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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 29 May 2009 05:57:07 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/29/t12435983344zr5zdggnf4dim1.htm/, Retrieved Sat, 27 Apr 2024 17:16:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40764, Retrieved Sat, 27 Apr 2024 17:16:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelation -...] [2009-05-29 11:57:07] [946afef1f31655e4e01d6b8ef4c25a2b] [Current]
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Dataseries X:
428800
424800
403400
398400
393500
380500
398300
387300
370400
372800
444600
449900
458100
424800
420600
400100
393000
387100
377500
400400
391400
363600
431000
441700
448500
415600
408000
416600
409300
387600
394500
407600
378500
359600
435700
433800
427700
413300
379500
379300
353700
378200
380600
394000
374000
375000
437600
443900
488800
463900
440000
453800
451600
453400
461400
509100
540600
555100
677400
694600
750100
733900
709300
720500
693200
687200
686800
720900
653100
624700
690000
717800
736500
699900
675600
635600
632500
594900
604000
620800
578400
571200
627400
657700
674100
672800
615300
609100
607600
566900
572700
589200
534800
543100
591100
624800
665300
642600
608700
594500
563800
596100
597600
633100
591000
584200
655800
670700
699700
712900
652000
635100
603100
610100
602000
597600
585400
567100
620600
646200
644800
645200
644800
593000
569100
518800
538700
554600
507900
488400
563300
592400
598100
546300
516100
518500
477400
483400
469400
501300
457400
446700
501900
550400
593700
548900
534200
550500
541800
569300
587400
627700
607000
629500
704600
767700
812200
824600
856300
812200
764100
801700
806000
867200
801600
817500
920900
959700
997700
949100
910900
920400
914200
926300
906400
926100
902500
895300
979900
1009700
1043800
979800
921600
923500
914500
891700
916000
931700
902400
893700
941500
980100
1006900
949200
883200
849900
839200
803900
797900
830800
753300
764100
807600
853700
886200
815700
743000
753600
724800
709600
721900




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40764&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40764&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40764&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.97765214.20120
20.94961513.7940
30.92380113.4190
40.90111713.08950
50.88272212.82230
60.85993412.49130
70.84038812.20730
80.82098411.92550
90.80476711.68990
100.7932711.52290
110.7875211.43940
120.7748711.25560
130.73806310.7210
140.69349110.07350
150.6519149.46960
160.6145678.92710
170.5826398.46330
180.5503647.99450
190.5203997.55920
200.4934487.16770
210.4726046.8650
220.4550026.60930
230.4447636.46060
240.4294916.23870
250.3932885.71280
260.3514585.10520
270.3125364.53985e-06
280.2812764.08583.1e-05
290.2556543.71360.000131
300.2296963.33650.000501
310.2078873.01970.001421
320.1878452.72860.003448
330.1737092.52330.006182
340.1643782.38770.008917
350.1620622.35410.009743
360.1549872.25130.012698
370.1270121.84490.033223
380.0938921.36390.087032
390.0644580.93630.175094
400.0414120.60150.274061
410.0234060.340.367102
420.005540.08050.467969
43-0.008782-0.12760.449307
44-0.018999-0.2760.391421
45-0.02471-0.35890.360001
46-0.026341-0.38260.351193
47-0.022971-0.33370.369477
48-0.024464-0.35540.361338

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.977652 & 14.2012 & 0 \tabularnewline
2 & 0.949615 & 13.794 & 0 \tabularnewline
3 & 0.923801 & 13.419 & 0 \tabularnewline
4 & 0.901117 & 13.0895 & 0 \tabularnewline
5 & 0.882722 & 12.8223 & 0 \tabularnewline
6 & 0.859934 & 12.4913 & 0 \tabularnewline
7 & 0.840388 & 12.2073 & 0 \tabularnewline
8 & 0.820984 & 11.9255 & 0 \tabularnewline
9 & 0.804767 & 11.6899 & 0 \tabularnewline
10 & 0.79327 & 11.5229 & 0 \tabularnewline
11 & 0.78752 & 11.4394 & 0 \tabularnewline
12 & 0.77487 & 11.2556 & 0 \tabularnewline
13 & 0.738063 & 10.721 & 0 \tabularnewline
14 & 0.693491 & 10.0735 & 0 \tabularnewline
15 & 0.651914 & 9.4696 & 0 \tabularnewline
16 & 0.614567 & 8.9271 & 0 \tabularnewline
17 & 0.582639 & 8.4633 & 0 \tabularnewline
18 & 0.550364 & 7.9945 & 0 \tabularnewline
19 & 0.520399 & 7.5592 & 0 \tabularnewline
20 & 0.493448 & 7.1677 & 0 \tabularnewline
21 & 0.472604 & 6.865 & 0 \tabularnewline
22 & 0.455002 & 6.6093 & 0 \tabularnewline
23 & 0.444763 & 6.4606 & 0 \tabularnewline
24 & 0.429491 & 6.2387 & 0 \tabularnewline
25 & 0.393288 & 5.7128 & 0 \tabularnewline
26 & 0.351458 & 5.1052 & 0 \tabularnewline
27 & 0.312536 & 4.5398 & 5e-06 \tabularnewline
28 & 0.281276 & 4.0858 & 3.1e-05 \tabularnewline
29 & 0.255654 & 3.7136 & 0.000131 \tabularnewline
30 & 0.229696 & 3.3365 & 0.000501 \tabularnewline
31 & 0.207887 & 3.0197 & 0.001421 \tabularnewline
32 & 0.187845 & 2.7286 & 0.003448 \tabularnewline
33 & 0.173709 & 2.5233 & 0.006182 \tabularnewline
34 & 0.164378 & 2.3877 & 0.008917 \tabularnewline
35 & 0.162062 & 2.3541 & 0.009743 \tabularnewline
36 & 0.154987 & 2.2513 & 0.012698 \tabularnewline
37 & 0.127012 & 1.8449 & 0.033223 \tabularnewline
38 & 0.093892 & 1.3639 & 0.087032 \tabularnewline
39 & 0.064458 & 0.9363 & 0.175094 \tabularnewline
40 & 0.041412 & 0.6015 & 0.274061 \tabularnewline
41 & 0.023406 & 0.34 & 0.367102 \tabularnewline
42 & 0.00554 & 0.0805 & 0.467969 \tabularnewline
43 & -0.008782 & -0.1276 & 0.449307 \tabularnewline
44 & -0.018999 & -0.276 & 0.391421 \tabularnewline
45 & -0.02471 & -0.3589 & 0.360001 \tabularnewline
46 & -0.026341 & -0.3826 & 0.351193 \tabularnewline
47 & -0.022971 & -0.3337 & 0.369477 \tabularnewline
48 & -0.024464 & -0.3554 & 0.361338 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40764&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]0.977652[/C][C]14.2012[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.949615[/C][C]13.794[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.923801[/C][C]13.419[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.901117[/C][C]13.0895[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.882722[/C][C]12.8223[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.859934[/C][C]12.4913[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.840388[/C][C]12.2073[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.820984[/C][C]11.9255[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.804767[/C][C]11.6899[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.79327[/C][C]11.5229[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.78752[/C][C]11.4394[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.77487[/C][C]11.2556[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.738063[/C][C]10.721[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.693491[/C][C]10.0735[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.651914[/C][C]9.4696[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.614567[/C][C]8.9271[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.582639[/C][C]8.4633[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.550364[/C][C]7.9945[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.520399[/C][C]7.5592[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.493448[/C][C]7.1677[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.472604[/C][C]6.865[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.455002[/C][C]6.6093[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.444763[/C][C]6.4606[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.429491[/C][C]6.2387[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.393288[/C][C]5.7128[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.351458[/C][C]5.1052[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.312536[/C][C]4.5398[/C][C]5e-06[/C][/ROW]
[ROW][C]28[/C][C]0.281276[/C][C]4.0858[/C][C]3.1e-05[/C][/ROW]
[ROW][C]29[/C][C]0.255654[/C][C]3.7136[/C][C]0.000131[/C][/ROW]
[ROW][C]30[/C][C]0.229696[/C][C]3.3365[/C][C]0.000501[/C][/ROW]
[ROW][C]31[/C][C]0.207887[/C][C]3.0197[/C][C]0.001421[/C][/ROW]
[ROW][C]32[/C][C]0.187845[/C][C]2.7286[/C][C]0.003448[/C][/ROW]
[ROW][C]33[/C][C]0.173709[/C][C]2.5233[/C][C]0.006182[/C][/ROW]
[ROW][C]34[/C][C]0.164378[/C][C]2.3877[/C][C]0.008917[/C][/ROW]
[ROW][C]35[/C][C]0.162062[/C][C]2.3541[/C][C]0.009743[/C][/ROW]
[ROW][C]36[/C][C]0.154987[/C][C]2.2513[/C][C]0.012698[/C][/ROW]
[ROW][C]37[/C][C]0.127012[/C][C]1.8449[/C][C]0.033223[/C][/ROW]
[ROW][C]38[/C][C]0.093892[/C][C]1.3639[/C][C]0.087032[/C][/ROW]
[ROW][C]39[/C][C]0.064458[/C][C]0.9363[/C][C]0.175094[/C][/ROW]
[ROW][C]40[/C][C]0.041412[/C][C]0.6015[/C][C]0.274061[/C][/ROW]
[ROW][C]41[/C][C]0.023406[/C][C]0.34[/C][C]0.367102[/C][/ROW]
[ROW][C]42[/C][C]0.00554[/C][C]0.0805[/C][C]0.467969[/C][/ROW]
[ROW][C]43[/C][C]-0.008782[/C][C]-0.1276[/C][C]0.449307[/C][/ROW]
[ROW][C]44[/C][C]-0.018999[/C][C]-0.276[/C][C]0.391421[/C][/ROW]
[ROW][C]45[/C][C]-0.02471[/C][C]-0.3589[/C][C]0.360001[/C][/ROW]
[ROW][C]46[/C][C]-0.026341[/C][C]-0.3826[/C][C]0.351193[/C][/ROW]
[ROW][C]47[/C][C]-0.022971[/C][C]-0.3337[/C][C]0.369477[/C][/ROW]
[ROW][C]48[/C][C]-0.024464[/C][C]-0.3554[/C][C]0.361338[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40764&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40764&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
10.97765214.20120
20.94961513.7940
30.92380113.4190
40.90111713.08950
50.88272212.82230
60.85993412.49130
70.84038812.20730
80.82098411.92550
90.80476711.68990
100.7932711.52290
110.7875211.43940
120.7748711.25560
130.73806310.7210
140.69349110.07350
150.6519149.46960
160.6145678.92710
170.5826398.46330
180.5503647.99450
190.5203997.55920
200.4934487.16770
210.4726046.8650
220.4550026.60930
230.4447636.46060
240.4294916.23870
250.3932885.71280
260.3514585.10520
270.3125364.53985e-06
280.2812764.08583.1e-05
290.2556543.71360.000131
300.2296963.33650.000501
310.2078873.01970.001421
320.1878452.72860.003448
330.1737092.52330.006182
340.1643782.38770.008917
350.1620622.35410.009743
360.1549872.25130.012698
370.1270121.84490.033223
380.0938921.36390.087032
390.0644580.93630.175094
400.0414120.60150.274061
410.0234060.340.367102
420.005540.08050.467969
43-0.008782-0.12760.449307
44-0.018999-0.2760.391421
45-0.02471-0.35890.360001
46-0.026341-0.38260.351193
47-0.022971-0.33370.369477
48-0.024464-0.35540.361338







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97765214.20120
2-0.140021-2.03390.021605
30.0532040.77280.220245
40.0434920.63180.264113
50.0736971.07050.142805
6-0.129467-1.88060.030701
70.1081451.57090.058853
8-0.037434-0.54380.293592
90.0776771.12830.130231
100.0646720.93940.174296
110.1473382.14020.016743
12-0.225963-3.28230.000602
13-0.509034-7.39410
14-0.137961-2.0040.023174
150.0680140.9880.162153
16-0.008662-0.12580.449995
170.1000091.45270.073895
180.0944431.37190.085782
190.0148250.21530.414856
20-0.003191-0.04630.481539
210.1203541.74820.040938
22-0.120926-1.75660.040222
230.0466340.67740.249447
24-0.017133-0.24890.401851
25-0.239119-3.47340.000312
26-0.031882-0.46310.321879
270.1296791.88370.030491
280.0840311.22060.111796
290.0244110.35460.361623
300.0510880.74210.229426
310.0660940.96010.16906
32-0.153672-2.23220.013326
330.0152860.2220.412251
340.0146420.21270.41589
35-0.003309-0.04810.480857
36-0.05647-0.82030.206495
37-0.12571-1.8260.034629
38-0.002879-0.04180.483341
390.0793871.15320.125073
400.0124210.18040.428498
41-0.012978-0.18850.425324
420.0135250.19650.422219
430.038740.56270.287107
440.007930.11520.454202
45-0.009-0.13070.448053
46-0.034281-0.4980.309514
47-0.070113-1.01850.154815
48-0.016871-0.24510.403324

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.977652 & 14.2012 & 0 \tabularnewline
2 & -0.140021 & -2.0339 & 0.021605 \tabularnewline
3 & 0.053204 & 0.7728 & 0.220245 \tabularnewline
4 & 0.043492 & 0.6318 & 0.264113 \tabularnewline
5 & 0.073697 & 1.0705 & 0.142805 \tabularnewline
6 & -0.129467 & -1.8806 & 0.030701 \tabularnewline
7 & 0.108145 & 1.5709 & 0.058853 \tabularnewline
8 & -0.037434 & -0.5438 & 0.293592 \tabularnewline
9 & 0.077677 & 1.1283 & 0.130231 \tabularnewline
10 & 0.064672 & 0.9394 & 0.174296 \tabularnewline
11 & 0.147338 & 2.1402 & 0.016743 \tabularnewline
12 & -0.225963 & -3.2823 & 0.000602 \tabularnewline
13 & -0.509034 & -7.3941 & 0 \tabularnewline
14 & -0.137961 & -2.004 & 0.023174 \tabularnewline
15 & 0.068014 & 0.988 & 0.162153 \tabularnewline
16 & -0.008662 & -0.1258 & 0.449995 \tabularnewline
17 & 0.100009 & 1.4527 & 0.073895 \tabularnewline
18 & 0.094443 & 1.3719 & 0.085782 \tabularnewline
19 & 0.014825 & 0.2153 & 0.414856 \tabularnewline
20 & -0.003191 & -0.0463 & 0.481539 \tabularnewline
21 & 0.120354 & 1.7482 & 0.040938 \tabularnewline
22 & -0.120926 & -1.7566 & 0.040222 \tabularnewline
23 & 0.046634 & 0.6774 & 0.249447 \tabularnewline
24 & -0.017133 & -0.2489 & 0.401851 \tabularnewline
25 & -0.239119 & -3.4734 & 0.000312 \tabularnewline
26 & -0.031882 & -0.4631 & 0.321879 \tabularnewline
27 & 0.129679 & 1.8837 & 0.030491 \tabularnewline
28 & 0.084031 & 1.2206 & 0.111796 \tabularnewline
29 & 0.024411 & 0.3546 & 0.361623 \tabularnewline
30 & 0.051088 & 0.7421 & 0.229426 \tabularnewline
31 & 0.066094 & 0.9601 & 0.16906 \tabularnewline
32 & -0.153672 & -2.2322 & 0.013326 \tabularnewline
33 & 0.015286 & 0.222 & 0.412251 \tabularnewline
34 & 0.014642 & 0.2127 & 0.41589 \tabularnewline
35 & -0.003309 & -0.0481 & 0.480857 \tabularnewline
36 & -0.05647 & -0.8203 & 0.206495 \tabularnewline
37 & -0.12571 & -1.826 & 0.034629 \tabularnewline
38 & -0.002879 & -0.0418 & 0.483341 \tabularnewline
39 & 0.079387 & 1.1532 & 0.125073 \tabularnewline
40 & 0.012421 & 0.1804 & 0.428498 \tabularnewline
41 & -0.012978 & -0.1885 & 0.425324 \tabularnewline
42 & 0.013525 & 0.1965 & 0.422219 \tabularnewline
43 & 0.03874 & 0.5627 & 0.287107 \tabularnewline
44 & 0.00793 & 0.1152 & 0.454202 \tabularnewline
45 & -0.009 & -0.1307 & 0.448053 \tabularnewline
46 & -0.034281 & -0.498 & 0.309514 \tabularnewline
47 & -0.070113 & -1.0185 & 0.154815 \tabularnewline
48 & -0.016871 & -0.2451 & 0.403324 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40764&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]0.977652[/C][C]14.2012[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.140021[/C][C]-2.0339[/C][C]0.021605[/C][/ROW]
[ROW][C]3[/C][C]0.053204[/C][C]0.7728[/C][C]0.220245[/C][/ROW]
[ROW][C]4[/C][C]0.043492[/C][C]0.6318[/C][C]0.264113[/C][/ROW]
[ROW][C]5[/C][C]0.073697[/C][C]1.0705[/C][C]0.142805[/C][/ROW]
[ROW][C]6[/C][C]-0.129467[/C][C]-1.8806[/C][C]0.030701[/C][/ROW]
[ROW][C]7[/C][C]0.108145[/C][C]1.5709[/C][C]0.058853[/C][/ROW]
[ROW][C]8[/C][C]-0.037434[/C][C]-0.5438[/C][C]0.293592[/C][/ROW]
[ROW][C]9[/C][C]0.077677[/C][C]1.1283[/C][C]0.130231[/C][/ROW]
[ROW][C]10[/C][C]0.064672[/C][C]0.9394[/C][C]0.174296[/C][/ROW]
[ROW][C]11[/C][C]0.147338[/C][C]2.1402[/C][C]0.016743[/C][/ROW]
[ROW][C]12[/C][C]-0.225963[/C][C]-3.2823[/C][C]0.000602[/C][/ROW]
[ROW][C]13[/C][C]-0.509034[/C][C]-7.3941[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]-0.137961[/C][C]-2.004[/C][C]0.023174[/C][/ROW]
[ROW][C]15[/C][C]0.068014[/C][C]0.988[/C][C]0.162153[/C][/ROW]
[ROW][C]16[/C][C]-0.008662[/C][C]-0.1258[/C][C]0.449995[/C][/ROW]
[ROW][C]17[/C][C]0.100009[/C][C]1.4527[/C][C]0.073895[/C][/ROW]
[ROW][C]18[/C][C]0.094443[/C][C]1.3719[/C][C]0.085782[/C][/ROW]
[ROW][C]19[/C][C]0.014825[/C][C]0.2153[/C][C]0.414856[/C][/ROW]
[ROW][C]20[/C][C]-0.003191[/C][C]-0.0463[/C][C]0.481539[/C][/ROW]
[ROW][C]21[/C][C]0.120354[/C][C]1.7482[/C][C]0.040938[/C][/ROW]
[ROW][C]22[/C][C]-0.120926[/C][C]-1.7566[/C][C]0.040222[/C][/ROW]
[ROW][C]23[/C][C]0.046634[/C][C]0.6774[/C][C]0.249447[/C][/ROW]
[ROW][C]24[/C][C]-0.017133[/C][C]-0.2489[/C][C]0.401851[/C][/ROW]
[ROW][C]25[/C][C]-0.239119[/C][C]-3.4734[/C][C]0.000312[/C][/ROW]
[ROW][C]26[/C][C]-0.031882[/C][C]-0.4631[/C][C]0.321879[/C][/ROW]
[ROW][C]27[/C][C]0.129679[/C][C]1.8837[/C][C]0.030491[/C][/ROW]
[ROW][C]28[/C][C]0.084031[/C][C]1.2206[/C][C]0.111796[/C][/ROW]
[ROW][C]29[/C][C]0.024411[/C][C]0.3546[/C][C]0.361623[/C][/ROW]
[ROW][C]30[/C][C]0.051088[/C][C]0.7421[/C][C]0.229426[/C][/ROW]
[ROW][C]31[/C][C]0.066094[/C][C]0.9601[/C][C]0.16906[/C][/ROW]
[ROW][C]32[/C][C]-0.153672[/C][C]-2.2322[/C][C]0.013326[/C][/ROW]
[ROW][C]33[/C][C]0.015286[/C][C]0.222[/C][C]0.412251[/C][/ROW]
[ROW][C]34[/C][C]0.014642[/C][C]0.2127[/C][C]0.41589[/C][/ROW]
[ROW][C]35[/C][C]-0.003309[/C][C]-0.0481[/C][C]0.480857[/C][/ROW]
[ROW][C]36[/C][C]-0.05647[/C][C]-0.8203[/C][C]0.206495[/C][/ROW]
[ROW][C]37[/C][C]-0.12571[/C][C]-1.826[/C][C]0.034629[/C][/ROW]
[ROW][C]38[/C][C]-0.002879[/C][C]-0.0418[/C][C]0.483341[/C][/ROW]
[ROW][C]39[/C][C]0.079387[/C][C]1.1532[/C][C]0.125073[/C][/ROW]
[ROW][C]40[/C][C]0.012421[/C][C]0.1804[/C][C]0.428498[/C][/ROW]
[ROW][C]41[/C][C]-0.012978[/C][C]-0.1885[/C][C]0.425324[/C][/ROW]
[ROW][C]42[/C][C]0.013525[/C][C]0.1965[/C][C]0.422219[/C][/ROW]
[ROW][C]43[/C][C]0.03874[/C][C]0.5627[/C][C]0.287107[/C][/ROW]
[ROW][C]44[/C][C]0.00793[/C][C]0.1152[/C][C]0.454202[/C][/ROW]
[ROW][C]45[/C][C]-0.009[/C][C]-0.1307[/C][C]0.448053[/C][/ROW]
[ROW][C]46[/C][C]-0.034281[/C][C]-0.498[/C][C]0.309514[/C][/ROW]
[ROW][C]47[/C][C]-0.070113[/C][C]-1.0185[/C][C]0.154815[/C][/ROW]
[ROW][C]48[/C][C]-0.016871[/C][C]-0.2451[/C][C]0.403324[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40764&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40764&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
10.97765214.20120
2-0.140021-2.03390.021605
30.0532040.77280.220245
40.0434920.63180.264113
50.0736971.07050.142805
6-0.129467-1.88060.030701
70.1081451.57090.058853
8-0.037434-0.54380.293592
90.0776771.12830.130231
100.0646720.93940.174296
110.1473382.14020.016743
12-0.225963-3.28230.000602
13-0.509034-7.39410
14-0.137961-2.0040.023174
150.0680140.9880.162153
16-0.008662-0.12580.449995
170.1000091.45270.073895
180.0944431.37190.085782
190.0148250.21530.414856
20-0.003191-0.04630.481539
210.1203541.74820.040938
22-0.120926-1.75660.040222
230.0466340.67740.249447
24-0.017133-0.24890.401851
25-0.239119-3.47340.000312
26-0.031882-0.46310.321879
270.1296791.88370.030491
280.0840311.22060.111796
290.0244110.35460.361623
300.0510880.74210.229426
310.0660940.96010.16906
32-0.153672-2.23220.013326
330.0152860.2220.412251
340.0146420.21270.41589
35-0.003309-0.04810.480857
36-0.05647-0.82030.206495
37-0.12571-1.8260.034629
38-0.002879-0.04180.483341
390.0793871.15320.125073
400.0124210.18040.428498
41-0.012978-0.18850.425324
420.0135250.19650.422219
430.038740.56270.287107
440.007930.11520.454202
45-0.009-0.13070.448053
46-0.034281-0.4980.309514
47-0.070113-1.01850.154815
48-0.016871-0.24510.403324



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')