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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 21 Dec 2015 09:35:04 +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/2015/Dec/21/t1450690557wo79faq4n2cq5lz.htm/, Retrieved Thu, 31 Oct 2024 23:48:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286986, Retrieved Thu, 31 Oct 2024 23:48:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Levend geborene v...] [2015-10-23 21:16:41] [bd0500bc70c400edacc49194edbaf94e]
- R PD  [(Partial) Autocorrelation Function] [Aantal levendgebo...] [2015-12-20 14:30:34] [bd0500bc70c400edacc49194edbaf94e]
-   P       [(Partial) Autocorrelation Function] [Aantal levendgebo...] [2015-12-21 09:35:04] [1e41f2c0cb9908cbb229b763456942f4] [Current]
-             [(Partial) Autocorrelation Function] [sam peeters ] [2016-01-09 16:57:25] [148b14c5dbcad3a1bad7729b47ff94ec]
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Dataseries X:
2341
2115
2402
2180
2453
2507
2679
2622
2618
2648
2523
2473
2513
2466
2544
2537
2564
2582
2716
2904
2851
2932
2772
2811
2935
2783
3003
2995
3127
2985
3287
3236
3252
3228
2856
3176
3362
3036
3330
3251
3318
3238
3597
3708
3902
3745
3426
3526
3483
3458
3824
3696
3518
3814
3996
4136
4037
3915
3760
3955
4160
4115
4202
4018
4233
4029
4401
4645
4491
4379
4394
4472
4614
4160
4328
4202
4635
4542
4920
4774
4698
4916
4703
4616
4873
4375
4801
4427
4684
4648
5225
5174
5181
5266
4839
5032
5221
4658
5014
4980
4952
4946
5365
5456
5397
5436
4995
5019
5249
4799
5137
4979
4951
5265
5612
5572
5403
5373
5252
5437
5296
5011
5294
5335
5398
5396
5724
5898
5718
5625
5380
5488
5678
5224
5596
5184
5620
5531
5816
6086
6175
6112
5813
5740
5821
5294
5881
5589
5845
5706
6355
6404
6426
6375
5869
5994
6105
5792
6011
5968
6255
6208
6897
6814
6897
6596
6188
6406
6548
5842
6555
6424
6596
6645
7203
7128
7133
6778
6593
6591
6120
5612
6070
5983
6145
6303
6588
6640
6719
6575
6487
6510
6365
5844
5974
5880
6279
6342
6598
6801
6529
6369
6028
6187
6164
5866
6198
5898
6462
6063
6496
6678
6554
6513
6210
5928
6268
5582
5869
5764
6082
6062
6810
6727
6537
6175
6014
6109




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286986&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286986&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'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.351632-5.29790
20.1956122.94720.001771
3-0.107374-1.61770.053553
4-0.06566-0.98930.161794
5-0.110298-1.66180.048966
6-0.073427-1.10630.134885
7-0.140383-2.11510.017756
8-0.029684-0.44720.327568
9-0.05743-0.86530.1939
100.1560342.35090.009793
11-0.196918-2.96690.001665
120.67005410.09540
13-0.289906-4.36791e-05
140.226013.40520.000391
15-0.072276-1.08890.138667
16-0.085212-1.28380.100253
17-0.039979-0.60240.273771
18-0.123001-1.85320.032576
19-0.115337-1.73770.041808
20-0.037983-0.57230.28385
21-0.055348-0.83390.202606
220.1394372.10080.01838
23-0.129297-1.94810.02632
240.5684348.56430
25-0.221004-3.32980.000507
260.191062.87860.002188
27-0.115971-1.74730.04097
28-0.026705-0.40230.343904
29-0.067036-1.010.156786
30-0.171086-2.57770.00529
31-0.060032-0.90450.183353
32-0.010759-0.16210.435688
33-0.070102-1.05620.146002
340.1748122.63380.004512
35-0.187649-2.82720.002557
360.5314228.00670
37-0.160674-2.42080.008136
380.1687772.54290.00583
39-0.115042-1.73330.042202
40-0.021007-0.31650.375958
41-0.08338-1.25620.10516
42-0.120301-1.81250.035614
43-0.065242-0.9830.163333
44-0.044962-0.67740.249412
45-0.082135-1.23750.108591
460.2139353.22330.000727
47-0.235316-3.54540.000238
480.5568458.38970

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.351632 & -5.2979 & 0 \tabularnewline
2 & 0.195612 & 2.9472 & 0.001771 \tabularnewline
3 & -0.107374 & -1.6177 & 0.053553 \tabularnewline
4 & -0.06566 & -0.9893 & 0.161794 \tabularnewline
5 & -0.110298 & -1.6618 & 0.048966 \tabularnewline
6 & -0.073427 & -1.1063 & 0.134885 \tabularnewline
7 & -0.140383 & -2.1151 & 0.017756 \tabularnewline
8 & -0.029684 & -0.4472 & 0.327568 \tabularnewline
9 & -0.05743 & -0.8653 & 0.1939 \tabularnewline
10 & 0.156034 & 2.3509 & 0.009793 \tabularnewline
11 & -0.196918 & -2.9669 & 0.001665 \tabularnewline
12 & 0.670054 & 10.0954 & 0 \tabularnewline
13 & -0.289906 & -4.3679 & 1e-05 \tabularnewline
14 & 0.22601 & 3.4052 & 0.000391 \tabularnewline
15 & -0.072276 & -1.0889 & 0.138667 \tabularnewline
16 & -0.085212 & -1.2838 & 0.100253 \tabularnewline
17 & -0.039979 & -0.6024 & 0.273771 \tabularnewline
18 & -0.123001 & -1.8532 & 0.032576 \tabularnewline
19 & -0.115337 & -1.7377 & 0.041808 \tabularnewline
20 & -0.037983 & -0.5723 & 0.28385 \tabularnewline
21 & -0.055348 & -0.8339 & 0.202606 \tabularnewline
22 & 0.139437 & 2.1008 & 0.01838 \tabularnewline
23 & -0.129297 & -1.9481 & 0.02632 \tabularnewline
24 & 0.568434 & 8.5643 & 0 \tabularnewline
25 & -0.221004 & -3.3298 & 0.000507 \tabularnewline
26 & 0.19106 & 2.8786 & 0.002188 \tabularnewline
27 & -0.115971 & -1.7473 & 0.04097 \tabularnewline
28 & -0.026705 & -0.4023 & 0.343904 \tabularnewline
29 & -0.067036 & -1.01 & 0.156786 \tabularnewline
30 & -0.171086 & -2.5777 & 0.00529 \tabularnewline
31 & -0.060032 & -0.9045 & 0.183353 \tabularnewline
32 & -0.010759 & -0.1621 & 0.435688 \tabularnewline
33 & -0.070102 & -1.0562 & 0.146002 \tabularnewline
34 & 0.174812 & 2.6338 & 0.004512 \tabularnewline
35 & -0.187649 & -2.8272 & 0.002557 \tabularnewline
36 & 0.531422 & 8.0067 & 0 \tabularnewline
37 & -0.160674 & -2.4208 & 0.008136 \tabularnewline
38 & 0.168777 & 2.5429 & 0.00583 \tabularnewline
39 & -0.115042 & -1.7333 & 0.042202 \tabularnewline
40 & -0.021007 & -0.3165 & 0.375958 \tabularnewline
41 & -0.08338 & -1.2562 & 0.10516 \tabularnewline
42 & -0.120301 & -1.8125 & 0.035614 \tabularnewline
43 & -0.065242 & -0.983 & 0.163333 \tabularnewline
44 & -0.044962 & -0.6774 & 0.249412 \tabularnewline
45 & -0.082135 & -1.2375 & 0.108591 \tabularnewline
46 & 0.213935 & 3.2233 & 0.000727 \tabularnewline
47 & -0.235316 & -3.5454 & 0.000238 \tabularnewline
48 & 0.556845 & 8.3897 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286986&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]-0.351632[/C][C]-5.2979[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.195612[/C][C]2.9472[/C][C]0.001771[/C][/ROW]
[ROW][C]3[/C][C]-0.107374[/C][C]-1.6177[/C][C]0.053553[/C][/ROW]
[ROW][C]4[/C][C]-0.06566[/C][C]-0.9893[/C][C]0.161794[/C][/ROW]
[ROW][C]5[/C][C]-0.110298[/C][C]-1.6618[/C][C]0.048966[/C][/ROW]
[ROW][C]6[/C][C]-0.073427[/C][C]-1.1063[/C][C]0.134885[/C][/ROW]
[ROW][C]7[/C][C]-0.140383[/C][C]-2.1151[/C][C]0.017756[/C][/ROW]
[ROW][C]8[/C][C]-0.029684[/C][C]-0.4472[/C][C]0.327568[/C][/ROW]
[ROW][C]9[/C][C]-0.05743[/C][C]-0.8653[/C][C]0.1939[/C][/ROW]
[ROW][C]10[/C][C]0.156034[/C][C]2.3509[/C][C]0.009793[/C][/ROW]
[ROW][C]11[/C][C]-0.196918[/C][C]-2.9669[/C][C]0.001665[/C][/ROW]
[ROW][C]12[/C][C]0.670054[/C][C]10.0954[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.289906[/C][C]-4.3679[/C][C]1e-05[/C][/ROW]
[ROW][C]14[/C][C]0.22601[/C][C]3.4052[/C][C]0.000391[/C][/ROW]
[ROW][C]15[/C][C]-0.072276[/C][C]-1.0889[/C][C]0.138667[/C][/ROW]
[ROW][C]16[/C][C]-0.085212[/C][C]-1.2838[/C][C]0.100253[/C][/ROW]
[ROW][C]17[/C][C]-0.039979[/C][C]-0.6024[/C][C]0.273771[/C][/ROW]
[ROW][C]18[/C][C]-0.123001[/C][C]-1.8532[/C][C]0.032576[/C][/ROW]
[ROW][C]19[/C][C]-0.115337[/C][C]-1.7377[/C][C]0.041808[/C][/ROW]
[ROW][C]20[/C][C]-0.037983[/C][C]-0.5723[/C][C]0.28385[/C][/ROW]
[ROW][C]21[/C][C]-0.055348[/C][C]-0.8339[/C][C]0.202606[/C][/ROW]
[ROW][C]22[/C][C]0.139437[/C][C]2.1008[/C][C]0.01838[/C][/ROW]
[ROW][C]23[/C][C]-0.129297[/C][C]-1.9481[/C][C]0.02632[/C][/ROW]
[ROW][C]24[/C][C]0.568434[/C][C]8.5643[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.221004[/C][C]-3.3298[/C][C]0.000507[/C][/ROW]
[ROW][C]26[/C][C]0.19106[/C][C]2.8786[/C][C]0.002188[/C][/ROW]
[ROW][C]27[/C][C]-0.115971[/C][C]-1.7473[/C][C]0.04097[/C][/ROW]
[ROW][C]28[/C][C]-0.026705[/C][C]-0.4023[/C][C]0.343904[/C][/ROW]
[ROW][C]29[/C][C]-0.067036[/C][C]-1.01[/C][C]0.156786[/C][/ROW]
[ROW][C]30[/C][C]-0.171086[/C][C]-2.5777[/C][C]0.00529[/C][/ROW]
[ROW][C]31[/C][C]-0.060032[/C][C]-0.9045[/C][C]0.183353[/C][/ROW]
[ROW][C]32[/C][C]-0.010759[/C][C]-0.1621[/C][C]0.435688[/C][/ROW]
[ROW][C]33[/C][C]-0.070102[/C][C]-1.0562[/C][C]0.146002[/C][/ROW]
[ROW][C]34[/C][C]0.174812[/C][C]2.6338[/C][C]0.004512[/C][/ROW]
[ROW][C]35[/C][C]-0.187649[/C][C]-2.8272[/C][C]0.002557[/C][/ROW]
[ROW][C]36[/C][C]0.531422[/C][C]8.0067[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.160674[/C][C]-2.4208[/C][C]0.008136[/C][/ROW]
[ROW][C]38[/C][C]0.168777[/C][C]2.5429[/C][C]0.00583[/C][/ROW]
[ROW][C]39[/C][C]-0.115042[/C][C]-1.7333[/C][C]0.042202[/C][/ROW]
[ROW][C]40[/C][C]-0.021007[/C][C]-0.3165[/C][C]0.375958[/C][/ROW]
[ROW][C]41[/C][C]-0.08338[/C][C]-1.2562[/C][C]0.10516[/C][/ROW]
[ROW][C]42[/C][C]-0.120301[/C][C]-1.8125[/C][C]0.035614[/C][/ROW]
[ROW][C]43[/C][C]-0.065242[/C][C]-0.983[/C][C]0.163333[/C][/ROW]
[ROW][C]44[/C][C]-0.044962[/C][C]-0.6774[/C][C]0.249412[/C][/ROW]
[ROW][C]45[/C][C]-0.082135[/C][C]-1.2375[/C][C]0.108591[/C][/ROW]
[ROW][C]46[/C][C]0.213935[/C][C]3.2233[/C][C]0.000727[/C][/ROW]
[ROW][C]47[/C][C]-0.235316[/C][C]-3.5454[/C][C]0.000238[/C][/ROW]
[ROW][C]48[/C][C]0.556845[/C][C]8.3897[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286986&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
1-0.351632-5.29790
20.1956122.94720.001771
3-0.107374-1.61770.053553
4-0.06566-0.98930.161794
5-0.110298-1.66180.048966
6-0.073427-1.10630.134885
7-0.140383-2.11510.017756
8-0.029684-0.44720.327568
9-0.05743-0.86530.1939
100.1560342.35090.009793
11-0.196918-2.96690.001665
120.67005410.09540
13-0.289906-4.36791e-05
140.226013.40520.000391
15-0.072276-1.08890.138667
16-0.085212-1.28380.100253
17-0.039979-0.60240.273771
18-0.123001-1.85320.032576
19-0.115337-1.73770.041808
20-0.037983-0.57230.28385
21-0.055348-0.83390.202606
220.1394372.10080.01838
23-0.129297-1.94810.02632
240.5684348.56430
25-0.221004-3.32980.000507
260.191062.87860.002188
27-0.115971-1.74730.04097
28-0.026705-0.40230.343904
29-0.067036-1.010.156786
30-0.171086-2.57770.00529
31-0.060032-0.90450.183353
32-0.010759-0.16210.435688
33-0.070102-1.05620.146002
340.1748122.63380.004512
35-0.187649-2.82720.002557
360.5314228.00670
37-0.160674-2.42080.008136
380.1687772.54290.00583
39-0.115042-1.73330.042202
40-0.021007-0.31650.375958
41-0.08338-1.25620.10516
42-0.120301-1.81250.035614
43-0.065242-0.9830.163333
44-0.044962-0.67740.249412
45-0.082135-1.23750.108591
460.2139353.22330.000727
47-0.235316-3.54540.000238
480.5568458.38970







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.351632-5.29790
20.0821211.23730.108632
3-0.017649-0.26590.395275
4-0.139414-2.10050.018395
5-0.18636-2.80780.002711
6-0.168121-2.5330.005992
7-0.248066-3.73750.000118
8-0.233952-3.52480.000256
9-0.255929-3.8567.5e-05
10-0.074901-1.12850.130149
11-0.410141-6.17940
120.4547216.85110
130.0697291.05060.147286
140.0497530.74960.227134
150.1477882.22660.013477
160.0552180.83190.203157
170.1383482.08440.01912
180.0342850.51660.302986
190.0496680.74830.227518
200.0004170.00630.497494
21-0.052921-0.79730.213045
220.003310.04990.480137
23-0.078013-1.17540.120537
240.1915532.8860.002139
250.1653632.49140.006719
260.0361420.54450.293304
27-0.05377-0.81010.209357
280.1150341.73320.042213
290.0119520.18010.428627
30-0.139681-2.10450.018217
31-0.003617-0.05450.478293
320.0722141.0880.138872
33-0.064549-0.97250.165912
340.0317280.4780.316542
35-0.180911-2.72570.003458
360.0153410.23110.408712
370.1165441.75590.040226
380.0155230.23390.407648
39-0.021503-0.3240.37313
40-0.007452-0.11230.455351
410.0277310.41780.338239
420.0702291.05810.145564
430.0136780.20610.418455
440.0186740.28130.38935
45-0.072055-1.08560.139399
460.0496430.74790.227633
47-0.137547-2.07240.019681
480.0396230.5970.27556

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.351632 & -5.2979 & 0 \tabularnewline
2 & 0.082121 & 1.2373 & 0.108632 \tabularnewline
3 & -0.017649 & -0.2659 & 0.395275 \tabularnewline
4 & -0.139414 & -2.1005 & 0.018395 \tabularnewline
5 & -0.18636 & -2.8078 & 0.002711 \tabularnewline
6 & -0.168121 & -2.533 & 0.005992 \tabularnewline
7 & -0.248066 & -3.7375 & 0.000118 \tabularnewline
8 & -0.233952 & -3.5248 & 0.000256 \tabularnewline
9 & -0.255929 & -3.856 & 7.5e-05 \tabularnewline
10 & -0.074901 & -1.1285 & 0.130149 \tabularnewline
11 & -0.410141 & -6.1794 & 0 \tabularnewline
12 & 0.454721 & 6.8511 & 0 \tabularnewline
13 & 0.069729 & 1.0506 & 0.147286 \tabularnewline
14 & 0.049753 & 0.7496 & 0.227134 \tabularnewline
15 & 0.147788 & 2.2266 & 0.013477 \tabularnewline
16 & 0.055218 & 0.8319 & 0.203157 \tabularnewline
17 & 0.138348 & 2.0844 & 0.01912 \tabularnewline
18 & 0.034285 & 0.5166 & 0.302986 \tabularnewline
19 & 0.049668 & 0.7483 & 0.227518 \tabularnewline
20 & 0.000417 & 0.0063 & 0.497494 \tabularnewline
21 & -0.052921 & -0.7973 & 0.213045 \tabularnewline
22 & 0.00331 & 0.0499 & 0.480137 \tabularnewline
23 & -0.078013 & -1.1754 & 0.120537 \tabularnewline
24 & 0.191553 & 2.886 & 0.002139 \tabularnewline
25 & 0.165363 & 2.4914 & 0.006719 \tabularnewline
26 & 0.036142 & 0.5445 & 0.293304 \tabularnewline
27 & -0.05377 & -0.8101 & 0.209357 \tabularnewline
28 & 0.115034 & 1.7332 & 0.042213 \tabularnewline
29 & 0.011952 & 0.1801 & 0.428627 \tabularnewline
30 & -0.139681 & -2.1045 & 0.018217 \tabularnewline
31 & -0.003617 & -0.0545 & 0.478293 \tabularnewline
32 & 0.072214 & 1.088 & 0.138872 \tabularnewline
33 & -0.064549 & -0.9725 & 0.165912 \tabularnewline
34 & 0.031728 & 0.478 & 0.316542 \tabularnewline
35 & -0.180911 & -2.7257 & 0.003458 \tabularnewline
36 & 0.015341 & 0.2311 & 0.408712 \tabularnewline
37 & 0.116544 & 1.7559 & 0.040226 \tabularnewline
38 & 0.015523 & 0.2339 & 0.407648 \tabularnewline
39 & -0.021503 & -0.324 & 0.37313 \tabularnewline
40 & -0.007452 & -0.1123 & 0.455351 \tabularnewline
41 & 0.027731 & 0.4178 & 0.338239 \tabularnewline
42 & 0.070229 & 1.0581 & 0.145564 \tabularnewline
43 & 0.013678 & 0.2061 & 0.418455 \tabularnewline
44 & 0.018674 & 0.2813 & 0.38935 \tabularnewline
45 & -0.072055 & -1.0856 & 0.139399 \tabularnewline
46 & 0.049643 & 0.7479 & 0.227633 \tabularnewline
47 & -0.137547 & -2.0724 & 0.019681 \tabularnewline
48 & 0.039623 & 0.597 & 0.27556 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286986&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]-0.351632[/C][C]-5.2979[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.082121[/C][C]1.2373[/C][C]0.108632[/C][/ROW]
[ROW][C]3[/C][C]-0.017649[/C][C]-0.2659[/C][C]0.395275[/C][/ROW]
[ROW][C]4[/C][C]-0.139414[/C][C]-2.1005[/C][C]0.018395[/C][/ROW]
[ROW][C]5[/C][C]-0.18636[/C][C]-2.8078[/C][C]0.002711[/C][/ROW]
[ROW][C]6[/C][C]-0.168121[/C][C]-2.533[/C][C]0.005992[/C][/ROW]
[ROW][C]7[/C][C]-0.248066[/C][C]-3.7375[/C][C]0.000118[/C][/ROW]
[ROW][C]8[/C][C]-0.233952[/C][C]-3.5248[/C][C]0.000256[/C][/ROW]
[ROW][C]9[/C][C]-0.255929[/C][C]-3.856[/C][C]7.5e-05[/C][/ROW]
[ROW][C]10[/C][C]-0.074901[/C][C]-1.1285[/C][C]0.130149[/C][/ROW]
[ROW][C]11[/C][C]-0.410141[/C][C]-6.1794[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.454721[/C][C]6.8511[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.069729[/C][C]1.0506[/C][C]0.147286[/C][/ROW]
[ROW][C]14[/C][C]0.049753[/C][C]0.7496[/C][C]0.227134[/C][/ROW]
[ROW][C]15[/C][C]0.147788[/C][C]2.2266[/C][C]0.013477[/C][/ROW]
[ROW][C]16[/C][C]0.055218[/C][C]0.8319[/C][C]0.203157[/C][/ROW]
[ROW][C]17[/C][C]0.138348[/C][C]2.0844[/C][C]0.01912[/C][/ROW]
[ROW][C]18[/C][C]0.034285[/C][C]0.5166[/C][C]0.302986[/C][/ROW]
[ROW][C]19[/C][C]0.049668[/C][C]0.7483[/C][C]0.227518[/C][/ROW]
[ROW][C]20[/C][C]0.000417[/C][C]0.0063[/C][C]0.497494[/C][/ROW]
[ROW][C]21[/C][C]-0.052921[/C][C]-0.7973[/C][C]0.213045[/C][/ROW]
[ROW][C]22[/C][C]0.00331[/C][C]0.0499[/C][C]0.480137[/C][/ROW]
[ROW][C]23[/C][C]-0.078013[/C][C]-1.1754[/C][C]0.120537[/C][/ROW]
[ROW][C]24[/C][C]0.191553[/C][C]2.886[/C][C]0.002139[/C][/ROW]
[ROW][C]25[/C][C]0.165363[/C][C]2.4914[/C][C]0.006719[/C][/ROW]
[ROW][C]26[/C][C]0.036142[/C][C]0.5445[/C][C]0.293304[/C][/ROW]
[ROW][C]27[/C][C]-0.05377[/C][C]-0.8101[/C][C]0.209357[/C][/ROW]
[ROW][C]28[/C][C]0.115034[/C][C]1.7332[/C][C]0.042213[/C][/ROW]
[ROW][C]29[/C][C]0.011952[/C][C]0.1801[/C][C]0.428627[/C][/ROW]
[ROW][C]30[/C][C]-0.139681[/C][C]-2.1045[/C][C]0.018217[/C][/ROW]
[ROW][C]31[/C][C]-0.003617[/C][C]-0.0545[/C][C]0.478293[/C][/ROW]
[ROW][C]32[/C][C]0.072214[/C][C]1.088[/C][C]0.138872[/C][/ROW]
[ROW][C]33[/C][C]-0.064549[/C][C]-0.9725[/C][C]0.165912[/C][/ROW]
[ROW][C]34[/C][C]0.031728[/C][C]0.478[/C][C]0.316542[/C][/ROW]
[ROW][C]35[/C][C]-0.180911[/C][C]-2.7257[/C][C]0.003458[/C][/ROW]
[ROW][C]36[/C][C]0.015341[/C][C]0.2311[/C][C]0.408712[/C][/ROW]
[ROW][C]37[/C][C]0.116544[/C][C]1.7559[/C][C]0.040226[/C][/ROW]
[ROW][C]38[/C][C]0.015523[/C][C]0.2339[/C][C]0.407648[/C][/ROW]
[ROW][C]39[/C][C]-0.021503[/C][C]-0.324[/C][C]0.37313[/C][/ROW]
[ROW][C]40[/C][C]-0.007452[/C][C]-0.1123[/C][C]0.455351[/C][/ROW]
[ROW][C]41[/C][C]0.027731[/C][C]0.4178[/C][C]0.338239[/C][/ROW]
[ROW][C]42[/C][C]0.070229[/C][C]1.0581[/C][C]0.145564[/C][/ROW]
[ROW][C]43[/C][C]0.013678[/C][C]0.2061[/C][C]0.418455[/C][/ROW]
[ROW][C]44[/C][C]0.018674[/C][C]0.2813[/C][C]0.38935[/C][/ROW]
[ROW][C]45[/C][C]-0.072055[/C][C]-1.0856[/C][C]0.139399[/C][/ROW]
[ROW][C]46[/C][C]0.049643[/C][C]0.7479[/C][C]0.227633[/C][/ROW]
[ROW][C]47[/C][C]-0.137547[/C][C]-2.0724[/C][C]0.019681[/C][/ROW]
[ROW][C]48[/C][C]0.039623[/C][C]0.597[/C][C]0.27556[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286986&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286986&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
1-0.351632-5.29790
20.0821211.23730.108632
3-0.017649-0.26590.395275
4-0.139414-2.10050.018395
5-0.18636-2.80780.002711
6-0.168121-2.5330.005992
7-0.248066-3.73750.000118
8-0.233952-3.52480.000256
9-0.255929-3.8567.5e-05
10-0.074901-1.12850.130149
11-0.410141-6.17940
120.4547216.85110
130.0697291.05060.147286
140.0497530.74960.227134
150.1477882.22660.013477
160.0552180.83190.203157
170.1383482.08440.01912
180.0342850.51660.302986
190.0496680.74830.227518
200.0004170.00630.497494
21-0.052921-0.79730.213045
220.003310.04990.480137
23-0.078013-1.17540.120537
240.1915532.8860.002139
250.1653632.49140.006719
260.0361420.54450.293304
27-0.05377-0.81010.209357
280.1150341.73320.042213
290.0119520.18010.428627
30-0.139681-2.10450.018217
31-0.003617-0.05450.478293
320.0722141.0880.138872
33-0.064549-0.97250.165912
340.0317280.4780.316542
35-0.180911-2.72570.003458
360.0153410.23110.408712
370.1165441.75590.040226
380.0155230.23390.407648
39-0.021503-0.3240.37313
40-0.007452-0.11230.455351
410.0277310.41780.338239
420.0702291.05810.145564
430.0136780.20610.418455
440.0186740.28130.38935
45-0.072055-1.08560.139399
460.0496430.74790.227633
47-0.137547-2.07240.019681
480.0396230.5970.27556



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 ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')