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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, 07 Dec 2010 08:52:55 +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/07/t12917118655pe6at2kb59fdbo.htm/, Retrieved Sat, 04 May 2024 03:23:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106027, Retrieved Sat, 04 May 2024 03:23:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
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] [WS9 ACF 1] [2010-12-07 08:47:05] [07a238a5afc23eb944f8545182f29d5a]
-   P         [(Partial) Autocorrelation Function] [WS9 ACF 3 d=1 D=0...] [2010-12-07 08:52:55] [67e3c2d70de1dbb070b545ca6c893d5e] [Current]
-   P           [(Partial) Autocorrelation Function] [WS9 ACF 4 d=D=1 (...] [2010-12-07 08:56:39] [07a238a5afc23eb944f8545182f29d5a]
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Dataseries X:
562.325
560.854
555.332
543.599
536.662
542.722
593.530
610.763
612.613
611.324
594.167
595.454
590.865
589.379
584.428
573.100
567.456
569.028
620.735
628.884
628.232
612.117
595.404
597.141
593.408
590.072
579.799
574.205
572.775
572.942
619.567
625.809
619.916
587.625
565.742
557.274
560.576
548.854
531.673
525.919
511.038
498.662
555.362
564.591
541.657
527.070
509.846
514.258
516.922
507.561
492.622
490.243
469.357
477.580
528.379
533.590
517.945
506.174
501.866
516.141
528.222
532.638
536.322
536.535
523.597
536.214
586.570
596.594
580.523
564.478
557.560
575.093




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=106027&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=106027&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106027&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
10.2639142.22380.014673
2-0.236146-1.98980.025232
3-0.315846-2.66140.004809
4-0.217368-1.83160.035605
50.1023960.86280.195574
60.1916591.61490.055379
70.0628550.52960.299013
8-0.202068-1.70270.046503
9-0.260347-2.19370.015765
10-0.199096-1.67760.04891
110.2600952.19160.015845
120.7655046.45020
130.145531.22630.112077
14-0.240216-2.02410.023362
15-0.318194-2.68110.004558
16-0.20724-1.74620.042548
170.0814080.6860.247488
180.1388631.17010.122941
190.027370.23060.409135
20-0.203323-1.71320.045517
21-0.232131-1.9560.027202
22-0.141478-1.19210.118593
230.2193661.84840.034354
240.5608064.72546e-06
250.0667670.56260.287745
26-0.243896-2.05510.021775
27-0.292155-2.46170.008129
28-0.160424-1.35180.090372
290.0723210.60940.272107
300.0973960.82070.207291
310.0100930.0850.466232
32-0.186837-1.57430.05993
33-0.175985-1.48290.071266
34-0.082598-0.6960.244355
350.1632761.37580.086606
360.3998293.3690.000611
370.055190.4650.321664
38-0.187872-1.5830.058929
39-0.186523-1.57170.060237
40-0.084623-0.7130.239077
410.0765470.6450.260504
420.0702870.59220.277784
430.0039530.03330.486762
44-0.106841-0.90030.185513
45-0.086002-0.72470.235519
46-0.045524-0.38360.351214
470.1221151.0290.153496
480.2547752.14680.017614

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.263914 & 2.2238 & 0.014673 \tabularnewline
2 & -0.236146 & -1.9898 & 0.025232 \tabularnewline
3 & -0.315846 & -2.6614 & 0.004809 \tabularnewline
4 & -0.217368 & -1.8316 & 0.035605 \tabularnewline
5 & 0.102396 & 0.8628 & 0.195574 \tabularnewline
6 & 0.191659 & 1.6149 & 0.055379 \tabularnewline
7 & 0.062855 & 0.5296 & 0.299013 \tabularnewline
8 & -0.202068 & -1.7027 & 0.046503 \tabularnewline
9 & -0.260347 & -2.1937 & 0.015765 \tabularnewline
10 & -0.199096 & -1.6776 & 0.04891 \tabularnewline
11 & 0.260095 & 2.1916 & 0.015845 \tabularnewline
12 & 0.765504 & 6.4502 & 0 \tabularnewline
13 & 0.14553 & 1.2263 & 0.112077 \tabularnewline
14 & -0.240216 & -2.0241 & 0.023362 \tabularnewline
15 & -0.318194 & -2.6811 & 0.004558 \tabularnewline
16 & -0.20724 & -1.7462 & 0.042548 \tabularnewline
17 & 0.081408 & 0.686 & 0.247488 \tabularnewline
18 & 0.138863 & 1.1701 & 0.122941 \tabularnewline
19 & 0.02737 & 0.2306 & 0.409135 \tabularnewline
20 & -0.203323 & -1.7132 & 0.045517 \tabularnewline
21 & -0.232131 & -1.956 & 0.027202 \tabularnewline
22 & -0.141478 & -1.1921 & 0.118593 \tabularnewline
23 & 0.219366 & 1.8484 & 0.034354 \tabularnewline
24 & 0.560806 & 4.7254 & 6e-06 \tabularnewline
25 & 0.066767 & 0.5626 & 0.287745 \tabularnewline
26 & -0.243896 & -2.0551 & 0.021775 \tabularnewline
27 & -0.292155 & -2.4617 & 0.008129 \tabularnewline
28 & -0.160424 & -1.3518 & 0.090372 \tabularnewline
29 & 0.072321 & 0.6094 & 0.272107 \tabularnewline
30 & 0.097396 & 0.8207 & 0.207291 \tabularnewline
31 & 0.010093 & 0.085 & 0.466232 \tabularnewline
32 & -0.186837 & -1.5743 & 0.05993 \tabularnewline
33 & -0.175985 & -1.4829 & 0.071266 \tabularnewline
34 & -0.082598 & -0.696 & 0.244355 \tabularnewline
35 & 0.163276 & 1.3758 & 0.086606 \tabularnewline
36 & 0.399829 & 3.369 & 0.000611 \tabularnewline
37 & 0.05519 & 0.465 & 0.321664 \tabularnewline
38 & -0.187872 & -1.583 & 0.058929 \tabularnewline
39 & -0.186523 & -1.5717 & 0.060237 \tabularnewline
40 & -0.084623 & -0.713 & 0.239077 \tabularnewline
41 & 0.076547 & 0.645 & 0.260504 \tabularnewline
42 & 0.070287 & 0.5922 & 0.277784 \tabularnewline
43 & 0.003953 & 0.0333 & 0.486762 \tabularnewline
44 & -0.106841 & -0.9003 & 0.185513 \tabularnewline
45 & -0.086002 & -0.7247 & 0.235519 \tabularnewline
46 & -0.045524 & -0.3836 & 0.351214 \tabularnewline
47 & 0.122115 & 1.029 & 0.153496 \tabularnewline
48 & 0.254775 & 2.1468 & 0.017614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106027&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]0.263914[/C][C]2.2238[/C][C]0.014673[/C][/ROW]
[ROW][C]2[/C][C]-0.236146[/C][C]-1.9898[/C][C]0.025232[/C][/ROW]
[ROW][C]3[/C][C]-0.315846[/C][C]-2.6614[/C][C]0.004809[/C][/ROW]
[ROW][C]4[/C][C]-0.217368[/C][C]-1.8316[/C][C]0.035605[/C][/ROW]
[ROW][C]5[/C][C]0.102396[/C][C]0.8628[/C][C]0.195574[/C][/ROW]
[ROW][C]6[/C][C]0.191659[/C][C]1.6149[/C][C]0.055379[/C][/ROW]
[ROW][C]7[/C][C]0.062855[/C][C]0.5296[/C][C]0.299013[/C][/ROW]
[ROW][C]8[/C][C]-0.202068[/C][C]-1.7027[/C][C]0.046503[/C][/ROW]
[ROW][C]9[/C][C]-0.260347[/C][C]-2.1937[/C][C]0.015765[/C][/ROW]
[ROW][C]10[/C][C]-0.199096[/C][C]-1.6776[/C][C]0.04891[/C][/ROW]
[ROW][C]11[/C][C]0.260095[/C][C]2.1916[/C][C]0.015845[/C][/ROW]
[ROW][C]12[/C][C]0.765504[/C][C]6.4502[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.14553[/C][C]1.2263[/C][C]0.112077[/C][/ROW]
[ROW][C]14[/C][C]-0.240216[/C][C]-2.0241[/C][C]0.023362[/C][/ROW]
[ROW][C]15[/C][C]-0.318194[/C][C]-2.6811[/C][C]0.004558[/C][/ROW]
[ROW][C]16[/C][C]-0.20724[/C][C]-1.7462[/C][C]0.042548[/C][/ROW]
[ROW][C]17[/C][C]0.081408[/C][C]0.686[/C][C]0.247488[/C][/ROW]
[ROW][C]18[/C][C]0.138863[/C][C]1.1701[/C][C]0.122941[/C][/ROW]
[ROW][C]19[/C][C]0.02737[/C][C]0.2306[/C][C]0.409135[/C][/ROW]
[ROW][C]20[/C][C]-0.203323[/C][C]-1.7132[/C][C]0.045517[/C][/ROW]
[ROW][C]21[/C][C]-0.232131[/C][C]-1.956[/C][C]0.027202[/C][/ROW]
[ROW][C]22[/C][C]-0.141478[/C][C]-1.1921[/C][C]0.118593[/C][/ROW]
[ROW][C]23[/C][C]0.219366[/C][C]1.8484[/C][C]0.034354[/C][/ROW]
[ROW][C]24[/C][C]0.560806[/C][C]4.7254[/C][C]6e-06[/C][/ROW]
[ROW][C]25[/C][C]0.066767[/C][C]0.5626[/C][C]0.287745[/C][/ROW]
[ROW][C]26[/C][C]-0.243896[/C][C]-2.0551[/C][C]0.021775[/C][/ROW]
[ROW][C]27[/C][C]-0.292155[/C][C]-2.4617[/C][C]0.008129[/C][/ROW]
[ROW][C]28[/C][C]-0.160424[/C][C]-1.3518[/C][C]0.090372[/C][/ROW]
[ROW][C]29[/C][C]0.072321[/C][C]0.6094[/C][C]0.272107[/C][/ROW]
[ROW][C]30[/C][C]0.097396[/C][C]0.8207[/C][C]0.207291[/C][/ROW]
[ROW][C]31[/C][C]0.010093[/C][C]0.085[/C][C]0.466232[/C][/ROW]
[ROW][C]32[/C][C]-0.186837[/C][C]-1.5743[/C][C]0.05993[/C][/ROW]
[ROW][C]33[/C][C]-0.175985[/C][C]-1.4829[/C][C]0.071266[/C][/ROW]
[ROW][C]34[/C][C]-0.082598[/C][C]-0.696[/C][C]0.244355[/C][/ROW]
[ROW][C]35[/C][C]0.163276[/C][C]1.3758[/C][C]0.086606[/C][/ROW]
[ROW][C]36[/C][C]0.399829[/C][C]3.369[/C][C]0.000611[/C][/ROW]
[ROW][C]37[/C][C]0.05519[/C][C]0.465[/C][C]0.321664[/C][/ROW]
[ROW][C]38[/C][C]-0.187872[/C][C]-1.583[/C][C]0.058929[/C][/ROW]
[ROW][C]39[/C][C]-0.186523[/C][C]-1.5717[/C][C]0.060237[/C][/ROW]
[ROW][C]40[/C][C]-0.084623[/C][C]-0.713[/C][C]0.239077[/C][/ROW]
[ROW][C]41[/C][C]0.076547[/C][C]0.645[/C][C]0.260504[/C][/ROW]
[ROW][C]42[/C][C]0.070287[/C][C]0.5922[/C][C]0.277784[/C][/ROW]
[ROW][C]43[/C][C]0.003953[/C][C]0.0333[/C][C]0.486762[/C][/ROW]
[ROW][C]44[/C][C]-0.106841[/C][C]-0.9003[/C][C]0.185513[/C][/ROW]
[ROW][C]45[/C][C]-0.086002[/C][C]-0.7247[/C][C]0.235519[/C][/ROW]
[ROW][C]46[/C][C]-0.045524[/C][C]-0.3836[/C][C]0.351214[/C][/ROW]
[ROW][C]47[/C][C]0.122115[/C][C]1.029[/C][C]0.153496[/C][/ROW]
[ROW][C]48[/C][C]0.254775[/C][C]2.1468[/C][C]0.017614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106027&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106027&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
10.2639142.22380.014673
2-0.236146-1.98980.025232
3-0.315846-2.66140.004809
4-0.217368-1.83160.035605
50.1023960.86280.195574
60.1916591.61490.055379
70.0628550.52960.299013
8-0.202068-1.70270.046503
9-0.260347-2.19370.015765
10-0.199096-1.67760.04891
110.2600952.19160.015845
120.7655046.45020
130.145531.22630.112077
14-0.240216-2.02410.023362
15-0.318194-2.68110.004558
16-0.20724-1.74620.042548
170.0814080.6860.247488
180.1388631.17010.122941
190.027370.23060.409135
20-0.203323-1.71320.045517
21-0.232131-1.9560.027202
22-0.141478-1.19210.118593
230.2193661.84840.034354
240.5608064.72546e-06
250.0667670.56260.287745
26-0.243896-2.05510.021775
27-0.292155-2.46170.008129
28-0.160424-1.35180.090372
290.0723210.60940.272107
300.0973960.82070.207291
310.0100930.0850.466232
32-0.186837-1.57430.05993
33-0.175985-1.48290.071266
34-0.082598-0.6960.244355
350.1632761.37580.086606
360.3998293.3690.000611
370.055190.4650.321664
38-0.187872-1.5830.058929
39-0.186523-1.57170.060237
40-0.084623-0.7130.239077
410.0765470.6450.260504
420.0702870.59220.277784
430.0039530.03330.486762
44-0.106841-0.90030.185513
45-0.086002-0.72470.235519
46-0.045524-0.38360.351214
470.1221151.0290.153496
480.2547752.14680.017614







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2639142.22380.014673
2-0.32869-2.76960.003578
3-0.176292-1.48550.070924
4-0.175873-1.48190.071392
50.0989640.83390.203571
6-0.007551-0.06360.474722
7-0.024472-0.20620.41861
8-0.208616-1.75780.041543
9-0.116925-0.98520.163929
10-0.238901-2.0130.023953
110.268562.26290.01335
120.6411875.40270
13-0.236456-1.99240.025085
140.0798010.67240.251752
15-0.014459-0.12180.451688
16-0.046362-0.39060.348613
17-0.137458-1.15820.125324
18-0.073814-0.6220.267976
19-0.021468-0.18090.428484
20-0.123077-1.03710.151612
21-0.045585-0.38410.351025
220.0357640.30140.382012
23-0.14734-1.24150.109252
24-0.042942-0.36180.359276
25-0.014971-0.12610.449987
26-0.086246-0.72670.234893
27-0.026778-0.22560.411067
280.0042940.03620.48562
29-0.044182-0.37230.355395
30-0.079606-0.67080.252271
31-0.010282-0.08660.465603
32-0.030605-0.25790.398621
33-0.038134-0.32130.374455
34-0.04573-0.38530.350575
35-0.0989-0.83330.203722
36-0.079624-0.67090.252223
370.0518650.4370.331712
38-0.014431-0.12160.45178
390.0909230.76610.22307
40-0.00559-0.04710.481283
410.041440.34920.363994
42-0.047355-0.3990.345537
43-0.003426-0.02890.488524
440.1157230.97510.16641
45-0.025649-0.21610.414756
46-0.062565-0.52720.299854
470.0623330.52520.300531
48-0.151909-1.280.102355

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.263914 & 2.2238 & 0.014673 \tabularnewline
2 & -0.32869 & -2.7696 & 0.003578 \tabularnewline
3 & -0.176292 & -1.4855 & 0.070924 \tabularnewline
4 & -0.175873 & -1.4819 & 0.071392 \tabularnewline
5 & 0.098964 & 0.8339 & 0.203571 \tabularnewline
6 & -0.007551 & -0.0636 & 0.474722 \tabularnewline
7 & -0.024472 & -0.2062 & 0.41861 \tabularnewline
8 & -0.208616 & -1.7578 & 0.041543 \tabularnewline
9 & -0.116925 & -0.9852 & 0.163929 \tabularnewline
10 & -0.238901 & -2.013 & 0.023953 \tabularnewline
11 & 0.26856 & 2.2629 & 0.01335 \tabularnewline
12 & 0.641187 & 5.4027 & 0 \tabularnewline
13 & -0.236456 & -1.9924 & 0.025085 \tabularnewline
14 & 0.079801 & 0.6724 & 0.251752 \tabularnewline
15 & -0.014459 & -0.1218 & 0.451688 \tabularnewline
16 & -0.046362 & -0.3906 & 0.348613 \tabularnewline
17 & -0.137458 & -1.1582 & 0.125324 \tabularnewline
18 & -0.073814 & -0.622 & 0.267976 \tabularnewline
19 & -0.021468 & -0.1809 & 0.428484 \tabularnewline
20 & -0.123077 & -1.0371 & 0.151612 \tabularnewline
21 & -0.045585 & -0.3841 & 0.351025 \tabularnewline
22 & 0.035764 & 0.3014 & 0.382012 \tabularnewline
23 & -0.14734 & -1.2415 & 0.109252 \tabularnewline
24 & -0.042942 & -0.3618 & 0.359276 \tabularnewline
25 & -0.014971 & -0.1261 & 0.449987 \tabularnewline
26 & -0.086246 & -0.7267 & 0.234893 \tabularnewline
27 & -0.026778 & -0.2256 & 0.411067 \tabularnewline
28 & 0.004294 & 0.0362 & 0.48562 \tabularnewline
29 & -0.044182 & -0.3723 & 0.355395 \tabularnewline
30 & -0.079606 & -0.6708 & 0.252271 \tabularnewline
31 & -0.010282 & -0.0866 & 0.465603 \tabularnewline
32 & -0.030605 & -0.2579 & 0.398621 \tabularnewline
33 & -0.038134 & -0.3213 & 0.374455 \tabularnewline
34 & -0.04573 & -0.3853 & 0.350575 \tabularnewline
35 & -0.0989 & -0.8333 & 0.203722 \tabularnewline
36 & -0.079624 & -0.6709 & 0.252223 \tabularnewline
37 & 0.051865 & 0.437 & 0.331712 \tabularnewline
38 & -0.014431 & -0.1216 & 0.45178 \tabularnewline
39 & 0.090923 & 0.7661 & 0.22307 \tabularnewline
40 & -0.00559 & -0.0471 & 0.481283 \tabularnewline
41 & 0.04144 & 0.3492 & 0.363994 \tabularnewline
42 & -0.047355 & -0.399 & 0.345537 \tabularnewline
43 & -0.003426 & -0.0289 & 0.488524 \tabularnewline
44 & 0.115723 & 0.9751 & 0.16641 \tabularnewline
45 & -0.025649 & -0.2161 & 0.414756 \tabularnewline
46 & -0.062565 & -0.5272 & 0.299854 \tabularnewline
47 & 0.062333 & 0.5252 & 0.300531 \tabularnewline
48 & -0.151909 & -1.28 & 0.102355 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106027&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]0.263914[/C][C]2.2238[/C][C]0.014673[/C][/ROW]
[ROW][C]2[/C][C]-0.32869[/C][C]-2.7696[/C][C]0.003578[/C][/ROW]
[ROW][C]3[/C][C]-0.176292[/C][C]-1.4855[/C][C]0.070924[/C][/ROW]
[ROW][C]4[/C][C]-0.175873[/C][C]-1.4819[/C][C]0.071392[/C][/ROW]
[ROW][C]5[/C][C]0.098964[/C][C]0.8339[/C][C]0.203571[/C][/ROW]
[ROW][C]6[/C][C]-0.007551[/C][C]-0.0636[/C][C]0.474722[/C][/ROW]
[ROW][C]7[/C][C]-0.024472[/C][C]-0.2062[/C][C]0.41861[/C][/ROW]
[ROW][C]8[/C][C]-0.208616[/C][C]-1.7578[/C][C]0.041543[/C][/ROW]
[ROW][C]9[/C][C]-0.116925[/C][C]-0.9852[/C][C]0.163929[/C][/ROW]
[ROW][C]10[/C][C]-0.238901[/C][C]-2.013[/C][C]0.023953[/C][/ROW]
[ROW][C]11[/C][C]0.26856[/C][C]2.2629[/C][C]0.01335[/C][/ROW]
[ROW][C]12[/C][C]0.641187[/C][C]5.4027[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.236456[/C][C]-1.9924[/C][C]0.025085[/C][/ROW]
[ROW][C]14[/C][C]0.079801[/C][C]0.6724[/C][C]0.251752[/C][/ROW]
[ROW][C]15[/C][C]-0.014459[/C][C]-0.1218[/C][C]0.451688[/C][/ROW]
[ROW][C]16[/C][C]-0.046362[/C][C]-0.3906[/C][C]0.348613[/C][/ROW]
[ROW][C]17[/C][C]-0.137458[/C][C]-1.1582[/C][C]0.125324[/C][/ROW]
[ROW][C]18[/C][C]-0.073814[/C][C]-0.622[/C][C]0.267976[/C][/ROW]
[ROW][C]19[/C][C]-0.021468[/C][C]-0.1809[/C][C]0.428484[/C][/ROW]
[ROW][C]20[/C][C]-0.123077[/C][C]-1.0371[/C][C]0.151612[/C][/ROW]
[ROW][C]21[/C][C]-0.045585[/C][C]-0.3841[/C][C]0.351025[/C][/ROW]
[ROW][C]22[/C][C]0.035764[/C][C]0.3014[/C][C]0.382012[/C][/ROW]
[ROW][C]23[/C][C]-0.14734[/C][C]-1.2415[/C][C]0.109252[/C][/ROW]
[ROW][C]24[/C][C]-0.042942[/C][C]-0.3618[/C][C]0.359276[/C][/ROW]
[ROW][C]25[/C][C]-0.014971[/C][C]-0.1261[/C][C]0.449987[/C][/ROW]
[ROW][C]26[/C][C]-0.086246[/C][C]-0.7267[/C][C]0.234893[/C][/ROW]
[ROW][C]27[/C][C]-0.026778[/C][C]-0.2256[/C][C]0.411067[/C][/ROW]
[ROW][C]28[/C][C]0.004294[/C][C]0.0362[/C][C]0.48562[/C][/ROW]
[ROW][C]29[/C][C]-0.044182[/C][C]-0.3723[/C][C]0.355395[/C][/ROW]
[ROW][C]30[/C][C]-0.079606[/C][C]-0.6708[/C][C]0.252271[/C][/ROW]
[ROW][C]31[/C][C]-0.010282[/C][C]-0.0866[/C][C]0.465603[/C][/ROW]
[ROW][C]32[/C][C]-0.030605[/C][C]-0.2579[/C][C]0.398621[/C][/ROW]
[ROW][C]33[/C][C]-0.038134[/C][C]-0.3213[/C][C]0.374455[/C][/ROW]
[ROW][C]34[/C][C]-0.04573[/C][C]-0.3853[/C][C]0.350575[/C][/ROW]
[ROW][C]35[/C][C]-0.0989[/C][C]-0.8333[/C][C]0.203722[/C][/ROW]
[ROW][C]36[/C][C]-0.079624[/C][C]-0.6709[/C][C]0.252223[/C][/ROW]
[ROW][C]37[/C][C]0.051865[/C][C]0.437[/C][C]0.331712[/C][/ROW]
[ROW][C]38[/C][C]-0.014431[/C][C]-0.1216[/C][C]0.45178[/C][/ROW]
[ROW][C]39[/C][C]0.090923[/C][C]0.7661[/C][C]0.22307[/C][/ROW]
[ROW][C]40[/C][C]-0.00559[/C][C]-0.0471[/C][C]0.481283[/C][/ROW]
[ROW][C]41[/C][C]0.04144[/C][C]0.3492[/C][C]0.363994[/C][/ROW]
[ROW][C]42[/C][C]-0.047355[/C][C]-0.399[/C][C]0.345537[/C][/ROW]
[ROW][C]43[/C][C]-0.003426[/C][C]-0.0289[/C][C]0.488524[/C][/ROW]
[ROW][C]44[/C][C]0.115723[/C][C]0.9751[/C][C]0.16641[/C][/ROW]
[ROW][C]45[/C][C]-0.025649[/C][C]-0.2161[/C][C]0.414756[/C][/ROW]
[ROW][C]46[/C][C]-0.062565[/C][C]-0.5272[/C][C]0.299854[/C][/ROW]
[ROW][C]47[/C][C]0.062333[/C][C]0.5252[/C][C]0.300531[/C][/ROW]
[ROW][C]48[/C][C]-0.151909[/C][C]-1.28[/C][C]0.102355[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106027&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106027&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
10.2639142.22380.014673
2-0.32869-2.76960.003578
3-0.176292-1.48550.070924
4-0.175873-1.48190.071392
50.0989640.83390.203571
6-0.007551-0.06360.474722
7-0.024472-0.20620.41861
8-0.208616-1.75780.041543
9-0.116925-0.98520.163929
10-0.238901-2.0130.023953
110.268562.26290.01335
120.6411875.40270
13-0.236456-1.99240.025085
140.0798010.67240.251752
15-0.014459-0.12180.451688
16-0.046362-0.39060.348613
17-0.137458-1.15820.125324
18-0.073814-0.6220.267976
19-0.021468-0.18090.428484
20-0.123077-1.03710.151612
21-0.045585-0.38410.351025
220.0357640.30140.382012
23-0.14734-1.24150.109252
24-0.042942-0.36180.359276
25-0.014971-0.12610.449987
26-0.086246-0.72670.234893
27-0.026778-0.22560.411067
280.0042940.03620.48562
29-0.044182-0.37230.355395
30-0.079606-0.67080.252271
31-0.010282-0.08660.465603
32-0.030605-0.25790.398621
33-0.038134-0.32130.374455
34-0.04573-0.38530.350575
35-0.0989-0.83330.203722
36-0.079624-0.67090.252223
370.0518650.4370.331712
38-0.014431-0.12160.45178
390.0909230.76610.22307
40-0.00559-0.04710.481283
410.041440.34920.363994
42-0.047355-0.3990.345537
43-0.003426-0.02890.488524
440.1157230.97510.16641
45-0.025649-0.21610.414756
46-0.062565-0.52720.299854
470.0623330.52520.300531
48-0.151909-1.280.102355



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