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Author's title

Author*Unverified author*
R Software Module--
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 04 Dec 2013 21:45:14 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/04/t1386211532cwy93eks7z7g9lj.htm/, Retrieved Fri, 29 Mar 2024 06:46:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230855, Retrieved Fri, 29 Mar 2024 06:46:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80
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  D    [(Partial) Autocorrelation Function] [WS9.3] [2012-12-03 21:33:02] [74be16979710d4c4e7c6647856088456]
-  M          [(Partial) Autocorrelation Function] [] [2013-12-05 02:45:14] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
8,9634
8,9522
8,8682
8,7331
8,3188
8,3462
8,3087
8,3836
8,8412
9,5001
10,1883
10,2931
10,1945
10,3014
10,0675
9,6715
9,5019
9,4597
9,4362
9,5919
10,0167
10,322
11,166
11,5454
11,3712
11,0723
10,813
10,3016
10,4227
10,3162
10,4519
10,8567
11,2716
11,4341
12,1273
11,9814
11,8352
11,9847
11,545
11,5285
11,5539
11,622
11,6578
11,6767
11,8752
13,2643
14,2297
14,308
13,7915
13,7633
13,9775
13,6478
13,2247
13,0971
13,1039
13,206
13,7901
14,6457
15,5764
15,6102
15,8855
16,0137
15,6186
15,384
15,2751
15,0912
14,9222
15,6231
16,6737
17,6805
19,1919
19,1711
18,5658
18,1285
16,791
16,9468
17,3164
17,1816
16,7627
17,239
17,8838
18,9038
20,0274
20,0087
19,6366
19,8163
18,8602
17,9206
17,6889
17,84
17,678
17,7258
18,5865
19,9804
21,1584
21,2921
20,9445
20,5731
19,3274
17,7866
17,7483
17,5648
17,4763
17,7264
18,5736
19,9236
21,3286
20,7249
20,3334
19,7658
18,7569
17,6963
17,7978
18,1771
18,3738
18,1996
18,8443
20,1001
21,2458
20,8381
20,1967
19,8159
18,5784
19,21
19,3419
19,12
19,1563
18,9783
20,2913
22,5439
23,2821
22,6191
22,1599
21,2766
19,0846
18,9096
18,8095
20,1164
20,7762
20,9044
22,0026
23,6401
25,04
24,7185
24,1752
24,1382
22,3949
21,3743
21,4911
21,2187
21,2137
21,6735
22,5096
24,3097
25,7989
25,4376
23,878
23,6966
23,3544
21,1993
22,0431
22,0203
21,886
21,9771
23,0759
24,9859
26,2614
26,1127
25,6296
25,2926
22,8146
22,2974
22,8868
22,4612
22,3165
22,7319
23,2692
24,9432
27,8272
27,4059
26,6232
26,8779
25,105
23,601
23,5374
23,5248
22,9465
23,6633
25,5932
27,7683
29,4691
28,3472
28,3879
27,9696
26,0075
24,2533
24,4999
23,8988
23,6683
23,9427
26,0155
28,9529
30,302
29,874
28,2257
28,0811
26,3398
25,4847
25,4823
24,9697
25,2282
25,9257
28,7818
27,9552
33,3475
32,7834
31,6586
31,6613
29,1839
28,8825
27,6334
27,7511
27,3792
27,7748
31,4329
33,2735
35,0962
34,9537
31,8307
30,9984
28,629
26,4379
25,4408
24,6681
24,0994
24,6043
27,2492
29,5511
29,8522
31,6989
29,6357
30,5197
32,7823
24,9942
23,5187
24,0249
24,5692
24,402
26,7089
31,6874
32,8801
32,7906
30,8785
30,3024
28,3679
25,6578
25,1598
24,6143
24,528
25,2905
30,0016
34,2728
34,4408
34,1907
33,6636
33,9073
30,2175
28,5274
25,9505
26,2398
26,2819
26,7362
28,8395
31,0951
33,7015
33,8091
32,1126
32
29,122
26,8124
25,4654
23,8331
24,714
28,3288
29,6391
32,4542
33,5657
33,1856
33,297
33,51
31,3789
29,4555
27,2699
27,2586
27,8591
29,6362
30,9587
31,8633
33,8188
33,7531
33,6103
32,9052
29,5005
27,3634
27,2298
26,5211
26,5228
27,2991
29,1726
30,297
32,5287
32,487
32,4197
30,854
28,6995
27,7881
26,5609
25,9431
25,5578
27,1275
30,2556
34,0976
34,5614
34,2948
33,3418
31,8187
29,0818
27,3444
26,6233
26,1869
26,2953
28,7043
32,0653
34,5401
34,6636
34,2557
32,0526
30,6892
28,012
26,1528
23,2276
24,244
24,8141
27,8632
29,6233
32,4245
33,3417
33,0442
32,0526
30,2182
28,9292
26,8221
26,1032
25,9792
27,1443
29,4993
31,656
33,3665
35,0521
34,4076
33,069
31,5816
30,0695
29,0035
28,6813
28,359
30,0447
31,5073
34,16
35,57
36,42
35,12
33,14
30,29
28,2
26,5
25,47
24,96
25,6
27,76
30,13
32,35
32,8
32,54
29,78
28,79
26,8
25,41
24,34
24,39
25
26,27
27,88
29,35
29,83
29,46




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230855&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230855&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230855&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.20797-4.072.9e-05
2-0.097235-1.90290.0289
3-0.035198-0.68880.245674
40.0002430.00470.498108
50.0935181.83020.033999
6-0.080635-1.57810.057689
70.0189230.37030.355669
8-0.053422-1.04550.148229
90.0123660.2420.404449
100.1022682.00140.023025
110.0728221.42520.077462
12-0.386967-7.57310
13-0.001294-0.02530.489907
140.0524931.02730.152463
150.0529571.03640.150337
160.0067250.13160.447683
17-0.091316-1.78710.037357
180.0637511.24760.106464
19-0.045345-0.88740.187707
200.0239250.46820.319948
21-0.017313-0.33880.367466
22-0.03744-0.73270.232088
230.0457480.89530.185592
24-0.089164-1.7450.040895
250.154363.02090.001345
26-0.134418-2.63060.004434
270.0265580.51970.301772
280.0537991.05290.146534
29-0.103186-2.01940.022071
300.0783281.53290.063061
31-0.04163-0.81470.20787
32-0.037839-0.74050.22972
330.0569971.11540.13268
340.0430780.8430.199864
350.0528321.03390.15091
36-0.03301-0.6460.259327
37-0.04189-0.81980.20642
380.0890131.7420.041154
39-0.002201-0.04310.482835
40-0.060661-1.18720.117951
410.1155552.26150.012145
42-0.127836-2.50180.006386
430.1093592.14020.016485
440.0445810.87250.191752
45-0.058219-1.13940.12763
460.0142020.27790.390602
47-0.094699-1.85330.032304
480.0301320.58970.277868

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.20797 & -4.07 & 2.9e-05 \tabularnewline
2 & -0.097235 & -1.9029 & 0.0289 \tabularnewline
3 & -0.035198 & -0.6888 & 0.245674 \tabularnewline
4 & 0.000243 & 0.0047 & 0.498108 \tabularnewline
5 & 0.093518 & 1.8302 & 0.033999 \tabularnewline
6 & -0.080635 & -1.5781 & 0.057689 \tabularnewline
7 & 0.018923 & 0.3703 & 0.355669 \tabularnewline
8 & -0.053422 & -1.0455 & 0.148229 \tabularnewline
9 & 0.012366 & 0.242 & 0.404449 \tabularnewline
10 & 0.102268 & 2.0014 & 0.023025 \tabularnewline
11 & 0.072822 & 1.4252 & 0.077462 \tabularnewline
12 & -0.386967 & -7.5731 & 0 \tabularnewline
13 & -0.001294 & -0.0253 & 0.489907 \tabularnewline
14 & 0.052493 & 1.0273 & 0.152463 \tabularnewline
15 & 0.052957 & 1.0364 & 0.150337 \tabularnewline
16 & 0.006725 & 0.1316 & 0.447683 \tabularnewline
17 & -0.091316 & -1.7871 & 0.037357 \tabularnewline
18 & 0.063751 & 1.2476 & 0.106464 \tabularnewline
19 & -0.045345 & -0.8874 & 0.187707 \tabularnewline
20 & 0.023925 & 0.4682 & 0.319948 \tabularnewline
21 & -0.017313 & -0.3388 & 0.367466 \tabularnewline
22 & -0.03744 & -0.7327 & 0.232088 \tabularnewline
23 & 0.045748 & 0.8953 & 0.185592 \tabularnewline
24 & -0.089164 & -1.745 & 0.040895 \tabularnewline
25 & 0.15436 & 3.0209 & 0.001345 \tabularnewline
26 & -0.134418 & -2.6306 & 0.004434 \tabularnewline
27 & 0.026558 & 0.5197 & 0.301772 \tabularnewline
28 & 0.053799 & 1.0529 & 0.146534 \tabularnewline
29 & -0.103186 & -2.0194 & 0.022071 \tabularnewline
30 & 0.078328 & 1.5329 & 0.063061 \tabularnewline
31 & -0.04163 & -0.8147 & 0.20787 \tabularnewline
32 & -0.037839 & -0.7405 & 0.22972 \tabularnewline
33 & 0.056997 & 1.1154 & 0.13268 \tabularnewline
34 & 0.043078 & 0.843 & 0.199864 \tabularnewline
35 & 0.052832 & 1.0339 & 0.15091 \tabularnewline
36 & -0.03301 & -0.646 & 0.259327 \tabularnewline
37 & -0.04189 & -0.8198 & 0.20642 \tabularnewline
38 & 0.089013 & 1.742 & 0.041154 \tabularnewline
39 & -0.002201 & -0.0431 & 0.482835 \tabularnewline
40 & -0.060661 & -1.1872 & 0.117951 \tabularnewline
41 & 0.115555 & 2.2615 & 0.012145 \tabularnewline
42 & -0.127836 & -2.5018 & 0.006386 \tabularnewline
43 & 0.109359 & 2.1402 & 0.016485 \tabularnewline
44 & 0.044581 & 0.8725 & 0.191752 \tabularnewline
45 & -0.058219 & -1.1394 & 0.12763 \tabularnewline
46 & 0.014202 & 0.2779 & 0.390602 \tabularnewline
47 & -0.094699 & -1.8533 & 0.032304 \tabularnewline
48 & 0.030132 & 0.5897 & 0.277868 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230855&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]-0.20797[/C][C]-4.07[/C][C]2.9e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.097235[/C][C]-1.9029[/C][C]0.0289[/C][/ROW]
[ROW][C]3[/C][C]-0.035198[/C][C]-0.6888[/C][C]0.245674[/C][/ROW]
[ROW][C]4[/C][C]0.000243[/C][C]0.0047[/C][C]0.498108[/C][/ROW]
[ROW][C]5[/C][C]0.093518[/C][C]1.8302[/C][C]0.033999[/C][/ROW]
[ROW][C]6[/C][C]-0.080635[/C][C]-1.5781[/C][C]0.057689[/C][/ROW]
[ROW][C]7[/C][C]0.018923[/C][C]0.3703[/C][C]0.355669[/C][/ROW]
[ROW][C]8[/C][C]-0.053422[/C][C]-1.0455[/C][C]0.148229[/C][/ROW]
[ROW][C]9[/C][C]0.012366[/C][C]0.242[/C][C]0.404449[/C][/ROW]
[ROW][C]10[/C][C]0.102268[/C][C]2.0014[/C][C]0.023025[/C][/ROW]
[ROW][C]11[/C][C]0.072822[/C][C]1.4252[/C][C]0.077462[/C][/ROW]
[ROW][C]12[/C][C]-0.386967[/C][C]-7.5731[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.001294[/C][C]-0.0253[/C][C]0.489907[/C][/ROW]
[ROW][C]14[/C][C]0.052493[/C][C]1.0273[/C][C]0.152463[/C][/ROW]
[ROW][C]15[/C][C]0.052957[/C][C]1.0364[/C][C]0.150337[/C][/ROW]
[ROW][C]16[/C][C]0.006725[/C][C]0.1316[/C][C]0.447683[/C][/ROW]
[ROW][C]17[/C][C]-0.091316[/C][C]-1.7871[/C][C]0.037357[/C][/ROW]
[ROW][C]18[/C][C]0.063751[/C][C]1.2476[/C][C]0.106464[/C][/ROW]
[ROW][C]19[/C][C]-0.045345[/C][C]-0.8874[/C][C]0.187707[/C][/ROW]
[ROW][C]20[/C][C]0.023925[/C][C]0.4682[/C][C]0.319948[/C][/ROW]
[ROW][C]21[/C][C]-0.017313[/C][C]-0.3388[/C][C]0.367466[/C][/ROW]
[ROW][C]22[/C][C]-0.03744[/C][C]-0.7327[/C][C]0.232088[/C][/ROW]
[ROW][C]23[/C][C]0.045748[/C][C]0.8953[/C][C]0.185592[/C][/ROW]
[ROW][C]24[/C][C]-0.089164[/C][C]-1.745[/C][C]0.040895[/C][/ROW]
[ROW][C]25[/C][C]0.15436[/C][C]3.0209[/C][C]0.001345[/C][/ROW]
[ROW][C]26[/C][C]-0.134418[/C][C]-2.6306[/C][C]0.004434[/C][/ROW]
[ROW][C]27[/C][C]0.026558[/C][C]0.5197[/C][C]0.301772[/C][/ROW]
[ROW][C]28[/C][C]0.053799[/C][C]1.0529[/C][C]0.146534[/C][/ROW]
[ROW][C]29[/C][C]-0.103186[/C][C]-2.0194[/C][C]0.022071[/C][/ROW]
[ROW][C]30[/C][C]0.078328[/C][C]1.5329[/C][C]0.063061[/C][/ROW]
[ROW][C]31[/C][C]-0.04163[/C][C]-0.8147[/C][C]0.20787[/C][/ROW]
[ROW][C]32[/C][C]-0.037839[/C][C]-0.7405[/C][C]0.22972[/C][/ROW]
[ROW][C]33[/C][C]0.056997[/C][C]1.1154[/C][C]0.13268[/C][/ROW]
[ROW][C]34[/C][C]0.043078[/C][C]0.843[/C][C]0.199864[/C][/ROW]
[ROW][C]35[/C][C]0.052832[/C][C]1.0339[/C][C]0.15091[/C][/ROW]
[ROW][C]36[/C][C]-0.03301[/C][C]-0.646[/C][C]0.259327[/C][/ROW]
[ROW][C]37[/C][C]-0.04189[/C][C]-0.8198[/C][C]0.20642[/C][/ROW]
[ROW][C]38[/C][C]0.089013[/C][C]1.742[/C][C]0.041154[/C][/ROW]
[ROW][C]39[/C][C]-0.002201[/C][C]-0.0431[/C][C]0.482835[/C][/ROW]
[ROW][C]40[/C][C]-0.060661[/C][C]-1.1872[/C][C]0.117951[/C][/ROW]
[ROW][C]41[/C][C]0.115555[/C][C]2.2615[/C][C]0.012145[/C][/ROW]
[ROW][C]42[/C][C]-0.127836[/C][C]-2.5018[/C][C]0.006386[/C][/ROW]
[ROW][C]43[/C][C]0.109359[/C][C]2.1402[/C][C]0.016485[/C][/ROW]
[ROW][C]44[/C][C]0.044581[/C][C]0.8725[/C][C]0.191752[/C][/ROW]
[ROW][C]45[/C][C]-0.058219[/C][C]-1.1394[/C][C]0.12763[/C][/ROW]
[ROW][C]46[/C][C]0.014202[/C][C]0.2779[/C][C]0.390602[/C][/ROW]
[ROW][C]47[/C][C]-0.094699[/C][C]-1.8533[/C][C]0.032304[/C][/ROW]
[ROW][C]48[/C][C]0.030132[/C][C]0.5897[/C][C]0.277868[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230855&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230855&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
1-0.20797-4.072.9e-05
2-0.097235-1.90290.0289
3-0.035198-0.68880.245674
40.0002430.00470.498108
50.0935181.83020.033999
6-0.080635-1.57810.057689
70.0189230.37030.355669
8-0.053422-1.04550.148229
90.0123660.2420.404449
100.1022682.00140.023025
110.0728221.42520.077462
12-0.386967-7.57310
13-0.001294-0.02530.489907
140.0524931.02730.152463
150.0529571.03640.150337
160.0067250.13160.447683
17-0.091316-1.78710.037357
180.0637511.24760.106464
19-0.045345-0.88740.187707
200.0239250.46820.319948
21-0.017313-0.33880.367466
22-0.03744-0.73270.232088
230.0457480.89530.185592
24-0.089164-1.7450.040895
250.154363.02090.001345
26-0.134418-2.63060.004434
270.0265580.51970.301772
280.0537991.05290.146534
29-0.103186-2.01940.022071
300.0783281.53290.063061
31-0.04163-0.81470.20787
32-0.037839-0.74050.22972
330.0569971.11540.13268
340.0430780.8430.199864
350.0528321.03390.15091
36-0.03301-0.6460.259327
37-0.04189-0.81980.20642
380.0890131.7420.041154
39-0.002201-0.04310.482835
40-0.060661-1.18720.117951
410.1155552.26150.012145
42-0.127836-2.50180.006386
430.1093592.14020.016485
440.0445810.87250.191752
45-0.058219-1.13940.12763
460.0142020.27790.390602
47-0.094699-1.85330.032304
480.0301320.58970.277868







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.20797-4.072.9e-05
2-0.146837-2.87370.002142
3-0.094995-1.85910.031891
4-0.048379-0.94680.17217
50.0722211.41340.079177
6-0.052226-1.02210.153695
70.0091010.17810.429362
8-0.058979-1.15420.124562
9-0.018035-0.3530.362159
100.0868351.69940.045028
110.1343942.63010.004439
12-0.35619-6.97080
13-0.15685-3.06960.001148
14-0.081144-1.5880.056553
15-0.015302-0.29950.382372
160.0004240.00830.49669
17-0.025038-0.490.312206
18-0.004996-0.09780.461084
19-0.045533-0.89110.18672
20-0.051263-1.00320.15819
21-0.053194-1.0410.14926
220.0116850.22870.409619
230.0993751.94480.026265
24-0.248527-4.86381e-06
250.0141260.27650.391174
26-0.174387-3.41280.000356
270.0001840.00360.498561
280.0552131.08050.14029
29-0.134965-2.64130.004298
300.0096330.18850.425285
31-0.05349-1.04680.147921
32-0.159108-3.11380.000993
33-0.004222-0.08260.467096
340.0737421.44320.074896
350.1462362.86190.002221
36-0.129488-2.53410.005835
37-0.008038-0.15730.437546
38-0.080134-1.56820.058825
390.0521961.02150.153834
400.0017750.03470.486155
410.0419160.82030.206273
42-0.07204-1.40980.079699
430.0304280.59550.275933
44-0.022891-0.4480.327208
45-0.019217-0.37610.353531
460.0825891.61630.053426
470.0977061.91210.028302
48-0.159983-3.13090.000938

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.20797 & -4.07 & 2.9e-05 \tabularnewline
2 & -0.146837 & -2.8737 & 0.002142 \tabularnewline
3 & -0.094995 & -1.8591 & 0.031891 \tabularnewline
4 & -0.048379 & -0.9468 & 0.17217 \tabularnewline
5 & 0.072221 & 1.4134 & 0.079177 \tabularnewline
6 & -0.052226 & -1.0221 & 0.153695 \tabularnewline
7 & 0.009101 & 0.1781 & 0.429362 \tabularnewline
8 & -0.058979 & -1.1542 & 0.124562 \tabularnewline
9 & -0.018035 & -0.353 & 0.362159 \tabularnewline
10 & 0.086835 & 1.6994 & 0.045028 \tabularnewline
11 & 0.134394 & 2.6301 & 0.004439 \tabularnewline
12 & -0.35619 & -6.9708 & 0 \tabularnewline
13 & -0.15685 & -3.0696 & 0.001148 \tabularnewline
14 & -0.081144 & -1.588 & 0.056553 \tabularnewline
15 & -0.015302 & -0.2995 & 0.382372 \tabularnewline
16 & 0.000424 & 0.0083 & 0.49669 \tabularnewline
17 & -0.025038 & -0.49 & 0.312206 \tabularnewline
18 & -0.004996 & -0.0978 & 0.461084 \tabularnewline
19 & -0.045533 & -0.8911 & 0.18672 \tabularnewline
20 & -0.051263 & -1.0032 & 0.15819 \tabularnewline
21 & -0.053194 & -1.041 & 0.14926 \tabularnewline
22 & 0.011685 & 0.2287 & 0.409619 \tabularnewline
23 & 0.099375 & 1.9448 & 0.026265 \tabularnewline
24 & -0.248527 & -4.8638 & 1e-06 \tabularnewline
25 & 0.014126 & 0.2765 & 0.391174 \tabularnewline
26 & -0.174387 & -3.4128 & 0.000356 \tabularnewline
27 & 0.000184 & 0.0036 & 0.498561 \tabularnewline
28 & 0.055213 & 1.0805 & 0.14029 \tabularnewline
29 & -0.134965 & -2.6413 & 0.004298 \tabularnewline
30 & 0.009633 & 0.1885 & 0.425285 \tabularnewline
31 & -0.05349 & -1.0468 & 0.147921 \tabularnewline
32 & -0.159108 & -3.1138 & 0.000993 \tabularnewline
33 & -0.004222 & -0.0826 & 0.467096 \tabularnewline
34 & 0.073742 & 1.4432 & 0.074896 \tabularnewline
35 & 0.146236 & 2.8619 & 0.002221 \tabularnewline
36 & -0.129488 & -2.5341 & 0.005835 \tabularnewline
37 & -0.008038 & -0.1573 & 0.437546 \tabularnewline
38 & -0.080134 & -1.5682 & 0.058825 \tabularnewline
39 & 0.052196 & 1.0215 & 0.153834 \tabularnewline
40 & 0.001775 & 0.0347 & 0.486155 \tabularnewline
41 & 0.041916 & 0.8203 & 0.206273 \tabularnewline
42 & -0.07204 & -1.4098 & 0.079699 \tabularnewline
43 & 0.030428 & 0.5955 & 0.275933 \tabularnewline
44 & -0.022891 & -0.448 & 0.327208 \tabularnewline
45 & -0.019217 & -0.3761 & 0.353531 \tabularnewline
46 & 0.082589 & 1.6163 & 0.053426 \tabularnewline
47 & 0.097706 & 1.9121 & 0.028302 \tabularnewline
48 & -0.159983 & -3.1309 & 0.000938 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230855&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]-0.20797[/C][C]-4.07[/C][C]2.9e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.146837[/C][C]-2.8737[/C][C]0.002142[/C][/ROW]
[ROW][C]3[/C][C]-0.094995[/C][C]-1.8591[/C][C]0.031891[/C][/ROW]
[ROW][C]4[/C][C]-0.048379[/C][C]-0.9468[/C][C]0.17217[/C][/ROW]
[ROW][C]5[/C][C]0.072221[/C][C]1.4134[/C][C]0.079177[/C][/ROW]
[ROW][C]6[/C][C]-0.052226[/C][C]-1.0221[/C][C]0.153695[/C][/ROW]
[ROW][C]7[/C][C]0.009101[/C][C]0.1781[/C][C]0.429362[/C][/ROW]
[ROW][C]8[/C][C]-0.058979[/C][C]-1.1542[/C][C]0.124562[/C][/ROW]
[ROW][C]9[/C][C]-0.018035[/C][C]-0.353[/C][C]0.362159[/C][/ROW]
[ROW][C]10[/C][C]0.086835[/C][C]1.6994[/C][C]0.045028[/C][/ROW]
[ROW][C]11[/C][C]0.134394[/C][C]2.6301[/C][C]0.004439[/C][/ROW]
[ROW][C]12[/C][C]-0.35619[/C][C]-6.9708[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.15685[/C][C]-3.0696[/C][C]0.001148[/C][/ROW]
[ROW][C]14[/C][C]-0.081144[/C][C]-1.588[/C][C]0.056553[/C][/ROW]
[ROW][C]15[/C][C]-0.015302[/C][C]-0.2995[/C][C]0.382372[/C][/ROW]
[ROW][C]16[/C][C]0.000424[/C][C]0.0083[/C][C]0.49669[/C][/ROW]
[ROW][C]17[/C][C]-0.025038[/C][C]-0.49[/C][C]0.312206[/C][/ROW]
[ROW][C]18[/C][C]-0.004996[/C][C]-0.0978[/C][C]0.461084[/C][/ROW]
[ROW][C]19[/C][C]-0.045533[/C][C]-0.8911[/C][C]0.18672[/C][/ROW]
[ROW][C]20[/C][C]-0.051263[/C][C]-1.0032[/C][C]0.15819[/C][/ROW]
[ROW][C]21[/C][C]-0.053194[/C][C]-1.041[/C][C]0.14926[/C][/ROW]
[ROW][C]22[/C][C]0.011685[/C][C]0.2287[/C][C]0.409619[/C][/ROW]
[ROW][C]23[/C][C]0.099375[/C][C]1.9448[/C][C]0.026265[/C][/ROW]
[ROW][C]24[/C][C]-0.248527[/C][C]-4.8638[/C][C]1e-06[/C][/ROW]
[ROW][C]25[/C][C]0.014126[/C][C]0.2765[/C][C]0.391174[/C][/ROW]
[ROW][C]26[/C][C]-0.174387[/C][C]-3.4128[/C][C]0.000356[/C][/ROW]
[ROW][C]27[/C][C]0.000184[/C][C]0.0036[/C][C]0.498561[/C][/ROW]
[ROW][C]28[/C][C]0.055213[/C][C]1.0805[/C][C]0.14029[/C][/ROW]
[ROW][C]29[/C][C]-0.134965[/C][C]-2.6413[/C][C]0.004298[/C][/ROW]
[ROW][C]30[/C][C]0.009633[/C][C]0.1885[/C][C]0.425285[/C][/ROW]
[ROW][C]31[/C][C]-0.05349[/C][C]-1.0468[/C][C]0.147921[/C][/ROW]
[ROW][C]32[/C][C]-0.159108[/C][C]-3.1138[/C][C]0.000993[/C][/ROW]
[ROW][C]33[/C][C]-0.004222[/C][C]-0.0826[/C][C]0.467096[/C][/ROW]
[ROW][C]34[/C][C]0.073742[/C][C]1.4432[/C][C]0.074896[/C][/ROW]
[ROW][C]35[/C][C]0.146236[/C][C]2.8619[/C][C]0.002221[/C][/ROW]
[ROW][C]36[/C][C]-0.129488[/C][C]-2.5341[/C][C]0.005835[/C][/ROW]
[ROW][C]37[/C][C]-0.008038[/C][C]-0.1573[/C][C]0.437546[/C][/ROW]
[ROW][C]38[/C][C]-0.080134[/C][C]-1.5682[/C][C]0.058825[/C][/ROW]
[ROW][C]39[/C][C]0.052196[/C][C]1.0215[/C][C]0.153834[/C][/ROW]
[ROW][C]40[/C][C]0.001775[/C][C]0.0347[/C][C]0.486155[/C][/ROW]
[ROW][C]41[/C][C]0.041916[/C][C]0.8203[/C][C]0.206273[/C][/ROW]
[ROW][C]42[/C][C]-0.07204[/C][C]-1.4098[/C][C]0.079699[/C][/ROW]
[ROW][C]43[/C][C]0.030428[/C][C]0.5955[/C][C]0.275933[/C][/ROW]
[ROW][C]44[/C][C]-0.022891[/C][C]-0.448[/C][C]0.327208[/C][/ROW]
[ROW][C]45[/C][C]-0.019217[/C][C]-0.3761[/C][C]0.353531[/C][/ROW]
[ROW][C]46[/C][C]0.082589[/C][C]1.6163[/C][C]0.053426[/C][/ROW]
[ROW][C]47[/C][C]0.097706[/C][C]1.9121[/C][C]0.028302[/C][/ROW]
[ROW][C]48[/C][C]-0.159983[/C][C]-3.1309[/C][C]0.000938[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230855&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230855&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
1-0.20797-4.072.9e-05
2-0.146837-2.87370.002142
3-0.094995-1.85910.031891
4-0.048379-0.94680.17217
50.0722211.41340.079177
6-0.052226-1.02210.153695
70.0091010.17810.429362
8-0.058979-1.15420.124562
9-0.018035-0.3530.362159
100.0868351.69940.045028
110.1343942.63010.004439
12-0.35619-6.97080
13-0.15685-3.06960.001148
14-0.081144-1.5880.056553
15-0.015302-0.29950.382372
160.0004240.00830.49669
17-0.025038-0.490.312206
18-0.004996-0.09780.461084
19-0.045533-0.89110.18672
20-0.051263-1.00320.15819
21-0.053194-1.0410.14926
220.0116850.22870.409619
230.0993751.94480.026265
24-0.248527-4.86381e-06
250.0141260.27650.391174
26-0.174387-3.41280.000356
270.0001840.00360.498561
280.0552131.08050.14029
29-0.134965-2.64130.004298
300.0096330.18850.425285
31-0.05349-1.04680.147921
32-0.159108-3.11380.000993
33-0.004222-0.08260.467096
340.0737421.44320.074896
350.1462362.86190.002221
36-0.129488-2.53410.005835
37-0.008038-0.15730.437546
38-0.080134-1.56820.058825
390.0521961.02150.153834
400.0017750.03470.486155
410.0419160.82030.206273
42-0.07204-1.40980.079699
430.0304280.59550.275933
44-0.022891-0.4480.327208
45-0.019217-0.37610.353531
460.0825891.61630.053426
470.0977061.91210.028302
48-0.159983-3.13090.000938



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 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')