/C][C]0.17341[/C][C]1.2014[/C][C]0.117741[/C][/ROW]
[ROW][C]28[/C][C]0.125241[/C][C]0.8677[/C][C]0.19494[/C][/ROW]
[ROW][C]29[/C][C]0.010019[/C][C]0.0694[/C][C]0.472474[/C][/ROW]
[ROW][C]30[/C][C]-0.162428[/C][C]-1.1253[/C][C]0.133022[/C][/ROW]
[ROW][C]31[/C][C]-0.133141[/C][C]-0.9224[/C][C]0.18046[/C][/ROW]
[ROW][C]32[/C][C]-0.08131[/C][C]-0.5633[/C][C]0.287915[/C][/ROW]
[ROW][C]33[/C][C]0.015607[/C][C]0.1081[/C][C]0.457172[/C][/ROW]
[ROW][C]34[/C][C]0.012524[/C][C]0.0868[/C][C]0.465608[/C][/ROW]
[ROW][C]35[/C][C]0.057418[/C][C]0.3978[/C][C]0.346269[/C][/ROW]
[ROW][C]36[/C][C]0.04104[/C][C]0.2843[/C][C]0.388688[/C][/ROW]
[ROW][C]37[/C][C]0.019461[/C][C]0.1348[/C][C]0.446656[/C][/ROW]
[ROW][C]38[/C][C]0.014644[/C][C]0.1015[/C][C]0.459807[/C][/ROW]
[ROW][C]39[/C][C]0.031214[/C][C]0.2163[/C][C]0.414852[/C][/ROW]
[ROW][C]40[/C][C]0.047206[/C][C]0.3271[/C][C]0.372525[/C][/ROW]
[ROW][C]41[/C][C]0.05395[/C][C]0.3738[/C][C]0.355108[/C][/ROW]
[ROW][C]42[/C][C]0.003468[/C][C]0.024[/C][C]0.490465[/C][/ROW]
[ROW][C]43[/C][C]-0.013487[/C][C]-0.0934[/C][C]0.46297[/C][/ROW]
[ROW][C]44[/C][C]-0.039114[/C][C]-0.271[/C][C]0.393781[/C][/ROW]
[ROW][C]45[/C][C]-0.049133[/C][C]-0.3404[/C][C]0.367519[/C][/ROW]
[ROW][C]46[/C][C]0.00501[/C][C]0.0347[/C][C]0.486228[/C][/ROW]
[ROW][C]47[/C][C]0.02158[/C][C]0.1495[/C][C]0.440889[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62876&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62876&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
10.4963393.43870.000609
2-0.061079-0.42320.337031
3-0.482081-3.340.000814
4-0.45395-3.14510.001424
5-0.122351-0.84770.200414
60.2421971.6780.049925
70.2957612.04910.02297
80.1412330.97850.166369
9-0.115029-0.79690.214704
10-0.199037-1.3790.087149
11-0.125819-0.87170.193856
12-0.06763-0.46860.320754
130.0512520.35510.36204
140.1048170.72620.235623
150.0306360.21230.416405
16-0.125626-0.87040.194217
17-0.184778-1.28020.103317
18-0.06185-0.42850.335099
190.1055880.73150.234005
200.2851641.97570.026978
210.2682081.85820.03464
220.0408480.2830.389196
23-0.266281-1.84490.035617
24-0.356647-2.47090.008539
25-0.166089-1.15070.127779
260.0730250.50590.30761
270.173411.20140.117741
280.1252410.86770.19494
290.0100190.06940.472474
30-0.162428-1.12530.133022
31-0.133141-0.92240.18046
32-0.08131-0.56330.287915
330.0156070.10810.457172
340.0125240.08680.465608
350.0574180.39780.346269
360.041040.28430.388688
370.0194610.13480.446656
380.0146440.10150.459807
390.0312140.21630.414852
400.0472060.32710.372525
410.053950.37380.355108
420.0034680.0240.490465
43-0.013487-0.09340.46297
44-0.039114-0.2710.393781
45-0.049133-0.34040.367519
460.005010.03470.486228
470.021580.14950.440889
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4963393.43870.000609
2-0.407925-2.82620.003423
3-0.377133-2.61290.005977
4-0.023873-0.16540.434662
50.0729580.50550.307772
60.0794130.55020.292371
7-0.109396-0.75790.226102
8-0.001945-0.01350.494652
9-0.038959-0.26990.394191
100.0413060.28620.387987
11-0.007024-0.04870.480693
12-0.205495-1.42370.080499
130.0731210.50660.307379
140.0532530.36890.356895
15-0.130767-0.9060.184737
16-0.218064-1.51080.068699
17-0.031353-0.21720.414478
180.1767531.22460.113355
19-0.016649-0.11530.454326
200.122660.84980.199824
210.0482110.3340.36991
22-0.021997-0.15240.439756
23-0.106424-0.73730.232257
24-0.080991-0.56110.288663
250.0557310.38610.350558
26-0.131152-0.90860.184037
27-0.141471-0.98010.165965
28-0.062694-0.43440.332989
290.0773810.53610.29718
30-0.123762-0.85740.197729
31-0.022583-0.15650.438163
32-0.089394-0.61930.269312
330.0091910.06370.474746
34-0.070935-0.49150.312673
350.0026230.01820.492789
36-0.047172-0.32680.372612
370.0065470.04540.482006
380.0887710.6150.270723
39-0.108011-0.74830.228959
40-0.061538-0.42630.335881
410.0765070.53010.299258
42-0.053501-0.37070.35626
430.0305250.21150.416703
440.0102840.07120.471747
450.0157240.10890.456854
46-0.049221-0.3410.367292
47-0.084922-0.58840.279525
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.496339 & 3.4387 & 0.000609 \tabularnewline
2 & -0.407925 & -2.8262 & 0.003423 \tabularnewline
3 & -0.377133 & -2.6129 & 0.005977 \tabularnewline
4 & -0.023873 & -0.1654 & 0.434662 \tabularnewline
5 & 0.072958 & 0.5055 & 0.307772 \tabularnewline
6 & 0.079413 & 0.5502 & 0.292371 \tabularnewline
7 & -0.109396 & -0.7579 & 0.226102 \tabularnewline
8 & -0.001945 & -0.0135 & 0.494652 \tabularnewline
9 & -0.038959 & -0.2699 & 0.394191 \tabularnewline
10 & 0.041306 & 0.2862 & 0.387987 \tabularnewline
11 & -0.007024 & -0.0487 & 0.480693 \tabularnewline
12 & -0.205495 & -1.4237 & 0.080499 \tabularnewline
13 & 0.073121 & 0.5066 & 0.307379 \tabularnewline
14 & 0.053253 & 0.3689 & 0.356895 \tabularnewline
15 & -0.130767 & -0.906 & 0.184737 \tabularnewline
16 & -0.218064 & -1.5108 & 0.068699 \tabularnewline
17 & -0.031353 & -0.2172 & 0.414478 \tabularnewline
18 & 0.176753 & 1.2246 & 0.113355 \tabularnewline
19 & -0.016649 & -0.1153 & 0.454326 \tabularnewline
20 & 0.12266 & 0.8498 & 0.199824 \tabularnewline
21 & 0.048211 & 0.334 & 0.36991 \tabularnewline
22 & -0.021997 & -0.1524 & 0.439756 \tabularnewline
23 & -0.106424 & -0.7373 & 0.232257 \tabularnewline
24 & -0.080991 & -0.5611 & 0.288663 \tabularnewline
25 & 0.055731 & 0.3861 & 0.350558 \tabularnewline
26 & -0.131152 & -0.9086 & 0.184037 \tabularnewline
27 & -0.141471 & -0.9801 & 0.165965 \tabularnewline
28 & -0.062694 & -0.4344 & 0.332989 \tabularnewline
29 & 0.077381 & 0.5361 & 0.29718 \tabularnewline
30 & -0.123762 & -0.8574 & 0.197729 \tabularnewline
31 & -0.022583 & -0.1565 & 0.438163 \tabularnewline
32 & -0.089394 & -0.6193 & 0.269312 \tabularnewline
33 & 0.009191 & 0.0637 & 0.474746 \tabularnewline
34 & -0.070935 & -0.4915 & 0.312673 \tabularnewline
35 & 0.002623 & 0.0182 & 0.492789 \tabularnewline
36 & -0.047172 & -0.3268 & 0.372612 \tabularnewline
37 & 0.006547 & 0.0454 & 0.482006 \tabularnewline
38 & 0.088771 & 0.615 & 0.270723 \tabularnewline
39 & -0.108011 & -0.7483 & 0.228959 \tabularnewline
40 & -0.061538 & -0.4263 & 0.335881 \tabularnewline
41 & 0.076507 & 0.5301 & 0.299258 \tabularnewline
42 & -0.053501 & -0.3707 & 0.35626 \tabularnewline
43 & 0.030525 & 0.2115 & 0.416703 \tabularnewline
44 & 0.010284 & 0.0712 & 0.471747 \tabularnewline
45 & 0.015724 & 0.1089 & 0.456854 \tabularnewline
46 & -0.049221 & -0.341 & 0.367292 \tabularnewline
47 & -0.084922 & -0.5884 & 0.279525 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62876&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]0.496339[/C][C]3.4387[/C][C]0.000609[/C][/ROW]
[ROW][C]2[/C][C]-0.407925[/C][C]-2.8262[/C][C]0.003423[/C][/ROW]
[ROW][C]3[/C][C]-0.377133[/C][C]-2.6129[/C][C]0.005977[/C][/ROW]
[ROW][C]4[/C][C]-0.023873[/C][C]-0.1654[/C][C]0.434662[/C][/ROW]
[ROW][C]5[/C][C]0.072958[/C][C]0.5055[/C][C]0.307772[/C][/ROW]
[ROW][C]6[/C][C]0.079413[/C][C]0.5502[/C][C]0.292371[/C][/ROW]
[ROW][C]7[/C][C]-0.109396[/C][C]-0.7579[/C][C]0.226102[/C][/ROW]
[ROW][C]8[/C][C]-0.001945[/C][C]-0.0135[/C][C]0.494652[/C][/ROW]
[ROW][C]9[/C][C]-0.038959[/C][C]-0.2699[/C][C]0.394191[/C][/ROW]
[ROW][C]10[/C][C]0.041306[/C][C]0.2862[/C][C]0.387987[/C][/ROW]
[ROW][C]11[/C][C]-0.007024[/C][C]-0.0487[/C][C]0.480693[/C][/ROW]
[ROW][C]12[/C][C]-0.205495[/C][C]-1.4237[/C][C]0.080499[/C][/ROW]
[ROW][C]13[/C][C]0.073121[/C][C]0.5066[/C][C]0.307379[/C][/ROW]
[ROW][C]14[/C][C]0.053253[/C][C]0.3689[/C][C]0.356895[/C][/ROW]
[ROW][C]15[/C][C]-0.130767[/C][C]-0.906[/C][C]0.184737[/C][/ROW]
[ROW][C]16[/C][C]-0.218064[/C][C]-1.5108[/C][C]0.068699[/C][/ROW]
[ROW][C]17[/C][C]-0.031353[/C][C]-0.2172[/C][C]0.414478[/C][/ROW]
[ROW][C]18[/C][C]0.176753[/C][C]1.2246[/C][C]0.113355[/C][/ROW]
[ROW][C]19[/C][C]-0.016649[/C][C]-0.1153[/C][C]0.454326[/C][/ROW]
[ROW][C]20[/C][C]0.12266[/C][C]0.8498[/C][C]0.199824[/C][/ROW]
[ROW][C]21[/C][C]0.048211[/C][C]0.334[/C][C]0.36991[/C][/ROW]
[ROW][C]22[/C][C]-0.021997[/C][C]-0.1524[/C][C]0.439756[/C][/ROW]
[ROW][C]23[/C][C]-0.106424[/C][C]-0.7373[/C][C]0.232257[/C][/ROW]
[ROW][C]24[/C][C]-0.080991[/C][C]-0.5611[/C][C]0.288663[/C][/ROW]
[ROW][C]25[/C][C]0.055731[/C][C]0.3861[/C][C]0.350558[/C][/ROW]
[ROW][C]26[/C][C]-0.131152[/C][C]-0.9086[/C][C]0.184037[/C][/ROW]
[ROW][C]27[/C][C]-0.141471[/C][C]-0.9801[/C][C]0.165965[/C][/ROW]
[ROW][C]28[/C][C]-0.062694[/C][C]-0.4344[/C][C]0.332989[/C][/ROW]
[ROW][C]29[/C][C]0.077381[/C][C]0.5361[/C][C]0.29718[/C][/ROW]
[ROW][C]30[/C][C]-0.123762[/C][C]-0.8574[/C][C]0.197729[/C][/ROW]
[ROW][C]31[/C][C]-0.022583[/C][C]-0.1565[/C][C]0.438163[/C][/ROW]
[ROW][C]32[/C][C]-0.089394[/C][C]-0.6193[/C][C]0.269312[/C][/ROW]
[ROW][C]33[/C][C]0.009191[/C][C]0.0637[/C][C]0.474746[/C][/ROW]
[ROW][C]34[/C][C]-0.070935[/C][C]-0.4915[/C][C]0.312673[/C][/ROW]
[ROW][C]35[/C][C]0.002623[/C][C]0.0182[/C][C]0.492789[/C][/ROW]
[ROW][C]36[/C][C]-0.047172[/C][C]-0.3268[/C][C]0.372612[/C][/ROW]
[ROW][C]37[/C][C]0.006547[/C][C]0.0454[/C][C]0.482006[/C][/ROW]
[ROW][C]38[/C][C]0.088771[/C][C]0.615[/C][C]0.270723[/C][/ROW]
[ROW][C]39[/C][C]-0.108011[/C][C]-0.7483[/C][C]0.228959[/C][/ROW]
[ROW][C]40[/C][C]-0.061538[/C][C]-0.4263[/C][C]0.335881[/C][/ROW]
[ROW][C]41[/C][C]0.076507[/C][C]0.5301[/C][C]0.299258[/C][/ROW]
[ROW][C]42[/C][C]-0.053501[/C][C]-0.3707[/C][C]0.35626[/C][/ROW]
[ROW][C]43[/C][C]0.030525[/C][C]0.2115[/C][C]0.416703[/C][/ROW]
[ROW][C]44[/C][C]0.010284[/C][C]0.0712[/C][C]0.471747[/C][/ROW]
[ROW][C]45[/C][C]0.015724[/C][C]0.1089[/C][C]0.456854[/C][/ROW]
[ROW][C]46[/C][C]-0.049221[/C][C]-0.341[/C][C]0.367292[/C][/ROW]
[ROW][C]47[/C][C]-0.084922[/C][C]-0.5884[/C][C]0.279525[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62876&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62876&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
10.4963393.43870.000609
2-0.407925-2.82620.003423
3-0.377133-2.61290.005977
4-0.023873-0.16540.434662
50.0729580.50550.307772
60.0794130.55020.292371
7-0.109396-0.75790.226102
8-0.001945-0.01350.494652
9-0.038959-0.26990.394191
100.0413060.28620.387987
11-0.007024-0.04870.480693
12-0.205495-1.42370.080499
130.0731210.50660.307379
140.0532530.36890.356895
15-0.130767-0.9060.184737
16-0.218064-1.51080.068699
17-0.031353-0.21720.414478
180.1767531.22460.113355
19-0.016649-0.11530.454326
200.122660.84980.199824
210.0482110.3340.36991
22-0.021997-0.15240.439756
23-0.106424-0.73730.232257
24-0.080991-0.56110.288663
250.0557310.38610.350558
26-0.131152-0.90860.184037
27-0.141471-0.98010.165965
28-0.062694-0.43440.332989
290.0773810.53610.29718
30-0.123762-0.85740.197729
31-0.022583-0.15650.438163
32-0.089394-0.61930.269312
330.0091910.06370.474746
34-0.070935-0.49150.312673
350.0026230.01820.492789
36-0.047172-0.32680.372612
370.0065470.04540.482006
380.0887710.6150.270723
39-0.108011-0.74830.228959
40-0.061538-0.42630.335881
410.0765070.53010.299258
42-0.053501-0.37070.35626
430.0305250.21150.416703
440.0102840.07120.471747
450.0157240.10890.456854
46-0.049221-0.3410.367292
47-0.084922-0.58840.279525
48NANANA



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')