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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, 16 Dec 2010 10:32:45 +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/16/t12924955054eagrigo5va9xng.htm/, Retrieved Fri, 03 May 2024 04:30:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110835, Retrieved Fri, 03 May 2024 04:30:45 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
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]
-   PD      [(Partial) Autocorrelation Function] [Aantal openstaand...] [2010-12-16 10:32:45] [f0b33ae54e73edcd25a3e2f31270d1c9] [Current]
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Dataseries X:
27.951
29.781
32.914
33.488
35.652
36.488
35.387
35.676
34.844
32.447
31.068
29.010
29.812
30.951
32.974
32.936
34.012
32.946
31.948
30.599
27.691
25.073
23.406
22.248
22.896
25.317
26.558
26.471
27.543
26.198
24.725
25.005
23.462
20.780
19.815
19.761
21.454
23.899
24.939
23.580
24.562
24.696
23.785
23.812
21.917
19.713
19.282
18.788
21.453
24.482
27.474
27.264
27.349
30.632
29.429
30.084
26.290
24.379
23.335
21.346
21.106
24.514
28.353
30.805
31.348
34.556
33.855
34.787
32.529
29.998
29.257
28.155
30.466
35.704
39.327
39.351
42.234
43.630
43.722
43.121
37.985
37.135
34.646
33.026
35.087
38.846
42.013
43.908
42.868
44.423
44.167
43.636
44.382
42.142
43.452
36.912
42.413
45.344
44.873
47.510
49.554
47.369
45.998
48.140
48.441
44.928
40.454
38.661
37.246
36.843
36.424
37.594
38.144
38.737
34.560
36.080
33.508
35.462
33.374
32.110
35.533
35.532
37.903
36.763
40.399
44.164
44.496
43.110
43.880
43.930
44.327




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=110835&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=110835&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110835&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
1-0.209778-2.27880.01224
20.1873972.03570.022012
30.0427310.46420.321687
40.1552671.68660.047158
50.0105910.1150.454301
6-0.010445-0.11350.454928
70.0640420.69570.244001
80.0740830.80470.211293
9-0.141825-1.54060.063044
100.0255320.27730.391
110.0855690.92950.177258
12-0.400937-4.35531.4e-05
130.243522.64530.004637
14-0.250189-2.71780.003782
150.0583090.63340.263849
16-0.216953-2.35670.010043
17-0.063648-0.69140.245339
180.0339030.36830.356663
19-0.030663-0.33310.369829
20-0.079811-0.8670.193858
210.1875242.0370.021942
22-0.151613-1.64690.051116
230.0791830.86010.195726
24-0.026099-0.28350.388642
25-0.068028-0.7390.230694
260.2073262.25210.013082
27-0.134602-1.46220.073178
280.1533911.66630.049158
29-0.041542-0.45130.326314
300.0277750.30170.3817
310.0184780.20070.420629
320.0008480.00920.496335
33-0.102036-1.10840.134972
340.0418290.45440.325196
35-0.115475-1.25440.106092
36-0.025375-0.27560.391654
37-0.03766-0.40910.341608
38-0.122046-1.32580.09374
390.1180861.28270.101049
40-0.144107-1.56540.060083
410.1129811.22730.111079
42-0.086236-0.93680.175396
43-0.052395-0.56920.285166
44-0.014902-0.16190.435838
45-0.044049-0.47850.316593
460.0090950.09880.460734
47-0.025743-0.27960.39012
48-0.028834-0.31320.377335

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.209778 & -2.2788 & 0.01224 \tabularnewline
2 & 0.187397 & 2.0357 & 0.022012 \tabularnewline
3 & 0.042731 & 0.4642 & 0.321687 \tabularnewline
4 & 0.155267 & 1.6866 & 0.047158 \tabularnewline
5 & 0.010591 & 0.115 & 0.454301 \tabularnewline
6 & -0.010445 & -0.1135 & 0.454928 \tabularnewline
7 & 0.064042 & 0.6957 & 0.244001 \tabularnewline
8 & 0.074083 & 0.8047 & 0.211293 \tabularnewline
9 & -0.141825 & -1.5406 & 0.063044 \tabularnewline
10 & 0.025532 & 0.2773 & 0.391 \tabularnewline
11 & 0.085569 & 0.9295 & 0.177258 \tabularnewline
12 & -0.400937 & -4.3553 & 1.4e-05 \tabularnewline
13 & 0.24352 & 2.6453 & 0.004637 \tabularnewline
14 & -0.250189 & -2.7178 & 0.003782 \tabularnewline
15 & 0.058309 & 0.6334 & 0.263849 \tabularnewline
16 & -0.216953 & -2.3567 & 0.010043 \tabularnewline
17 & -0.063648 & -0.6914 & 0.245339 \tabularnewline
18 & 0.033903 & 0.3683 & 0.356663 \tabularnewline
19 & -0.030663 & -0.3331 & 0.369829 \tabularnewline
20 & -0.079811 & -0.867 & 0.193858 \tabularnewline
21 & 0.187524 & 2.037 & 0.021942 \tabularnewline
22 & -0.151613 & -1.6469 & 0.051116 \tabularnewline
23 & 0.079183 & 0.8601 & 0.195726 \tabularnewline
24 & -0.026099 & -0.2835 & 0.388642 \tabularnewline
25 & -0.068028 & -0.739 & 0.230694 \tabularnewline
26 & 0.207326 & 2.2521 & 0.013082 \tabularnewline
27 & -0.134602 & -1.4622 & 0.073178 \tabularnewline
28 & 0.153391 & 1.6663 & 0.049158 \tabularnewline
29 & -0.041542 & -0.4513 & 0.326314 \tabularnewline
30 & 0.027775 & 0.3017 & 0.3817 \tabularnewline
31 & 0.018478 & 0.2007 & 0.420629 \tabularnewline
32 & 0.000848 & 0.0092 & 0.496335 \tabularnewline
33 & -0.102036 & -1.1084 & 0.134972 \tabularnewline
34 & 0.041829 & 0.4544 & 0.325196 \tabularnewline
35 & -0.115475 & -1.2544 & 0.106092 \tabularnewline
36 & -0.025375 & -0.2756 & 0.391654 \tabularnewline
37 & -0.03766 & -0.4091 & 0.341608 \tabularnewline
38 & -0.122046 & -1.3258 & 0.09374 \tabularnewline
39 & 0.118086 & 1.2827 & 0.101049 \tabularnewline
40 & -0.144107 & -1.5654 & 0.060083 \tabularnewline
41 & 0.112981 & 1.2273 & 0.111079 \tabularnewline
42 & -0.086236 & -0.9368 & 0.175396 \tabularnewline
43 & -0.052395 & -0.5692 & 0.285166 \tabularnewline
44 & -0.014902 & -0.1619 & 0.435838 \tabularnewline
45 & -0.044049 & -0.4785 & 0.316593 \tabularnewline
46 & 0.009095 & 0.0988 & 0.460734 \tabularnewline
47 & -0.025743 & -0.2796 & 0.39012 \tabularnewline
48 & -0.028834 & -0.3132 & 0.377335 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110835&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]-0.209778[/C][C]-2.2788[/C][C]0.01224[/C][/ROW]
[ROW][C]2[/C][C]0.187397[/C][C]2.0357[/C][C]0.022012[/C][/ROW]
[ROW][C]3[/C][C]0.042731[/C][C]0.4642[/C][C]0.321687[/C][/ROW]
[ROW][C]4[/C][C]0.155267[/C][C]1.6866[/C][C]0.047158[/C][/ROW]
[ROW][C]5[/C][C]0.010591[/C][C]0.115[/C][C]0.454301[/C][/ROW]
[ROW][C]6[/C][C]-0.010445[/C][C]-0.1135[/C][C]0.454928[/C][/ROW]
[ROW][C]7[/C][C]0.064042[/C][C]0.6957[/C][C]0.244001[/C][/ROW]
[ROW][C]8[/C][C]0.074083[/C][C]0.8047[/C][C]0.211293[/C][/ROW]
[ROW][C]9[/C][C]-0.141825[/C][C]-1.5406[/C][C]0.063044[/C][/ROW]
[ROW][C]10[/C][C]0.025532[/C][C]0.2773[/C][C]0.391[/C][/ROW]
[ROW][C]11[/C][C]0.085569[/C][C]0.9295[/C][C]0.177258[/C][/ROW]
[ROW][C]12[/C][C]-0.400937[/C][C]-4.3553[/C][C]1.4e-05[/C][/ROW]
[ROW][C]13[/C][C]0.24352[/C][C]2.6453[/C][C]0.004637[/C][/ROW]
[ROW][C]14[/C][C]-0.250189[/C][C]-2.7178[/C][C]0.003782[/C][/ROW]
[ROW][C]15[/C][C]0.058309[/C][C]0.6334[/C][C]0.263849[/C][/ROW]
[ROW][C]16[/C][C]-0.216953[/C][C]-2.3567[/C][C]0.010043[/C][/ROW]
[ROW][C]17[/C][C]-0.063648[/C][C]-0.6914[/C][C]0.245339[/C][/ROW]
[ROW][C]18[/C][C]0.033903[/C][C]0.3683[/C][C]0.356663[/C][/ROW]
[ROW][C]19[/C][C]-0.030663[/C][C]-0.3331[/C][C]0.369829[/C][/ROW]
[ROW][C]20[/C][C]-0.079811[/C][C]-0.867[/C][C]0.193858[/C][/ROW]
[ROW][C]21[/C][C]0.187524[/C][C]2.037[/C][C]0.021942[/C][/ROW]
[ROW][C]22[/C][C]-0.151613[/C][C]-1.6469[/C][C]0.051116[/C][/ROW]
[ROW][C]23[/C][C]0.079183[/C][C]0.8601[/C][C]0.195726[/C][/ROW]
[ROW][C]24[/C][C]-0.026099[/C][C]-0.2835[/C][C]0.388642[/C][/ROW]
[ROW][C]25[/C][C]-0.068028[/C][C]-0.739[/C][C]0.230694[/C][/ROW]
[ROW][C]26[/C][C]0.207326[/C][C]2.2521[/C][C]0.013082[/C][/ROW]
[ROW][C]27[/C][C]-0.134602[/C][C]-1.4622[/C][C]0.073178[/C][/ROW]
[ROW][C]28[/C][C]0.153391[/C][C]1.6663[/C][C]0.049158[/C][/ROW]
[ROW][C]29[/C][C]-0.041542[/C][C]-0.4513[/C][C]0.326314[/C][/ROW]
[ROW][C]30[/C][C]0.027775[/C][C]0.3017[/C][C]0.3817[/C][/ROW]
[ROW][C]31[/C][C]0.018478[/C][C]0.2007[/C][C]0.420629[/C][/ROW]
[ROW][C]32[/C][C]0.000848[/C][C]0.0092[/C][C]0.496335[/C][/ROW]
[ROW][C]33[/C][C]-0.102036[/C][C]-1.1084[/C][C]0.134972[/C][/ROW]
[ROW][C]34[/C][C]0.041829[/C][C]0.4544[/C][C]0.325196[/C][/ROW]
[ROW][C]35[/C][C]-0.115475[/C][C]-1.2544[/C][C]0.106092[/C][/ROW]
[ROW][C]36[/C][C]-0.025375[/C][C]-0.2756[/C][C]0.391654[/C][/ROW]
[ROW][C]37[/C][C]-0.03766[/C][C]-0.4091[/C][C]0.341608[/C][/ROW]
[ROW][C]38[/C][C]-0.122046[/C][C]-1.3258[/C][C]0.09374[/C][/ROW]
[ROW][C]39[/C][C]0.118086[/C][C]1.2827[/C][C]0.101049[/C][/ROW]
[ROW][C]40[/C][C]-0.144107[/C][C]-1.5654[/C][C]0.060083[/C][/ROW]
[ROW][C]41[/C][C]0.112981[/C][C]1.2273[/C][C]0.111079[/C][/ROW]
[ROW][C]42[/C][C]-0.086236[/C][C]-0.9368[/C][C]0.175396[/C][/ROW]
[ROW][C]43[/C][C]-0.052395[/C][C]-0.5692[/C][C]0.285166[/C][/ROW]
[ROW][C]44[/C][C]-0.014902[/C][C]-0.1619[/C][C]0.435838[/C][/ROW]
[ROW][C]45[/C][C]-0.044049[/C][C]-0.4785[/C][C]0.316593[/C][/ROW]
[ROW][C]46[/C][C]0.009095[/C][C]0.0988[/C][C]0.460734[/C][/ROW]
[ROW][C]47[/C][C]-0.025743[/C][C]-0.2796[/C][C]0.39012[/C][/ROW]
[ROW][C]48[/C][C]-0.028834[/C][C]-0.3132[/C][C]0.377335[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110835&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110835&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
1-0.209778-2.27880.01224
20.1873972.03570.022012
30.0427310.46420.321687
40.1552671.68660.047158
50.0105910.1150.454301
6-0.010445-0.11350.454928
70.0640420.69570.244001
80.0740830.80470.211293
9-0.141825-1.54060.063044
100.0255320.27730.391
110.0855690.92950.177258
12-0.400937-4.35531.4e-05
130.243522.64530.004637
14-0.250189-2.71780.003782
150.0583090.63340.263849
16-0.216953-2.35670.010043
17-0.063648-0.69140.245339
180.0339030.36830.356663
19-0.030663-0.33310.369829
20-0.079811-0.8670.193858
210.1875242.0370.021942
22-0.151613-1.64690.051116
230.0791830.86010.195726
24-0.026099-0.28350.388642
25-0.068028-0.7390.230694
260.2073262.25210.013082
27-0.134602-1.46220.073178
280.1533911.66630.049158
29-0.041542-0.45130.326314
300.0277750.30170.3817
310.0184780.20070.420629
320.0008480.00920.496335
33-0.102036-1.10840.134972
340.0418290.45440.325196
35-0.115475-1.25440.106092
36-0.025375-0.27560.391654
37-0.03766-0.40910.341608
38-0.122046-1.32580.09374
390.1180861.28270.101049
40-0.144107-1.56540.060083
410.1129811.22730.111079
42-0.086236-0.93680.175396
43-0.052395-0.56920.285166
44-0.014902-0.16190.435838
45-0.044049-0.47850.316593
460.0090950.09880.460734
47-0.025743-0.27960.39012
48-0.028834-0.31320.377335







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.209778-2.27880.01224
20.1499911.62930.052956
30.1151561.25090.106721
40.1689911.83570.034459
50.0509090.5530.290652
6-0.064887-0.70490.241144
70.009430.10240.459291
80.0801320.87050.19291
9-0.140404-1.52520.064945
10-0.063747-0.69250.245
110.1127511.22480.111546
12-0.415301-4.51138e-06
130.1590441.72770.043333
14-0.087707-0.95270.171335
15-0.063559-0.69040.245642
16-0.054673-0.59390.276859
17-0.143307-1.55670.061109
180.0536930.58330.280419
190.1380011.49910.068263
200.0024120.02620.489569
210.1418671.54110.062989
22-0.053909-0.58560.27963
230.0042740.04640.481524
24-0.138165-1.50090.068031
25-0.013914-0.15110.440059
260.0909420.98790.162616
27-0.018096-0.19660.42225
28-0.008855-0.09620.461766
29-0.08057-0.87520.191618
300.0354990.38560.350238
31-0.010837-0.11770.453244
32-0.050831-0.55220.29094
33-0.044366-0.48190.315372
34-0.174435-1.89480.03028
350.0900760.97850.164922
36-0.187334-2.0350.022047
370.0718820.78080.218232
380.0177150.19240.423865
39-0.020257-0.220.413108
400.0541910.58870.278605
410.0269660.29290.385048
420.0217040.23580.407013
43-0.062857-0.68280.248035
44-0.069781-0.7580.224975
45-0.106003-1.15150.125931
46-0.006455-0.07010.472111
47-0.049793-0.54090.294803
48-0.135105-1.46760.072434

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.209778 & -2.2788 & 0.01224 \tabularnewline
2 & 0.149991 & 1.6293 & 0.052956 \tabularnewline
3 & 0.115156 & 1.2509 & 0.106721 \tabularnewline
4 & 0.168991 & 1.8357 & 0.034459 \tabularnewline
5 & 0.050909 & 0.553 & 0.290652 \tabularnewline
6 & -0.064887 & -0.7049 & 0.241144 \tabularnewline
7 & 0.00943 & 0.1024 & 0.459291 \tabularnewline
8 & 0.080132 & 0.8705 & 0.19291 \tabularnewline
9 & -0.140404 & -1.5252 & 0.064945 \tabularnewline
10 & -0.063747 & -0.6925 & 0.245 \tabularnewline
11 & 0.112751 & 1.2248 & 0.111546 \tabularnewline
12 & -0.415301 & -4.5113 & 8e-06 \tabularnewline
13 & 0.159044 & 1.7277 & 0.043333 \tabularnewline
14 & -0.087707 & -0.9527 & 0.171335 \tabularnewline
15 & -0.063559 & -0.6904 & 0.245642 \tabularnewline
16 & -0.054673 & -0.5939 & 0.276859 \tabularnewline
17 & -0.143307 & -1.5567 & 0.061109 \tabularnewline
18 & 0.053693 & 0.5833 & 0.280419 \tabularnewline
19 & 0.138001 & 1.4991 & 0.068263 \tabularnewline
20 & 0.002412 & 0.0262 & 0.489569 \tabularnewline
21 & 0.141867 & 1.5411 & 0.062989 \tabularnewline
22 & -0.053909 & -0.5856 & 0.27963 \tabularnewline
23 & 0.004274 & 0.0464 & 0.481524 \tabularnewline
24 & -0.138165 & -1.5009 & 0.068031 \tabularnewline
25 & -0.013914 & -0.1511 & 0.440059 \tabularnewline
26 & 0.090942 & 0.9879 & 0.162616 \tabularnewline
27 & -0.018096 & -0.1966 & 0.42225 \tabularnewline
28 & -0.008855 & -0.0962 & 0.461766 \tabularnewline
29 & -0.08057 & -0.8752 & 0.191618 \tabularnewline
30 & 0.035499 & 0.3856 & 0.350238 \tabularnewline
31 & -0.010837 & -0.1177 & 0.453244 \tabularnewline
32 & -0.050831 & -0.5522 & 0.29094 \tabularnewline
33 & -0.044366 & -0.4819 & 0.315372 \tabularnewline
34 & -0.174435 & -1.8948 & 0.03028 \tabularnewline
35 & 0.090076 & 0.9785 & 0.164922 \tabularnewline
36 & -0.187334 & -2.035 & 0.022047 \tabularnewline
37 & 0.071882 & 0.7808 & 0.218232 \tabularnewline
38 & 0.017715 & 0.1924 & 0.423865 \tabularnewline
39 & -0.020257 & -0.22 & 0.413108 \tabularnewline
40 & 0.054191 & 0.5887 & 0.278605 \tabularnewline
41 & 0.026966 & 0.2929 & 0.385048 \tabularnewline
42 & 0.021704 & 0.2358 & 0.407013 \tabularnewline
43 & -0.062857 & -0.6828 & 0.248035 \tabularnewline
44 & -0.069781 & -0.758 & 0.224975 \tabularnewline
45 & -0.106003 & -1.1515 & 0.125931 \tabularnewline
46 & -0.006455 & -0.0701 & 0.472111 \tabularnewline
47 & -0.049793 & -0.5409 & 0.294803 \tabularnewline
48 & -0.135105 & -1.4676 & 0.072434 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110835&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]-0.209778[/C][C]-2.2788[/C][C]0.01224[/C][/ROW]
[ROW][C]2[/C][C]0.149991[/C][C]1.6293[/C][C]0.052956[/C][/ROW]
[ROW][C]3[/C][C]0.115156[/C][C]1.2509[/C][C]0.106721[/C][/ROW]
[ROW][C]4[/C][C]0.168991[/C][C]1.8357[/C][C]0.034459[/C][/ROW]
[ROW][C]5[/C][C]0.050909[/C][C]0.553[/C][C]0.290652[/C][/ROW]
[ROW][C]6[/C][C]-0.064887[/C][C]-0.7049[/C][C]0.241144[/C][/ROW]
[ROW][C]7[/C][C]0.00943[/C][C]0.1024[/C][C]0.459291[/C][/ROW]
[ROW][C]8[/C][C]0.080132[/C][C]0.8705[/C][C]0.19291[/C][/ROW]
[ROW][C]9[/C][C]-0.140404[/C][C]-1.5252[/C][C]0.064945[/C][/ROW]
[ROW][C]10[/C][C]-0.063747[/C][C]-0.6925[/C][C]0.245[/C][/ROW]
[ROW][C]11[/C][C]0.112751[/C][C]1.2248[/C][C]0.111546[/C][/ROW]
[ROW][C]12[/C][C]-0.415301[/C][C]-4.5113[/C][C]8e-06[/C][/ROW]
[ROW][C]13[/C][C]0.159044[/C][C]1.7277[/C][C]0.043333[/C][/ROW]
[ROW][C]14[/C][C]-0.087707[/C][C]-0.9527[/C][C]0.171335[/C][/ROW]
[ROW][C]15[/C][C]-0.063559[/C][C]-0.6904[/C][C]0.245642[/C][/ROW]
[ROW][C]16[/C][C]-0.054673[/C][C]-0.5939[/C][C]0.276859[/C][/ROW]
[ROW][C]17[/C][C]-0.143307[/C][C]-1.5567[/C][C]0.061109[/C][/ROW]
[ROW][C]18[/C][C]0.053693[/C][C]0.5833[/C][C]0.280419[/C][/ROW]
[ROW][C]19[/C][C]0.138001[/C][C]1.4991[/C][C]0.068263[/C][/ROW]
[ROW][C]20[/C][C]0.002412[/C][C]0.0262[/C][C]0.489569[/C][/ROW]
[ROW][C]21[/C][C]0.141867[/C][C]1.5411[/C][C]0.062989[/C][/ROW]
[ROW][C]22[/C][C]-0.053909[/C][C]-0.5856[/C][C]0.27963[/C][/ROW]
[ROW][C]23[/C][C]0.004274[/C][C]0.0464[/C][C]0.481524[/C][/ROW]
[ROW][C]24[/C][C]-0.138165[/C][C]-1.5009[/C][C]0.068031[/C][/ROW]
[ROW][C]25[/C][C]-0.013914[/C][C]-0.1511[/C][C]0.440059[/C][/ROW]
[ROW][C]26[/C][C]0.090942[/C][C]0.9879[/C][C]0.162616[/C][/ROW]
[ROW][C]27[/C][C]-0.018096[/C][C]-0.1966[/C][C]0.42225[/C][/ROW]
[ROW][C]28[/C][C]-0.008855[/C][C]-0.0962[/C][C]0.461766[/C][/ROW]
[ROW][C]29[/C][C]-0.08057[/C][C]-0.8752[/C][C]0.191618[/C][/ROW]
[ROW][C]30[/C][C]0.035499[/C][C]0.3856[/C][C]0.350238[/C][/ROW]
[ROW][C]31[/C][C]-0.010837[/C][C]-0.1177[/C][C]0.453244[/C][/ROW]
[ROW][C]32[/C][C]-0.050831[/C][C]-0.5522[/C][C]0.29094[/C][/ROW]
[ROW][C]33[/C][C]-0.044366[/C][C]-0.4819[/C][C]0.315372[/C][/ROW]
[ROW][C]34[/C][C]-0.174435[/C][C]-1.8948[/C][C]0.03028[/C][/ROW]
[ROW][C]35[/C][C]0.090076[/C][C]0.9785[/C][C]0.164922[/C][/ROW]
[ROW][C]36[/C][C]-0.187334[/C][C]-2.035[/C][C]0.022047[/C][/ROW]
[ROW][C]37[/C][C]0.071882[/C][C]0.7808[/C][C]0.218232[/C][/ROW]
[ROW][C]38[/C][C]0.017715[/C][C]0.1924[/C][C]0.423865[/C][/ROW]
[ROW][C]39[/C][C]-0.020257[/C][C]-0.22[/C][C]0.413108[/C][/ROW]
[ROW][C]40[/C][C]0.054191[/C][C]0.5887[/C][C]0.278605[/C][/ROW]
[ROW][C]41[/C][C]0.026966[/C][C]0.2929[/C][C]0.385048[/C][/ROW]
[ROW][C]42[/C][C]0.021704[/C][C]0.2358[/C][C]0.407013[/C][/ROW]
[ROW][C]43[/C][C]-0.062857[/C][C]-0.6828[/C][C]0.248035[/C][/ROW]
[ROW][C]44[/C][C]-0.069781[/C][C]-0.758[/C][C]0.224975[/C][/ROW]
[ROW][C]45[/C][C]-0.106003[/C][C]-1.1515[/C][C]0.125931[/C][/ROW]
[ROW][C]46[/C][C]-0.006455[/C][C]-0.0701[/C][C]0.472111[/C][/ROW]
[ROW][C]47[/C][C]-0.049793[/C][C]-0.5409[/C][C]0.294803[/C][/ROW]
[ROW][C]48[/C][C]-0.135105[/C][C]-1.4676[/C][C]0.072434[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110835&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110835&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
1-0.209778-2.27880.01224
20.1499911.62930.052956
30.1151561.25090.106721
40.1689911.83570.034459
50.0509090.5530.290652
6-0.064887-0.70490.241144
70.009430.10240.459291
80.0801320.87050.19291
9-0.140404-1.52520.064945
10-0.063747-0.69250.245
110.1127511.22480.111546
12-0.415301-4.51138e-06
130.1590441.72770.043333
14-0.087707-0.95270.171335
15-0.063559-0.69040.245642
16-0.054673-0.59390.276859
17-0.143307-1.55670.061109
180.0536930.58330.280419
190.1380011.49910.068263
200.0024120.02620.489569
210.1418671.54110.062989
22-0.053909-0.58560.27963
230.0042740.04640.481524
24-0.138165-1.50090.068031
25-0.013914-0.15110.440059
260.0909420.98790.162616
27-0.018096-0.19660.42225
28-0.008855-0.09620.461766
29-0.08057-0.87520.191618
300.0354990.38560.350238
31-0.010837-0.11770.453244
32-0.050831-0.55220.29094
33-0.044366-0.48190.315372
34-0.174435-1.89480.03028
350.0900760.97850.164922
36-0.187334-2.0350.022047
370.0718820.78080.218232
380.0177150.19240.423865
39-0.020257-0.220.413108
400.0541910.58870.278605
410.0269660.29290.385048
420.0217040.23580.407013
43-0.062857-0.68280.248035
44-0.069781-0.7580.224975
45-0.106003-1.15150.125931
46-0.006455-0.07010.472111
47-0.049793-0.54090.294803
48-0.135105-1.46760.072434



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