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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, 03 May 2010 20:20:37 +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/May/03/t127291814068vwx04l8a4w42r.htm/, Retrieved Tue, 16 Apr 2024 08:25:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75308, Retrieved Tue, 16 Apr 2024 08:25:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [opgave6bisoef2] [2010-05-03 20:20:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD    [(Partial) Autocorrelation Function] [opgave6bisoef2] [2010-05-03 20:25:24] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
196.9 
192.1 
201.8 
186.9
  218
214.4
227.5
204.1
225.8
223.7
244.7
243.9
257.3
234.5
251.4
243.8
247.4
245.3
262.5
  270
259.9
262.2
244.9
249.3
268.2
231.2
264.3
252.7
275.5
261.5
275.5
272.3
268.6
270.4
267.7
  275
272.6
248.6
279.4
270.5
292.8
297.8
296.8
290.9
282.8
312.8
303.2
301.4
289.8
279.6
302.2
299.1
319.7
310.9
315.2
338.5
315.6
321.2
318.5
342.7
261.4
  287
331.5
326.9
338.6
  337
358.4
344.5
345.7
344.1
317.4
354.5
345.2
314.1
352.5
361.2
365.9
332.5
  364
359.1
345.6
366.9
370.2
359.9
366.6
336.3
368.5
374.2
384.3
358.9
407.7
433.3
404.7
392.7
409.7
416.5
414.3
404.3
421.4
372.6
404.7
420.2
438.4
449.1
445.8
413.8
420.5
442.3
438.9
394.5
416.8
402.9
424.5
432.3
484.1
492.7
496.3
471.9
491.2
512.9
482.4
407.9
448.5
431.1
498.8
497.1
517.1
487.7
512.5
550.1
532.5
524.1
515.7
  461
529.3
467.4
559.8
536.5
531.9
546.5
547.4
536.1
482.8
  551
532.9
484.1
554.8
  537
  558
511.4
502.9
558.6
545.1
574.3
542.2
  600
588.6
524.4
618.5
580.9
557.2
571.2
597.5
601.7
558.9
600.9
  601
615.7
578.1
495.9
526.8
522.1
605.1
574.4
609.7
580.7
565.1
590.7
571.5
601.3
567.3
467.9
588.9
579.4
502.6
568.7
  616
586.2
575.5
599.9
568.2
  516
493.4
496.8
529.9
491.7
543.2
490.8
554.7
625.7
  605
645.2
645.2
611.8
600.3
549.8
635.5
617.7
643.5
485.7
689.5
  692
677.3
704.7
668.6
717.8
689.8
640.4
675.2
528.1
  538
527.2
655.6
650.6
623.7
748.4
727.4
750.5
678.9
659.5
691.9
639.8
663.8
572.9
592.5
734.8
696.1
589.2
662.9
661.2
672.1
583.7
705.5
  631
733.3
674.9
695.5
634.1
630.6
635.2
554.1
623.9
679.3
565.6
564.1
637.2
650.8
602.7
587.5
619.2
616.5
637.9
557.9
  594
668.7
603.3
674.5
573.4
  706
693.7
627.5
550.7
592.3
660.2
597.3
  641
663.6
595.9
638.4
665.4
671.4
  637
685.7
705.8
704.8
734.4
674.2
748.6
763.4
  658
627.5
528.9
488.3
575.5
735.6
685.3
613.6
629.5
634.7
652.6
728.3
634.3
690.7
676.3
675.4
595.6
712.4
735.8
544.4
  567
  510
  564
630.7
496.7
660.9
601.2
655.2
591.6
606.1
560.7
368.3
371.6
413.9
413.9
  389
399.2
429.8
395.6
  472
  486
  525
  396
  511
  525
  492
  517
  525
  474
  539
  468
  543
  532
  565
  535
  534
  546
  494
  552
  511
  451
  537
  494
  549
  544
  598
  583
  582
  589
  578
  561
  592
  504
  545
  547
  585
  562
  520
  581
  590
  562
  548
  567
  542
  473
  531
  462
  479
  533
  552
  547
  562
  524
  479
  445
  406
  475
  589
  495
  484
  536
  555
  565
  564
  573
  569
  588
  546
  508
  560
  558
  516
  549
  595
  586
  597
  592
  538
  590
  576
  451
  538
  555
  532
  530
  553
  626
  601
  573
  569
  562
  468
  483
  460
  411
  458
  455
  600
  605
  545
  549
  415
  568
  577
  517
  558
  518
  489
  502
  569
  540
  550
  557
  542
  542
  582
  525
  584
  562
  639
  613
  604
  613
  625
  654
  638




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=75308&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=75308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75308&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
10.91874819.59760
20.89075419.00040
30.87103118.57970
40.85064518.14490
50.83452117.80090
60.80925717.2620
70.80981717.2740
80.79682216.99680
90.79543416.96720
100.80076517.08090
110.78794216.80740
120.80668717.20720
130.77561216.54440
140.76607516.34090
150.74752615.94530
160.73661715.71260
170.72905215.55120
180.70519215.04230
190.70385915.01380
200.6931914.78630
210.69040814.72690
220.68766814.66850
230.66324314.14750
240.68115314.52950
250.65569713.98650
260.65112513.8890
270.64138513.68120
280.63677813.58290
290.62718813.37840
300.60913512.99330
310.60194412.83990
320.58922712.56860
330.58882212.560
340.59139712.61490
350.57241112.20990
360.58582512.49610
370.56012911.9480
380.57075412.17460
390.55899611.92380
400.54199911.56120
410.53621911.43790
420.51992111.09030
430.51903111.07130
440.50214210.71110
450.50102110.68710
460.50585510.79030
470.49044210.46150
480.50829210.84220

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.918748 & 19.5976 & 0 \tabularnewline
2 & 0.890754 & 19.0004 & 0 \tabularnewline
3 & 0.871031 & 18.5797 & 0 \tabularnewline
4 & 0.850645 & 18.1449 & 0 \tabularnewline
5 & 0.834521 & 17.8009 & 0 \tabularnewline
6 & 0.809257 & 17.262 & 0 \tabularnewline
7 & 0.809817 & 17.274 & 0 \tabularnewline
8 & 0.796822 & 16.9968 & 0 \tabularnewline
9 & 0.795434 & 16.9672 & 0 \tabularnewline
10 & 0.800765 & 17.0809 & 0 \tabularnewline
11 & 0.787942 & 16.8074 & 0 \tabularnewline
12 & 0.806687 & 17.2072 & 0 \tabularnewline
13 & 0.775612 & 16.5444 & 0 \tabularnewline
14 & 0.766075 & 16.3409 & 0 \tabularnewline
15 & 0.747526 & 15.9453 & 0 \tabularnewline
16 & 0.736617 & 15.7126 & 0 \tabularnewline
17 & 0.729052 & 15.5512 & 0 \tabularnewline
18 & 0.705192 & 15.0423 & 0 \tabularnewline
19 & 0.703859 & 15.0138 & 0 \tabularnewline
20 & 0.69319 & 14.7863 & 0 \tabularnewline
21 & 0.690408 & 14.7269 & 0 \tabularnewline
22 & 0.687668 & 14.6685 & 0 \tabularnewline
23 & 0.663243 & 14.1475 & 0 \tabularnewline
24 & 0.681153 & 14.5295 & 0 \tabularnewline
25 & 0.655697 & 13.9865 & 0 \tabularnewline
26 & 0.651125 & 13.889 & 0 \tabularnewline
27 & 0.641385 & 13.6812 & 0 \tabularnewline
28 & 0.636778 & 13.5829 & 0 \tabularnewline
29 & 0.627188 & 13.3784 & 0 \tabularnewline
30 & 0.609135 & 12.9933 & 0 \tabularnewline
31 & 0.601944 & 12.8399 & 0 \tabularnewline
32 & 0.589227 & 12.5686 & 0 \tabularnewline
33 & 0.588822 & 12.56 & 0 \tabularnewline
34 & 0.591397 & 12.6149 & 0 \tabularnewline
35 & 0.572411 & 12.2099 & 0 \tabularnewline
36 & 0.585825 & 12.4961 & 0 \tabularnewline
37 & 0.560129 & 11.948 & 0 \tabularnewline
38 & 0.570754 & 12.1746 & 0 \tabularnewline
39 & 0.558996 & 11.9238 & 0 \tabularnewline
40 & 0.541999 & 11.5612 & 0 \tabularnewline
41 & 0.536219 & 11.4379 & 0 \tabularnewline
42 & 0.519921 & 11.0903 & 0 \tabularnewline
43 & 0.519031 & 11.0713 & 0 \tabularnewline
44 & 0.502142 & 10.7111 & 0 \tabularnewline
45 & 0.501021 & 10.6871 & 0 \tabularnewline
46 & 0.505855 & 10.7903 & 0 \tabularnewline
47 & 0.490442 & 10.4615 & 0 \tabularnewline
48 & 0.508292 & 10.8422 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75308&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]0.918748[/C][C]19.5976[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.890754[/C][C]19.0004[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.871031[/C][C]18.5797[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.850645[/C][C]18.1449[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.834521[/C][C]17.8009[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.809257[/C][C]17.262[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.809817[/C][C]17.274[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.796822[/C][C]16.9968[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.795434[/C][C]16.9672[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.800765[/C][C]17.0809[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.787942[/C][C]16.8074[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.806687[/C][C]17.2072[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.775612[/C][C]16.5444[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.766075[/C][C]16.3409[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.747526[/C][C]15.9453[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.736617[/C][C]15.7126[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.729052[/C][C]15.5512[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.705192[/C][C]15.0423[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.703859[/C][C]15.0138[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.69319[/C][C]14.7863[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.690408[/C][C]14.7269[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.687668[/C][C]14.6685[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.663243[/C][C]14.1475[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.681153[/C][C]14.5295[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.655697[/C][C]13.9865[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.651125[/C][C]13.889[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.641385[/C][C]13.6812[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.636778[/C][C]13.5829[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]0.627188[/C][C]13.3784[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.609135[/C][C]12.9933[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0.601944[/C][C]12.8399[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0.589227[/C][C]12.5686[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]0.588822[/C][C]12.56[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]0.591397[/C][C]12.6149[/C][C]0[/C][/ROW]
[ROW][C]35[/C][C]0.572411[/C][C]12.2099[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.585825[/C][C]12.4961[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.560129[/C][C]11.948[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]0.570754[/C][C]12.1746[/C][C]0[/C][/ROW]
[ROW][C]39[/C][C]0.558996[/C][C]11.9238[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]0.541999[/C][C]11.5612[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]0.536219[/C][C]11.4379[/C][C]0[/C][/ROW]
[ROW][C]42[/C][C]0.519921[/C][C]11.0903[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]0.519031[/C][C]11.0713[/C][C]0[/C][/ROW]
[ROW][C]44[/C][C]0.502142[/C][C]10.7111[/C][C]0[/C][/ROW]
[ROW][C]45[/C][C]0.501021[/C][C]10.6871[/C][C]0[/C][/ROW]
[ROW][C]46[/C][C]0.505855[/C][C]10.7903[/C][C]0[/C][/ROW]
[ROW][C]47[/C][C]0.490442[/C][C]10.4615[/C][C]0[/C][/ROW]
[ROW][C]48[/C][C]0.508292[/C][C]10.8422[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75308&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
10.91874819.59760
20.89075419.00040
30.87103118.57970
40.85064518.14490
50.83452117.80090
60.80925717.2620
70.80981717.2740
80.79682216.99680
90.79543416.96720
100.80076517.08090
110.78794216.80740
120.80668717.20720
130.77561216.54440
140.76607516.34090
150.74752615.94530
160.73661715.71260
170.72905215.55120
180.70519215.04230
190.70385915.01380
200.6931914.78630
210.69040814.72690
220.68766814.66850
230.66324314.14750
240.68115314.52950
250.65569713.98650
260.65112513.8890
270.64138513.68120
280.63677813.58290
290.62718813.37840
300.60913512.99330
310.60194412.83990
320.58922712.56860
330.58882212.560
340.59139712.61490
350.57241112.20990
360.58582512.49610
370.56012911.9480
380.57075412.17460
390.55899611.92380
400.54199911.56120
410.53621911.43790
420.51992111.09030
430.51903111.07130
440.50214210.71110
450.50102110.68710
460.50585510.79030
470.49044210.46150
480.50829210.84220







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.91874819.59760
20.2992666.38360
30.1593313.39860.000368
40.0710091.51470.065276
50.0613681.3090.095594
6-0.031139-0.66420.253442
70.1521153.24470.000631
80.0226260.48260.314795
90.0999232.13140.016794
100.1216622.59510.00488
11-0.028053-0.59840.274935
120.1947964.15511.9e-05
13-0.194711-4.15332e-05
14-0.002677-0.05710.477244
15-0.076031-1.62180.052771
160.0343550.73280.232023
170.004830.1030.458994
18-0.041947-0.89480.185691
190.0228610.48760.313021
200.0038250.08160.467501
210.0329240.70230.24143
22-0.012029-0.25660.39881
23-0.094465-2.0150.022246
240.1414183.01650.00135
25-0.097764-2.08540.018796
260.0347590.74140.229404
270.0110460.23560.406921
280.0427110.91110.181372
29-0.060792-1.29670.097688
300.0094130.20080.420478
31-0.07026-1.49870.067324
320.0093990.20050.420597
330.0627641.33880.090652
340.0368690.78640.216011
35-0.011013-0.23490.407193
360.0618611.31950.093825
37-0.126222-2.69240.003678
380.132142.81860.002517
39-0.059922-1.27820.100918
40-0.079541-1.69670.045221
410.007280.15530.438331
420.001790.03820.484776
430.024940.5320.297494
44-0.028751-0.61330.269998
450.0326840.69720.243026
460.0104210.22230.412095
470.0263820.56270.286946
480.0586291.25060.105863

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.918748 & 19.5976 & 0 \tabularnewline
2 & 0.299266 & 6.3836 & 0 \tabularnewline
3 & 0.159331 & 3.3986 & 0.000368 \tabularnewline
4 & 0.071009 & 1.5147 & 0.065276 \tabularnewline
5 & 0.061368 & 1.309 & 0.095594 \tabularnewline
6 & -0.031139 & -0.6642 & 0.253442 \tabularnewline
7 & 0.152115 & 3.2447 & 0.000631 \tabularnewline
8 & 0.022626 & 0.4826 & 0.314795 \tabularnewline
9 & 0.099923 & 2.1314 & 0.016794 \tabularnewline
10 & 0.121662 & 2.5951 & 0.00488 \tabularnewline
11 & -0.028053 & -0.5984 & 0.274935 \tabularnewline
12 & 0.194796 & 4.1551 & 1.9e-05 \tabularnewline
13 & -0.194711 & -4.1533 & 2e-05 \tabularnewline
14 & -0.002677 & -0.0571 & 0.477244 \tabularnewline
15 & -0.076031 & -1.6218 & 0.052771 \tabularnewline
16 & 0.034355 & 0.7328 & 0.232023 \tabularnewline
17 & 0.00483 & 0.103 & 0.458994 \tabularnewline
18 & -0.041947 & -0.8948 & 0.185691 \tabularnewline
19 & 0.022861 & 0.4876 & 0.313021 \tabularnewline
20 & 0.003825 & 0.0816 & 0.467501 \tabularnewline
21 & 0.032924 & 0.7023 & 0.24143 \tabularnewline
22 & -0.012029 & -0.2566 & 0.39881 \tabularnewline
23 & -0.094465 & -2.015 & 0.022246 \tabularnewline
24 & 0.141418 & 3.0165 & 0.00135 \tabularnewline
25 & -0.097764 & -2.0854 & 0.018796 \tabularnewline
26 & 0.034759 & 0.7414 & 0.229404 \tabularnewline
27 & 0.011046 & 0.2356 & 0.406921 \tabularnewline
28 & 0.042711 & 0.9111 & 0.181372 \tabularnewline
29 & -0.060792 & -1.2967 & 0.097688 \tabularnewline
30 & 0.009413 & 0.2008 & 0.420478 \tabularnewline
31 & -0.07026 & -1.4987 & 0.067324 \tabularnewline
32 & 0.009399 & 0.2005 & 0.420597 \tabularnewline
33 & 0.062764 & 1.3388 & 0.090652 \tabularnewline
34 & 0.036869 & 0.7864 & 0.216011 \tabularnewline
35 & -0.011013 & -0.2349 & 0.407193 \tabularnewline
36 & 0.061861 & 1.3195 & 0.093825 \tabularnewline
37 & -0.126222 & -2.6924 & 0.003678 \tabularnewline
38 & 0.13214 & 2.8186 & 0.002517 \tabularnewline
39 & -0.059922 & -1.2782 & 0.100918 \tabularnewline
40 & -0.079541 & -1.6967 & 0.045221 \tabularnewline
41 & 0.00728 & 0.1553 & 0.438331 \tabularnewline
42 & 0.00179 & 0.0382 & 0.484776 \tabularnewline
43 & 0.02494 & 0.532 & 0.297494 \tabularnewline
44 & -0.028751 & -0.6133 & 0.269998 \tabularnewline
45 & 0.032684 & 0.6972 & 0.243026 \tabularnewline
46 & 0.010421 & 0.2223 & 0.412095 \tabularnewline
47 & 0.026382 & 0.5627 & 0.286946 \tabularnewline
48 & 0.058629 & 1.2506 & 0.105863 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75308&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]0.918748[/C][C]19.5976[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.299266[/C][C]6.3836[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.159331[/C][C]3.3986[/C][C]0.000368[/C][/ROW]
[ROW][C]4[/C][C]0.071009[/C][C]1.5147[/C][C]0.065276[/C][/ROW]
[ROW][C]5[/C][C]0.061368[/C][C]1.309[/C][C]0.095594[/C][/ROW]
[ROW][C]6[/C][C]-0.031139[/C][C]-0.6642[/C][C]0.253442[/C][/ROW]
[ROW][C]7[/C][C]0.152115[/C][C]3.2447[/C][C]0.000631[/C][/ROW]
[ROW][C]8[/C][C]0.022626[/C][C]0.4826[/C][C]0.314795[/C][/ROW]
[ROW][C]9[/C][C]0.099923[/C][C]2.1314[/C][C]0.016794[/C][/ROW]
[ROW][C]10[/C][C]0.121662[/C][C]2.5951[/C][C]0.00488[/C][/ROW]
[ROW][C]11[/C][C]-0.028053[/C][C]-0.5984[/C][C]0.274935[/C][/ROW]
[ROW][C]12[/C][C]0.194796[/C][C]4.1551[/C][C]1.9e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.194711[/C][C]-4.1533[/C][C]2e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.002677[/C][C]-0.0571[/C][C]0.477244[/C][/ROW]
[ROW][C]15[/C][C]-0.076031[/C][C]-1.6218[/C][C]0.052771[/C][/ROW]
[ROW][C]16[/C][C]0.034355[/C][C]0.7328[/C][C]0.232023[/C][/ROW]
[ROW][C]17[/C][C]0.00483[/C][C]0.103[/C][C]0.458994[/C][/ROW]
[ROW][C]18[/C][C]-0.041947[/C][C]-0.8948[/C][C]0.185691[/C][/ROW]
[ROW][C]19[/C][C]0.022861[/C][C]0.4876[/C][C]0.313021[/C][/ROW]
[ROW][C]20[/C][C]0.003825[/C][C]0.0816[/C][C]0.467501[/C][/ROW]
[ROW][C]21[/C][C]0.032924[/C][C]0.7023[/C][C]0.24143[/C][/ROW]
[ROW][C]22[/C][C]-0.012029[/C][C]-0.2566[/C][C]0.39881[/C][/ROW]
[ROW][C]23[/C][C]-0.094465[/C][C]-2.015[/C][C]0.022246[/C][/ROW]
[ROW][C]24[/C][C]0.141418[/C][C]3.0165[/C][C]0.00135[/C][/ROW]
[ROW][C]25[/C][C]-0.097764[/C][C]-2.0854[/C][C]0.018796[/C][/ROW]
[ROW][C]26[/C][C]0.034759[/C][C]0.7414[/C][C]0.229404[/C][/ROW]
[ROW][C]27[/C][C]0.011046[/C][C]0.2356[/C][C]0.406921[/C][/ROW]
[ROW][C]28[/C][C]0.042711[/C][C]0.9111[/C][C]0.181372[/C][/ROW]
[ROW][C]29[/C][C]-0.060792[/C][C]-1.2967[/C][C]0.097688[/C][/ROW]
[ROW][C]30[/C][C]0.009413[/C][C]0.2008[/C][C]0.420478[/C][/ROW]
[ROW][C]31[/C][C]-0.07026[/C][C]-1.4987[/C][C]0.067324[/C][/ROW]
[ROW][C]32[/C][C]0.009399[/C][C]0.2005[/C][C]0.420597[/C][/ROW]
[ROW][C]33[/C][C]0.062764[/C][C]1.3388[/C][C]0.090652[/C][/ROW]
[ROW][C]34[/C][C]0.036869[/C][C]0.7864[/C][C]0.216011[/C][/ROW]
[ROW][C]35[/C][C]-0.011013[/C][C]-0.2349[/C][C]0.407193[/C][/ROW]
[ROW][C]36[/C][C]0.061861[/C][C]1.3195[/C][C]0.093825[/C][/ROW]
[ROW][C]37[/C][C]-0.126222[/C][C]-2.6924[/C][C]0.003678[/C][/ROW]
[ROW][C]38[/C][C]0.13214[/C][C]2.8186[/C][C]0.002517[/C][/ROW]
[ROW][C]39[/C][C]-0.059922[/C][C]-1.2782[/C][C]0.100918[/C][/ROW]
[ROW][C]40[/C][C]-0.079541[/C][C]-1.6967[/C][C]0.045221[/C][/ROW]
[ROW][C]41[/C][C]0.00728[/C][C]0.1553[/C][C]0.438331[/C][/ROW]
[ROW][C]42[/C][C]0.00179[/C][C]0.0382[/C][C]0.484776[/C][/ROW]
[ROW][C]43[/C][C]0.02494[/C][C]0.532[/C][C]0.297494[/C][/ROW]
[ROW][C]44[/C][C]-0.028751[/C][C]-0.6133[/C][C]0.269998[/C][/ROW]
[ROW][C]45[/C][C]0.032684[/C][C]0.6972[/C][C]0.243026[/C][/ROW]
[ROW][C]46[/C][C]0.010421[/C][C]0.2223[/C][C]0.412095[/C][/ROW]
[ROW][C]47[/C][C]0.026382[/C][C]0.5627[/C][C]0.286946[/C][/ROW]
[ROW][C]48[/C][C]0.058629[/C][C]1.2506[/C][C]0.105863[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75308&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
10.91874819.59760
20.2992666.38360
30.1593313.39860.000368
40.0710091.51470.065276
50.0613681.3090.095594
6-0.031139-0.66420.253442
70.1521153.24470.000631
80.0226260.48260.314795
90.0999232.13140.016794
100.1216622.59510.00488
11-0.028053-0.59840.274935
120.1947964.15511.9e-05
13-0.194711-4.15332e-05
14-0.002677-0.05710.477244
15-0.076031-1.62180.052771
160.0343550.73280.232023
170.004830.1030.458994
18-0.041947-0.89480.185691
190.0228610.48760.313021
200.0038250.08160.467501
210.0329240.70230.24143
22-0.012029-0.25660.39881
23-0.094465-2.0150.022246
240.1414183.01650.00135
25-0.097764-2.08540.018796
260.0347590.74140.229404
270.0110460.23560.406921
280.0427110.91110.181372
29-0.060792-1.29670.097688
300.0094130.20080.420478
31-0.07026-1.49870.067324
320.0093990.20050.420597
330.0627641.33880.090652
340.0368690.78640.216011
35-0.011013-0.23490.407193
360.0618611.31950.093825
37-0.126222-2.69240.003678
380.132142.81860.002517
39-0.059922-1.27820.100918
40-0.079541-1.69670.045221
410.007280.15530.438331
420.001790.03820.484776
430.024940.5320.297494
44-0.028751-0.61330.269998
450.0326840.69720.243026
460.0104210.22230.412095
470.0263820.56270.286946
480.0586291.25060.105863



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