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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 computationWed, 29 Dec 2010 12:51:59 +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/29/t1293626995uwhqikzhqnykisq.htm/, Retrieved Fri, 03 May 2024 14:43:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116770, Retrieved Fri, 03 May 2024 14:43:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137
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 09:13:00] [b98453cac15ba1066b407e146608df68]
- R PD    [(Partial) Autocorrelation Function] [ACF 1,0,0] [2010-12-29 12:46:40] [a7c91bc614e4e21e8b9c8593f39a36f1]
-   P         [(Partial) Autocorrelation Function] [ACF 1,0,1] [2010-12-29 12:51:59] [062de5fc17e30860c0960288bdb996a8] [Current]
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Dataseries X:
621
587
655
517
646
657
382
345
625
654
606
510
614
647
580
614
636
388
356
639
753
611
639
630
586
695
552
619
681
421
307
754
690
644
643
608
651
691
627
634
731
475
337
803
722
590
724
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
706
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858
775
785
1006
789
734
906
532
387
991
841
892
782
813
793
978
775
797
946
594
438
1022
868
795




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=116770&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=116770&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116770&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
10.1452631.5780.058626
20.008960.09730.461315
30.1706571.85380.033132
40.0428170.46510.321356
50.0621180.67480.250568
60.1345071.46110.07332
70.0676070.73440.232081
80.2832853.07730.001299
90.1455911.58150.058217
100.0563890.61250.27068
110.1013261.10070.136639
12-0.137321-1.49170.069225
13-0.070588-0.76680.222373
140.0410130.44550.328381
150.0679280.73790.231024
160.0519620.56450.286759
170.0711560.77290.220549
180.0441040.47910.316379
19-0.059333-0.64450.260243
20-0.064991-0.7060.240796
21-0.034288-0.37250.355109
22-0.130718-1.420.079128
23-0.048146-0.5230.300978
24-0.120247-1.30620.097011
25-0.0368-0.39970.345032
26-0.067347-0.73160.23294
27-0.143162-1.55510.061296
28-0.021299-0.23140.408715
29-0.072092-0.78310.217564
30-0.166508-1.80870.036519
31-0.078442-0.85210.197943
32-0.168006-1.8250.035265
33-0.16096-1.74850.041491
34-0.053609-0.58230.280724
35-0.068565-0.74480.228935
360.0071970.07820.46891
37-0.032565-0.35370.36208
38-0.128174-1.39230.08322
39-0.066969-0.72750.234188
40-0.12762-1.38630.084134
41-0.078359-0.85120.198192
42-0.036429-0.39570.346512
430.0059660.06480.474218
440.0977681.0620.145196
450.0056670.06160.47551
46-0.016697-0.18140.42819
47-0.097212-1.0560.146565
48-0.114156-1.24010.108708

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.145263 & 1.578 & 0.058626 \tabularnewline
2 & 0.00896 & 0.0973 & 0.461315 \tabularnewline
3 & 0.170657 & 1.8538 & 0.033132 \tabularnewline
4 & 0.042817 & 0.4651 & 0.321356 \tabularnewline
5 & 0.062118 & 0.6748 & 0.250568 \tabularnewline
6 & 0.134507 & 1.4611 & 0.07332 \tabularnewline
7 & 0.067607 & 0.7344 & 0.232081 \tabularnewline
8 & 0.283285 & 3.0773 & 0.001299 \tabularnewline
9 & 0.145591 & 1.5815 & 0.058217 \tabularnewline
10 & 0.056389 & 0.6125 & 0.27068 \tabularnewline
11 & 0.101326 & 1.1007 & 0.136639 \tabularnewline
12 & -0.137321 & -1.4917 & 0.069225 \tabularnewline
13 & -0.070588 & -0.7668 & 0.222373 \tabularnewline
14 & 0.041013 & 0.4455 & 0.328381 \tabularnewline
15 & 0.067928 & 0.7379 & 0.231024 \tabularnewline
16 & 0.051962 & 0.5645 & 0.286759 \tabularnewline
17 & 0.071156 & 0.7729 & 0.220549 \tabularnewline
18 & 0.044104 & 0.4791 & 0.316379 \tabularnewline
19 & -0.059333 & -0.6445 & 0.260243 \tabularnewline
20 & -0.064991 & -0.706 & 0.240796 \tabularnewline
21 & -0.034288 & -0.3725 & 0.355109 \tabularnewline
22 & -0.130718 & -1.42 & 0.079128 \tabularnewline
23 & -0.048146 & -0.523 & 0.300978 \tabularnewline
24 & -0.120247 & -1.3062 & 0.097011 \tabularnewline
25 & -0.0368 & -0.3997 & 0.345032 \tabularnewline
26 & -0.067347 & -0.7316 & 0.23294 \tabularnewline
27 & -0.143162 & -1.5551 & 0.061296 \tabularnewline
28 & -0.021299 & -0.2314 & 0.408715 \tabularnewline
29 & -0.072092 & -0.7831 & 0.217564 \tabularnewline
30 & -0.166508 & -1.8087 & 0.036519 \tabularnewline
31 & -0.078442 & -0.8521 & 0.197943 \tabularnewline
32 & -0.168006 & -1.825 & 0.035265 \tabularnewline
33 & -0.16096 & -1.7485 & 0.041491 \tabularnewline
34 & -0.053609 & -0.5823 & 0.280724 \tabularnewline
35 & -0.068565 & -0.7448 & 0.228935 \tabularnewline
36 & 0.007197 & 0.0782 & 0.46891 \tabularnewline
37 & -0.032565 & -0.3537 & 0.36208 \tabularnewline
38 & -0.128174 & -1.3923 & 0.08322 \tabularnewline
39 & -0.066969 & -0.7275 & 0.234188 \tabularnewline
40 & -0.12762 & -1.3863 & 0.084134 \tabularnewline
41 & -0.078359 & -0.8512 & 0.198192 \tabularnewline
42 & -0.036429 & -0.3957 & 0.346512 \tabularnewline
43 & 0.005966 & 0.0648 & 0.474218 \tabularnewline
44 & 0.097768 & 1.062 & 0.145196 \tabularnewline
45 & 0.005667 & 0.0616 & 0.47551 \tabularnewline
46 & -0.016697 & -0.1814 & 0.42819 \tabularnewline
47 & -0.097212 & -1.056 & 0.146565 \tabularnewline
48 & -0.114156 & -1.2401 & 0.108708 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116770&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]0.145263[/C][C]1.578[/C][C]0.058626[/C][/ROW]
[ROW][C]2[/C][C]0.00896[/C][C]0.0973[/C][C]0.461315[/C][/ROW]
[ROW][C]3[/C][C]0.170657[/C][C]1.8538[/C][C]0.033132[/C][/ROW]
[ROW][C]4[/C][C]0.042817[/C][C]0.4651[/C][C]0.321356[/C][/ROW]
[ROW][C]5[/C][C]0.062118[/C][C]0.6748[/C][C]0.250568[/C][/ROW]
[ROW][C]6[/C][C]0.134507[/C][C]1.4611[/C][C]0.07332[/C][/ROW]
[ROW][C]7[/C][C]0.067607[/C][C]0.7344[/C][C]0.232081[/C][/ROW]
[ROW][C]8[/C][C]0.283285[/C][C]3.0773[/C][C]0.001299[/C][/ROW]
[ROW][C]9[/C][C]0.145591[/C][C]1.5815[/C][C]0.058217[/C][/ROW]
[ROW][C]10[/C][C]0.056389[/C][C]0.6125[/C][C]0.27068[/C][/ROW]
[ROW][C]11[/C][C]0.101326[/C][C]1.1007[/C][C]0.136639[/C][/ROW]
[ROW][C]12[/C][C]-0.137321[/C][C]-1.4917[/C][C]0.069225[/C][/ROW]
[ROW][C]13[/C][C]-0.070588[/C][C]-0.7668[/C][C]0.222373[/C][/ROW]
[ROW][C]14[/C][C]0.041013[/C][C]0.4455[/C][C]0.328381[/C][/ROW]
[ROW][C]15[/C][C]0.067928[/C][C]0.7379[/C][C]0.231024[/C][/ROW]
[ROW][C]16[/C][C]0.051962[/C][C]0.5645[/C][C]0.286759[/C][/ROW]
[ROW][C]17[/C][C]0.071156[/C][C]0.7729[/C][C]0.220549[/C][/ROW]
[ROW][C]18[/C][C]0.044104[/C][C]0.4791[/C][C]0.316379[/C][/ROW]
[ROW][C]19[/C][C]-0.059333[/C][C]-0.6445[/C][C]0.260243[/C][/ROW]
[ROW][C]20[/C][C]-0.064991[/C][C]-0.706[/C][C]0.240796[/C][/ROW]
[ROW][C]21[/C][C]-0.034288[/C][C]-0.3725[/C][C]0.355109[/C][/ROW]
[ROW][C]22[/C][C]-0.130718[/C][C]-1.42[/C][C]0.079128[/C][/ROW]
[ROW][C]23[/C][C]-0.048146[/C][C]-0.523[/C][C]0.300978[/C][/ROW]
[ROW][C]24[/C][C]-0.120247[/C][C]-1.3062[/C][C]0.097011[/C][/ROW]
[ROW][C]25[/C][C]-0.0368[/C][C]-0.3997[/C][C]0.345032[/C][/ROW]
[ROW][C]26[/C][C]-0.067347[/C][C]-0.7316[/C][C]0.23294[/C][/ROW]
[ROW][C]27[/C][C]-0.143162[/C][C]-1.5551[/C][C]0.061296[/C][/ROW]
[ROW][C]28[/C][C]-0.021299[/C][C]-0.2314[/C][C]0.408715[/C][/ROW]
[ROW][C]29[/C][C]-0.072092[/C][C]-0.7831[/C][C]0.217564[/C][/ROW]
[ROW][C]30[/C][C]-0.166508[/C][C]-1.8087[/C][C]0.036519[/C][/ROW]
[ROW][C]31[/C][C]-0.078442[/C][C]-0.8521[/C][C]0.197943[/C][/ROW]
[ROW][C]32[/C][C]-0.168006[/C][C]-1.825[/C][C]0.035265[/C][/ROW]
[ROW][C]33[/C][C]-0.16096[/C][C]-1.7485[/C][C]0.041491[/C][/ROW]
[ROW][C]34[/C][C]-0.053609[/C][C]-0.5823[/C][C]0.280724[/C][/ROW]
[ROW][C]35[/C][C]-0.068565[/C][C]-0.7448[/C][C]0.228935[/C][/ROW]
[ROW][C]36[/C][C]0.007197[/C][C]0.0782[/C][C]0.46891[/C][/ROW]
[ROW][C]37[/C][C]-0.032565[/C][C]-0.3537[/C][C]0.36208[/C][/ROW]
[ROW][C]38[/C][C]-0.128174[/C][C]-1.3923[/C][C]0.08322[/C][/ROW]
[ROW][C]39[/C][C]-0.066969[/C][C]-0.7275[/C][C]0.234188[/C][/ROW]
[ROW][C]40[/C][C]-0.12762[/C][C]-1.3863[/C][C]0.084134[/C][/ROW]
[ROW][C]41[/C][C]-0.078359[/C][C]-0.8512[/C][C]0.198192[/C][/ROW]
[ROW][C]42[/C][C]-0.036429[/C][C]-0.3957[/C][C]0.346512[/C][/ROW]
[ROW][C]43[/C][C]0.005966[/C][C]0.0648[/C][C]0.474218[/C][/ROW]
[ROW][C]44[/C][C]0.097768[/C][C]1.062[/C][C]0.145196[/C][/ROW]
[ROW][C]45[/C][C]0.005667[/C][C]0.0616[/C][C]0.47551[/C][/ROW]
[ROW][C]46[/C][C]-0.016697[/C][C]-0.1814[/C][C]0.42819[/C][/ROW]
[ROW][C]47[/C][C]-0.097212[/C][C]-1.056[/C][C]0.146565[/C][/ROW]
[ROW][C]48[/C][C]-0.114156[/C][C]-1.2401[/C][C]0.108708[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116770&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116770&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
10.1452631.5780.058626
20.008960.09730.461315
30.1706571.85380.033132
40.0428170.46510.321356
50.0621180.67480.250568
60.1345071.46110.07332
70.0676070.73440.232081
80.2832853.07730.001299
90.1455911.58150.058217
100.0563890.61250.27068
110.1013261.10070.136639
12-0.137321-1.49170.069225
13-0.070588-0.76680.222373
140.0410130.44550.328381
150.0679280.73790.231024
160.0519620.56450.286759
170.0711560.77290.220549
180.0441040.47910.316379
19-0.059333-0.64450.260243
20-0.064991-0.7060.240796
21-0.034288-0.37250.355109
22-0.130718-1.420.079128
23-0.048146-0.5230.300978
24-0.120247-1.30620.097011
25-0.0368-0.39970.345032
26-0.067347-0.73160.23294
27-0.143162-1.55510.061296
28-0.021299-0.23140.408715
29-0.072092-0.78310.217564
30-0.166508-1.80870.036519
31-0.078442-0.85210.197943
32-0.168006-1.8250.035265
33-0.16096-1.74850.041491
34-0.053609-0.58230.280724
35-0.068565-0.74480.228935
360.0071970.07820.46891
37-0.032565-0.35370.36208
38-0.128174-1.39230.08322
39-0.066969-0.72750.234188
40-0.12762-1.38630.084134
41-0.078359-0.85120.198192
42-0.036429-0.39570.346512
430.0059660.06480.474218
440.0977681.0620.145196
450.0056670.06160.47551
46-0.016697-0.18140.42819
47-0.097212-1.0560.146565
48-0.114156-1.24010.108708







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1452631.5780.058626
2-0.012403-0.13470.446526
30.1748581.89940.029974
4-0.008126-0.08830.464905
50.0651680.70790.2402
60.0925891.00580.158291
70.0347070.3770.353421
80.2739582.97590.001772
90.0423310.45980.323242
100.0450310.48920.312819
110.0088630.09630.461731
12-0.223291-2.42560.0084
13-0.074876-0.81340.208825
14-0.062592-0.67990.248944
150.0816360.88680.188496
16-0.025116-0.27280.392731
170.0310840.33770.368111
180.0388240.42170.336993
19-0.105921-1.15060.126112
200.037370.40590.342759
21-0.001795-0.01950.492239
22-0.108314-1.17660.120863
23-0.028545-0.31010.378523
24-0.222332-2.41510.008632
25-0.007246-0.07870.468697
26-0.138999-1.50990.066868
27-0.028389-0.30840.379168
280.1084161.17770.120642
29-0.035581-0.38650.349906
300.0489810.53210.297838
31-0.061011-0.66270.254393
32-0.088206-0.95820.169969
33-0.060751-0.65990.255294
34-0.057124-0.62050.268053
350.071350.77510.219927
36-0.001024-0.01110.495572
370.0462160.5020.30829
38-0.05805-0.63060.264766
39-0.029877-0.32460.373048
400.0094050.10220.459399
410.0423150.45970.323305
420.0380830.41370.339926
430.0422630.45910.323504
440.0767010.83320.203211
45-0.055632-0.60430.273396
46-0.03525-0.38290.351238
47-0.105732-1.14850.126534
48-0.070356-0.76430.223118

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.145263 & 1.578 & 0.058626 \tabularnewline
2 & -0.012403 & -0.1347 & 0.446526 \tabularnewline
3 & 0.174858 & 1.8994 & 0.029974 \tabularnewline
4 & -0.008126 & -0.0883 & 0.464905 \tabularnewline
5 & 0.065168 & 0.7079 & 0.2402 \tabularnewline
6 & 0.092589 & 1.0058 & 0.158291 \tabularnewline
7 & 0.034707 & 0.377 & 0.353421 \tabularnewline
8 & 0.273958 & 2.9759 & 0.001772 \tabularnewline
9 & 0.042331 & 0.4598 & 0.323242 \tabularnewline
10 & 0.045031 & 0.4892 & 0.312819 \tabularnewline
11 & 0.008863 & 0.0963 & 0.461731 \tabularnewline
12 & -0.223291 & -2.4256 & 0.0084 \tabularnewline
13 & -0.074876 & -0.8134 & 0.208825 \tabularnewline
14 & -0.062592 & -0.6799 & 0.248944 \tabularnewline
15 & 0.081636 & 0.8868 & 0.188496 \tabularnewline
16 & -0.025116 & -0.2728 & 0.392731 \tabularnewline
17 & 0.031084 & 0.3377 & 0.368111 \tabularnewline
18 & 0.038824 & 0.4217 & 0.336993 \tabularnewline
19 & -0.105921 & -1.1506 & 0.126112 \tabularnewline
20 & 0.03737 & 0.4059 & 0.342759 \tabularnewline
21 & -0.001795 & -0.0195 & 0.492239 \tabularnewline
22 & -0.108314 & -1.1766 & 0.120863 \tabularnewline
23 & -0.028545 & -0.3101 & 0.378523 \tabularnewline
24 & -0.222332 & -2.4151 & 0.008632 \tabularnewline
25 & -0.007246 & -0.0787 & 0.468697 \tabularnewline
26 & -0.138999 & -1.5099 & 0.066868 \tabularnewline
27 & -0.028389 & -0.3084 & 0.379168 \tabularnewline
28 & 0.108416 & 1.1777 & 0.120642 \tabularnewline
29 & -0.035581 & -0.3865 & 0.349906 \tabularnewline
30 & 0.048981 & 0.5321 & 0.297838 \tabularnewline
31 & -0.061011 & -0.6627 & 0.254393 \tabularnewline
32 & -0.088206 & -0.9582 & 0.169969 \tabularnewline
33 & -0.060751 & -0.6599 & 0.255294 \tabularnewline
34 & -0.057124 & -0.6205 & 0.268053 \tabularnewline
35 & 0.07135 & 0.7751 & 0.219927 \tabularnewline
36 & -0.001024 & -0.0111 & 0.495572 \tabularnewline
37 & 0.046216 & 0.502 & 0.30829 \tabularnewline
38 & -0.05805 & -0.6306 & 0.264766 \tabularnewline
39 & -0.029877 & -0.3246 & 0.373048 \tabularnewline
40 & 0.009405 & 0.1022 & 0.459399 \tabularnewline
41 & 0.042315 & 0.4597 & 0.323305 \tabularnewline
42 & 0.038083 & 0.4137 & 0.339926 \tabularnewline
43 & 0.042263 & 0.4591 & 0.323504 \tabularnewline
44 & 0.076701 & 0.8332 & 0.203211 \tabularnewline
45 & -0.055632 & -0.6043 & 0.273396 \tabularnewline
46 & -0.03525 & -0.3829 & 0.351238 \tabularnewline
47 & -0.105732 & -1.1485 & 0.126534 \tabularnewline
48 & -0.070356 & -0.7643 & 0.223118 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116770&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]0.145263[/C][C]1.578[/C][C]0.058626[/C][/ROW]
[ROW][C]2[/C][C]-0.012403[/C][C]-0.1347[/C][C]0.446526[/C][/ROW]
[ROW][C]3[/C][C]0.174858[/C][C]1.8994[/C][C]0.029974[/C][/ROW]
[ROW][C]4[/C][C]-0.008126[/C][C]-0.0883[/C][C]0.464905[/C][/ROW]
[ROW][C]5[/C][C]0.065168[/C][C]0.7079[/C][C]0.2402[/C][/ROW]
[ROW][C]6[/C][C]0.092589[/C][C]1.0058[/C][C]0.158291[/C][/ROW]
[ROW][C]7[/C][C]0.034707[/C][C]0.377[/C][C]0.353421[/C][/ROW]
[ROW][C]8[/C][C]0.273958[/C][C]2.9759[/C][C]0.001772[/C][/ROW]
[ROW][C]9[/C][C]0.042331[/C][C]0.4598[/C][C]0.323242[/C][/ROW]
[ROW][C]10[/C][C]0.045031[/C][C]0.4892[/C][C]0.312819[/C][/ROW]
[ROW][C]11[/C][C]0.008863[/C][C]0.0963[/C][C]0.461731[/C][/ROW]
[ROW][C]12[/C][C]-0.223291[/C][C]-2.4256[/C][C]0.0084[/C][/ROW]
[ROW][C]13[/C][C]-0.074876[/C][C]-0.8134[/C][C]0.208825[/C][/ROW]
[ROW][C]14[/C][C]-0.062592[/C][C]-0.6799[/C][C]0.248944[/C][/ROW]
[ROW][C]15[/C][C]0.081636[/C][C]0.8868[/C][C]0.188496[/C][/ROW]
[ROW][C]16[/C][C]-0.025116[/C][C]-0.2728[/C][C]0.392731[/C][/ROW]
[ROW][C]17[/C][C]0.031084[/C][C]0.3377[/C][C]0.368111[/C][/ROW]
[ROW][C]18[/C][C]0.038824[/C][C]0.4217[/C][C]0.336993[/C][/ROW]
[ROW][C]19[/C][C]-0.105921[/C][C]-1.1506[/C][C]0.126112[/C][/ROW]
[ROW][C]20[/C][C]0.03737[/C][C]0.4059[/C][C]0.342759[/C][/ROW]
[ROW][C]21[/C][C]-0.001795[/C][C]-0.0195[/C][C]0.492239[/C][/ROW]
[ROW][C]22[/C][C]-0.108314[/C][C]-1.1766[/C][C]0.120863[/C][/ROW]
[ROW][C]23[/C][C]-0.028545[/C][C]-0.3101[/C][C]0.378523[/C][/ROW]
[ROW][C]24[/C][C]-0.222332[/C][C]-2.4151[/C][C]0.008632[/C][/ROW]
[ROW][C]25[/C][C]-0.007246[/C][C]-0.0787[/C][C]0.468697[/C][/ROW]
[ROW][C]26[/C][C]-0.138999[/C][C]-1.5099[/C][C]0.066868[/C][/ROW]
[ROW][C]27[/C][C]-0.028389[/C][C]-0.3084[/C][C]0.379168[/C][/ROW]
[ROW][C]28[/C][C]0.108416[/C][C]1.1777[/C][C]0.120642[/C][/ROW]
[ROW][C]29[/C][C]-0.035581[/C][C]-0.3865[/C][C]0.349906[/C][/ROW]
[ROW][C]30[/C][C]0.048981[/C][C]0.5321[/C][C]0.297838[/C][/ROW]
[ROW][C]31[/C][C]-0.061011[/C][C]-0.6627[/C][C]0.254393[/C][/ROW]
[ROW][C]32[/C][C]-0.088206[/C][C]-0.9582[/C][C]0.169969[/C][/ROW]
[ROW][C]33[/C][C]-0.060751[/C][C]-0.6599[/C][C]0.255294[/C][/ROW]
[ROW][C]34[/C][C]-0.057124[/C][C]-0.6205[/C][C]0.268053[/C][/ROW]
[ROW][C]35[/C][C]0.07135[/C][C]0.7751[/C][C]0.219927[/C][/ROW]
[ROW][C]36[/C][C]-0.001024[/C][C]-0.0111[/C][C]0.495572[/C][/ROW]
[ROW][C]37[/C][C]0.046216[/C][C]0.502[/C][C]0.30829[/C][/ROW]
[ROW][C]38[/C][C]-0.05805[/C][C]-0.6306[/C][C]0.264766[/C][/ROW]
[ROW][C]39[/C][C]-0.029877[/C][C]-0.3246[/C][C]0.373048[/C][/ROW]
[ROW][C]40[/C][C]0.009405[/C][C]0.1022[/C][C]0.459399[/C][/ROW]
[ROW][C]41[/C][C]0.042315[/C][C]0.4597[/C][C]0.323305[/C][/ROW]
[ROW][C]42[/C][C]0.038083[/C][C]0.4137[/C][C]0.339926[/C][/ROW]
[ROW][C]43[/C][C]0.042263[/C][C]0.4591[/C][C]0.323504[/C][/ROW]
[ROW][C]44[/C][C]0.076701[/C][C]0.8332[/C][C]0.203211[/C][/ROW]
[ROW][C]45[/C][C]-0.055632[/C][C]-0.6043[/C][C]0.273396[/C][/ROW]
[ROW][C]46[/C][C]-0.03525[/C][C]-0.3829[/C][C]0.351238[/C][/ROW]
[ROW][C]47[/C][C]-0.105732[/C][C]-1.1485[/C][C]0.126534[/C][/ROW]
[ROW][C]48[/C][C]-0.070356[/C][C]-0.7643[/C][C]0.223118[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116770&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116770&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
10.1452631.5780.058626
2-0.012403-0.13470.446526
30.1748581.89940.029974
4-0.008126-0.08830.464905
50.0651680.70790.2402
60.0925891.00580.158291
70.0347070.3770.353421
80.2739582.97590.001772
90.0423310.45980.323242
100.0450310.48920.312819
110.0088630.09630.461731
12-0.223291-2.42560.0084
13-0.074876-0.81340.208825
14-0.062592-0.67990.248944
150.0816360.88680.188496
16-0.025116-0.27280.392731
170.0310840.33770.368111
180.0388240.42170.336993
19-0.105921-1.15060.126112
200.037370.40590.342759
21-0.001795-0.01950.492239
22-0.108314-1.17660.120863
23-0.028545-0.31010.378523
24-0.222332-2.41510.008632
25-0.007246-0.07870.468697
26-0.138999-1.50990.066868
27-0.028389-0.30840.379168
280.1084161.17770.120642
29-0.035581-0.38650.349906
300.0489810.53210.297838
31-0.061011-0.66270.254393
32-0.088206-0.95820.169969
33-0.060751-0.65990.255294
34-0.057124-0.62050.268053
350.071350.77510.219927
36-0.001024-0.01110.495572
370.0462160.5020.30829
38-0.05805-0.63060.264766
39-0.029877-0.32460.373048
400.0094050.10220.459399
410.0423150.45970.323305
420.0380830.41370.339926
430.0422630.45910.323504
440.0767010.83320.203211
45-0.055632-0.60430.273396
46-0.03525-0.38290.351238
47-0.105732-1.14850.126534
48-0.070356-0.76430.223118



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