FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 03 Dec 2008 08:12:42 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/03/t1228317286ocj01fr85xlc3ih.htm/, Retrieved Fri, 05 Dec 2025 04:28:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28728, Retrieved Fri, 05 Dec 2025 04:28:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact597

Tree of Dependent Computations

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]
F RMP     [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-03 15:12:42] [286e96bd53289970f8e5f25a93fb50b3] [Current]
-    D      [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-04 18:21:05] [819b576fab25b35cfda70f80599828ec]
-   P         [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:18:35] [6fea0e9a9b3b29a63badf2c274e82506]
-   P           [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:24:16] [6fea0e9a9b3b29a63badf2c274e82506]
-   P             [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:28:10] [6fea0e9a9b3b29a63badf2c274e82506]
F             [(Partial) Autocorrelation Function] [stap 2] [2008-12-08 16:33:12] [74be16979710d4c4e7c6647856088456]
-   P           [(Partial) Autocorrelation Function] [Verbetering ACF s...] [2008-12-15 20:47:34] [bc937651ef42bf891200cf0e0edc7238]
- RMP             [Spectral Analysis] [Verbetering SA st...] [2008-12-15 20:50:37] [bc937651ef42bf891200cf0e0edc7238]
- R P         [(Partial) Autocorrelation Function] [Step 2 D=1 en d=1] [2008-12-08 16:44:02] [7458e879e85b911182071700fff19fbd]
F   P         [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-08 16:54:24] [6fea0e9a9b3b29a63badf2c274e82506]
-   P           [(Partial) Autocorrelation Function] [Identification an...] [2008-12-08 19:21:03] [79c17183721a40a589db5f9f561947d8]
F   P         [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-08 16:56:20] [6fea0e9a9b3b29a63badf2c274e82506]
-   P           [(Partial) Autocorrelation Function] [Identification an...] [2008-12-08 19:23:00] [79c17183721a40a589db5f9f561947d8]
-           [(Partial) Autocorrelation Function] [Identification an...] [2008-12-08 19:02:59] [79c17183721a40a589db5f9f561947d8]
Feedback Forum
2008-12-13 14:46:18 [An De Koninck] [reply] 
Correct opgelost.
2008-12-14 09:43:49 [Kristof Van Esbroeck] [reply] 
Men gebruikt juiste software.

Student merkt vervolgens correct een langetermijntrend op.
In een volgende berekening zal deze weggewerkt worden.
2008-12-14 10:55:17 [Jeroen Michel] [reply] 
Ook hier past de student een correcte methode toe (juiste techniek/module). Voorts zal de student een langetermijntrend vast stellen op de grafieken. Dit heeft de student correct geconcludeerd. In volgende berekeningen bestaat de mogelijkheid deze weg te werken.
2008-12-14 12:19:57 [Kevin Neelen] [reply] 
De student maakt hier wederom gebruik van de juiste methode om vraagstellin gcorrect te kunnen oplossen, namelijk de Autocorrelation Function (ACF).

De student heeft de volgende gegevens in de calculator ingevoerd: lags = 60, d = 0, D = 0 en Seasonal period = 12.

Concluderend kunnen we stellen dat we een autocorrelatiegrafiek zien met langzaam aflopende correlatiewaarden. Dit duidt dus op een lange termijn trend. Om deze weg te werken, zal een volgende berekening toegepast worden.
  2008-12-15 21:03:12 [Nilay Erdogdu] [reply] 
Ik ben het eens met de uitleg van Kevin Neelen. En ook zien we bij de ACF een soort van afgeronde trapjes die elke keer terug komen.
2008-12-14 13:32:35 [Ilknur Günes] [reply] 
Correct!
2008-12-14 16:59:29 [Mehmet Yilmaz] [reply] 
Correct.
2008-12-15 10:33:39 [Jef Keersmaekers] [reply] 
de berekeningen zijn correct

2008-12-15 18:00:12 [Steffi Van Isveldt] [reply] 
Hier gebruikt men opnieuw de juiste methode om de vraag op te lossen, namelijk de Autocorrelation Function (ACF).
We kunnen stellen dat de grafiek een langzaam dalend verloop kent, wat duidt op een lange termijn trend.
2008-12-16 08:44:00 [Tim Damen] [reply] 
slim gezien om de lags gelijk te stellen aan 60 in plaats van 12 (48 was ook goed geweest denk ik) Zo krijgen we een minder vertekend beeld

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7
384.6
365.8
368.1
367.9
347
343.3
292.9
311.5
300.9
366.9
356.9
329.7
316.2
269
289.3
266.2
253.6
233.8
228.4
253.6
260.1
306.6
309.2
309.5
271
279.9
317.9
298.4
246.7
227.3
209.1
259.9
266
320.6
308.5
282.2
262.7
263.5
313.1
284.3
252.6
250.3
246.5
312.7
333.2
446.4
511.6
515.5
506.4
483.2
522.3
509.8
460.7
405.8
375
378.5
406.8
467.8
469.8
429.8
355.8
332.7
378
360.5
334.7
319.5
323.1
363.6
352.1
411.9
388.6
416.4
360.7
338
417.2
388.4
371.1
331.5
353.7
396.7
447
533.5
565.4
542.3
488.7
467.1
531.3
496.1
444
403.4
386.3
394.1
404.1
462.1
448.1
432.3
386.3
395.2
421.9
382.9
384.2
345.5
323.4
372.6
376
462.7
487
444.2
399.3
394.9
455.4
414
375.5
347
339.4
385.8
378.8
451.8
446.1
422.5
383.1
352.8
445.3
367.5
355.1
326.2
319.8
331.8
340.9
394.1
417.2
369.9
349.2
321.4
405.7
342.9
316.5
284.2
270.9
288.8
278.8
324.4
310.9
299
273
279.3
359.2
305
282.1
250.3
246.5
257.9
266.5
315.9
318.4
295.4
266.4
245.8
362.8
324.9
294.2
289.5
295.2
290.3
272
307.4
328.7
292.9
249.1
230.4
361.5
321.7
277.2
260.7
251
257.6
241.8
287.5
292.3
274.7
254.2
230
339
318.2
287
295.8
284
271
262.7
340.6
379.4
373.3
355.2
338.4
466.9
451
422
429.2
425.9
460.7
463.6
541.4
544.2
517.5
469.4
439.4
549
533
506.1
484
457
481.5
469.5
544.7
541.2
521.5
469.7
434.4
542.6
517.3
485.7
465.8
447
426.6
411.6
467.5
484.5
451.2
417.4
379.9
484.7
455
420.8
416.5
376.3
405.6
405.8
500.8
514
475.5
430.1
414.4
538
526
488.5
520.2
504.4
568.5
610.6
818
830.9
835.9
782
762.3
856.9
820.9
769.6
752.2
724.4
723.1
719.5
817.4
803.3
752.5
689
630.4
765.5
757.7
732.2
702.6
683.3
709.5
702.2
784.8
810.9
755.6
656.8
615.1
745.3
694.1
675.7
643.7
622.1
634.6
588
689.7
673.9
647.9
568.8
545.7
632.6
643.8
593.1
579.7
546
562.9
572.5

Tables (Output of Computation)





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=28728&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=28728&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28728&T=0

As an alternative you can also use a QR Code:  
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
10.95829718.4830
20.91521817.65210
30.88341217.03860
40.87008816.78160
50.86173516.62050
60.83236716.05410
70.81215315.66420
80.77509514.94950
90.74559214.38050
100.73465214.16950
110.73915414.25630
120.74370514.34410
130.69318813.36970
140.6441612.42410
150.61139311.79210
160.59979311.56840
170.59740911.52240
180.57795411.14720
190.56895310.97360
200.54377610.4880
210.52623210.14960
220.52570110.13940
230.53771210.3710
240.55135410.63410
250.5128499.89150
260.4750369.16220
270.451488.70780
280.4465798.61330
290.448128.6430
300.4318678.32950
310.4249028.19520
320.4028217.76930
330.3883397.490
340.3888877.50060
350.401247.73880
360.4155648.01510
370.3792257.31420
380.344126.63710
390.3204116.17990
400.3139326.05490
410.3139726.05570
420.2986625.76040
430.2917155.62640
440.2712295.23130
450.2585574.98690
460.26195.05130
470.2776165.35450
480.2937845.66630
490.2637235.08650
500.2335144.50394e-06
510.2142154.13162.2e-05
520.209714.04473.2e-05
530.2113754.07682.8e-05
540.1968923.79758.5e-05
550.190393.67210.000138
560.1683633.24730.000635
570.1523882.93920.001748
580.1500172.89340.002018
590.1578023.04360.001252
600.1653633.18940.000773

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.958297 & 18.483 & 0 \tabularnewline
2 & 0.915218 & 17.6521 & 0 \tabularnewline
3 & 0.883412 & 17.0386 & 0 \tabularnewline
4 & 0.870088 & 16.7816 & 0 \tabularnewline
5 & 0.861735 & 16.6205 & 0 \tabularnewline
6 & 0.832367 & 16.0541 & 0 \tabularnewline
7 & 0.812153 & 15.6642 & 0 \tabularnewline
8 & 0.775095 & 14.9495 & 0 \tabularnewline
9 & 0.745592 & 14.3805 & 0 \tabularnewline
10 & 0.734652 & 14.1695 & 0 \tabularnewline
11 & 0.739154 & 14.2563 & 0 \tabularnewline
12 & 0.743705 & 14.3441 & 0 \tabularnewline
13 & 0.693188 & 13.3697 & 0 \tabularnewline
14 & 0.64416 & 12.4241 & 0 \tabularnewline
15 & 0.611393 & 11.7921 & 0 \tabularnewline
16 & 0.599793 & 11.5684 & 0 \tabularnewline
17 & 0.597409 & 11.5224 & 0 \tabularnewline
18 & 0.577954 & 11.1472 & 0 \tabularnewline
19 & 0.568953 & 10.9736 & 0 \tabularnewline
20 & 0.543776 & 10.488 & 0 \tabularnewline
21 & 0.526232 & 10.1496 & 0 \tabularnewline
22 & 0.525701 & 10.1394 & 0 \tabularnewline
23 & 0.537712 & 10.371 & 0 \tabularnewline
24 & 0.551354 & 10.6341 & 0 \tabularnewline
25 & 0.512849 & 9.8915 & 0 \tabularnewline
26 & 0.475036 & 9.1622 & 0 \tabularnewline
27 & 0.45148 & 8.7078 & 0 \tabularnewline
28 & 0.446579 & 8.6133 & 0 \tabularnewline
29 & 0.44812 & 8.643 & 0 \tabularnewline
30 & 0.431867 & 8.3295 & 0 \tabularnewline
31 & 0.424902 & 8.1952 & 0 \tabularnewline
32 & 0.402821 & 7.7693 & 0 \tabularnewline
33 & 0.388339 & 7.49 & 0 \tabularnewline
34 & 0.388887 & 7.5006 & 0 \tabularnewline
35 & 0.40124 & 7.7388 & 0 \tabularnewline
36 & 0.415564 & 8.0151 & 0 \tabularnewline
37 & 0.379225 & 7.3142 & 0 \tabularnewline
38 & 0.34412 & 6.6371 & 0 \tabularnewline
39 & 0.320411 & 6.1799 & 0 \tabularnewline
40 & 0.313932 & 6.0549 & 0 \tabularnewline
41 & 0.313972 & 6.0557 & 0 \tabularnewline
42 & 0.298662 & 5.7604 & 0 \tabularnewline
43 & 0.291715 & 5.6264 & 0 \tabularnewline
44 & 0.271229 & 5.2313 & 0 \tabularnewline
45 & 0.258557 & 4.9869 & 0 \tabularnewline
46 & 0.2619 & 5.0513 & 0 \tabularnewline
47 & 0.277616 & 5.3545 & 0 \tabularnewline
48 & 0.293784 & 5.6663 & 0 \tabularnewline
49 & 0.263723 & 5.0865 & 0 \tabularnewline
50 & 0.233514 & 4.5039 & 4e-06 \tabularnewline
51 & 0.214215 & 4.1316 & 2.2e-05 \tabularnewline
52 & 0.20971 & 4.0447 & 3.2e-05 \tabularnewline
53 & 0.211375 & 4.0768 & 2.8e-05 \tabularnewline
54 & 0.196892 & 3.7975 & 8.5e-05 \tabularnewline
55 & 0.19039 & 3.6721 & 0.000138 \tabularnewline
56 & 0.168363 & 3.2473 & 0.000635 \tabularnewline
57 & 0.152388 & 2.9392 & 0.001748 \tabularnewline
58 & 0.150017 & 2.8934 & 0.002018 \tabularnewline
59 & 0.157802 & 3.0436 & 0.001252 \tabularnewline
60 & 0.165363 & 3.1894 & 0.000773 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28728&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]0.958297[/C][C]18.483[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.915218[/C][C]17.6521[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.883412[/C][C]17.0386[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.870088[/C][C]16.7816[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.861735[/C][C]16.6205[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.832367[/C][C]16.0541[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.812153[/C][C]15.6642[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.775095[/C][C]14.9495[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.745592[/C][C]14.3805[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.734652[/C][C]14.1695[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.739154[/C][C]14.2563[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.743705[/C][C]14.3441[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.693188[/C][C]13.3697[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.64416[/C][C]12.4241[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.611393[/C][C]11.7921[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.599793[/C][C]11.5684[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.597409[/C][C]11.5224[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.577954[/C][C]11.1472[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.568953[/C][C]10.9736[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.543776[/C][C]10.488[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.526232[/C][C]10.1496[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.525701[/C][C]10.1394[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.537712[/C][C]10.371[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.551354[/C][C]10.6341[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.512849[/C][C]9.8915[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.475036[/C][C]9.1622[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.45148[/C][C]8.7078[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.446579[/C][C]8.6133[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]0.44812[/C][C]8.643[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.431867[/C][C]8.3295[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0.424902[/C][C]8.1952[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0.402821[/C][C]7.7693[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]0.388339[/C][C]7.49[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]0.388887[/C][C]7.5006[/C][C]0[/C][/ROW]
[ROW][C]35[/C][C]0.40124[/C][C]7.7388[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.415564[/C][C]8.0151[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.379225[/C][C]7.3142[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]0.34412[/C][C]6.6371[/C][C]0[/C][/ROW]
[ROW][C]39[/C][C]0.320411[/C][C]6.1799[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]0.313932[/C][C]6.0549[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]0.313972[/C][C]6.0557[/C][C]0[/C][/ROW]
[ROW][C]42[/C][C]0.298662[/C][C]5.7604[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]0.291715[/C][C]5.6264[/C][C]0[/C][/ROW]
[ROW][C]44[/C][C]0.271229[/C][C]5.2313[/C][C]0[/C][/ROW]
[ROW][C]45[/C][C]0.258557[/C][C]4.9869[/C][C]0[/C][/ROW]
[ROW][C]46[/C][C]0.2619[/C][C]5.0513[/C][C]0[/C][/ROW]
[ROW][C]47[/C][C]0.277616[/C][C]5.3545[/C][C]0[/C][/ROW]
[ROW][C]48[/C][C]0.293784[/C][C]5.6663[/C][C]0[/C][/ROW]
[ROW][C]49[/C][C]0.263723[/C][C]5.0865[/C][C]0[/C][/ROW]
[ROW][C]50[/C][C]0.233514[/C][C]4.5039[/C][C]4e-06[/C][/ROW]
[ROW][C]51[/C][C]0.214215[/C][C]4.1316[/C][C]2.2e-05[/C][/ROW]
[ROW][C]52[/C][C]0.20971[/C][C]4.0447[/C][C]3.2e-05[/C][/ROW]
[ROW][C]53[/C][C]0.211375[/C][C]4.0768[/C][C]2.8e-05[/C][/ROW]
[ROW][C]54[/C][C]0.196892[/C][C]3.7975[/C][C]8.5e-05[/C][/ROW]
[ROW][C]55[/C][C]0.19039[/C][C]3.6721[/C][C]0.000138[/C][/ROW]
[ROW][C]56[/C][C]0.168363[/C][C]3.2473[/C][C]0.000635[/C][/ROW]
[ROW][C]57[/C][C]0.152388[/C][C]2.9392[/C][C]0.001748[/C][/ROW]
[ROW][C]58[/C][C]0.150017[/C][C]2.8934[/C][C]0.002018[/C][/ROW]
[ROW][C]59[/C][C]0.157802[/C][C]3.0436[/C][C]0.001252[/C][/ROW]
[ROW][C]60[/C][C]0.165363[/C][C]3.1894[/C][C]0.000773[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28728&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28728&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95829718.4830
20.91521817.65210
30.88341217.03860
40.87008816.78160
50.86173516.62050
60.83236716.05410
70.81215315.66420
80.77509514.94950
90.74559214.38050
100.73465214.16950
110.73915414.25630
120.74370514.34410
130.69318813.36970
140.6441612.42410
150.61139311.79210
160.59979311.56840
170.59740911.52240
180.57795411.14720
190.56895310.97360
200.54377610.4880
210.52623210.14960
220.52570110.13940
230.53771210.3710
240.55135410.63410
250.5128499.89150
260.4750369.16220
270.451488.70780
280.4465798.61330
290.448128.6430
300.4318678.32950
310.4249028.19520
320.4028217.76930
330.3883397.490
340.3888877.50060
350.401247.73880
360.4155648.01510
370.3792257.31420
380.344126.63710
390.3204116.17990
400.3139326.05490
410.3139726.05570
420.2986625.76040
430.2917155.62640
440.2712295.23130
450.2585574.98690
460.26195.05130
470.2776165.35450
480.2937845.66630
490.2637235.08650
500.2335144.50394e-06
510.2142154.13162.2e-05
520.209714.04473.2e-05
530.2113754.07682.8e-05
540.1968923.79758.5e-05
550.190393.67210.000138
560.1683633.24730.000635
570.1523882.93920.001748
580.1500172.89340.002018
590.1578023.04360.001252
600.1653633.18940.000773






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95829718.4830
2-0.038138-0.73560.231227
30.1160082.23750.012923
40.2073453.99913.8e-05
50.0712951.37510.084967
6-0.216629-4.17821.8e-05
70.1778433.43010.000336
8-0.280159-5.40350
90.0515850.99490.160206
100.2214434.2711.2e-05
110.1890493.64620.000152
12-0.045031-0.86850.192833
13-0.550158-10.61110
140.0486850.9390.17417
150.1391522.68390.003802
160.0589661.13730.128074
170.1450152.7970.002713
180.0564151.08810.13863
190.0891681.71980.04315
20-0.085304-1.64530.050378
210.0107060.20650.418258
220.0204530.39450.346725
23-0.016396-0.31620.376
240.0564891.08950.138315
25-0.235006-4.53264e-06
260.008890.17150.431974
270.0490980.9470.172137
28-0.018295-0.35290.362198
29-0.002463-0.04750.481071
300.0294940.56890.284897
310.0502210.96860.16668
32-0.006361-0.12270.45121
330.0439290.84730.198693
340.016920.32630.372172
35-0.002393-0.04620.481607
360.0201210.38810.349091
37-0.189406-3.65310.000148
380.0123510.23820.405923
39-0.038849-0.74930.227076
40-0.033337-0.6430.260319
410.0326140.6290.264854
420.0928391.79060.037084
43-0.013284-0.25620.398966
440.0235280.45380.325119
450.0335990.6480.25868
460.0403740.77870.218321
470.0116450.22460.411208
48-0.024423-0.47110.31894
49-0.06699-1.29210.098569
50-0.031084-0.59950.274592
51-0.023084-0.44520.328206
52-0.061509-1.18630.118122
53-0.001646-0.03180.487343
54-0.002282-0.0440.482462
550.0011130.02150.491441
56-0.039442-0.76070.223649
57-0.0128-0.24690.402567
58-0.013281-0.25620.398983
59-0.018742-0.36150.358969
60-0.027922-0.53850.29526

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.958297 & 18.483 & 0 \tabularnewline
2 & -0.038138 & -0.7356 & 0.231227 \tabularnewline
3 & 0.116008 & 2.2375 & 0.012923 \tabularnewline
4 & 0.207345 & 3.9991 & 3.8e-05 \tabularnewline
5 & 0.071295 & 1.3751 & 0.084967 \tabularnewline
6 & -0.216629 & -4.1782 & 1.8e-05 \tabularnewline
7 & 0.177843 & 3.4301 & 0.000336 \tabularnewline
8 & -0.280159 & -5.4035 & 0 \tabularnewline
9 & 0.051585 & 0.9949 & 0.160206 \tabularnewline
10 & 0.221443 & 4.271 & 1.2e-05 \tabularnewline
11 & 0.189049 & 3.6462 & 0.000152 \tabularnewline
12 & -0.045031 & -0.8685 & 0.192833 \tabularnewline
13 & -0.550158 & -10.6111 & 0 \tabularnewline
14 & 0.048685 & 0.939 & 0.17417 \tabularnewline
15 & 0.139152 & 2.6839 & 0.003802 \tabularnewline
16 & 0.058966 & 1.1373 & 0.128074 \tabularnewline
17 & 0.145015 & 2.797 & 0.002713 \tabularnewline
18 & 0.056415 & 1.0881 & 0.13863 \tabularnewline
19 & 0.089168 & 1.7198 & 0.04315 \tabularnewline
20 & -0.085304 & -1.6453 & 0.050378 \tabularnewline
21 & 0.010706 & 0.2065 & 0.418258 \tabularnewline
22 & 0.020453 & 0.3945 & 0.346725 \tabularnewline
23 & -0.016396 & -0.3162 & 0.376 \tabularnewline
24 & 0.056489 & 1.0895 & 0.138315 \tabularnewline
25 & -0.235006 & -4.5326 & 4e-06 \tabularnewline
26 & 0.00889 & 0.1715 & 0.431974 \tabularnewline
27 & 0.049098 & 0.947 & 0.172137 \tabularnewline
28 & -0.018295 & -0.3529 & 0.362198 \tabularnewline
29 & -0.002463 & -0.0475 & 0.481071 \tabularnewline
30 & 0.029494 & 0.5689 & 0.284897 \tabularnewline
31 & 0.050221 & 0.9686 & 0.16668 \tabularnewline
32 & -0.006361 & -0.1227 & 0.45121 \tabularnewline
33 & 0.043929 & 0.8473 & 0.198693 \tabularnewline
34 & 0.01692 & 0.3263 & 0.372172 \tabularnewline
35 & -0.002393 & -0.0462 & 0.481607 \tabularnewline
36 & 0.020121 & 0.3881 & 0.349091 \tabularnewline
37 & -0.189406 & -3.6531 & 0.000148 \tabularnewline
38 & 0.012351 & 0.2382 & 0.405923 \tabularnewline
39 & -0.038849 & -0.7493 & 0.227076 \tabularnewline
40 & -0.033337 & -0.643 & 0.260319 \tabularnewline
41 & 0.032614 & 0.629 & 0.264854 \tabularnewline
42 & 0.092839 & 1.7906 & 0.037084 \tabularnewline
43 & -0.013284 & -0.2562 & 0.398966 \tabularnewline
44 & 0.023528 & 0.4538 & 0.325119 \tabularnewline
45 & 0.033599 & 0.648 & 0.25868 \tabularnewline
46 & 0.040374 & 0.7787 & 0.218321 \tabularnewline
47 & 0.011645 & 0.2246 & 0.411208 \tabularnewline
48 & -0.024423 & -0.4711 & 0.31894 \tabularnewline
49 & -0.06699 & -1.2921 & 0.098569 \tabularnewline
50 & -0.031084 & -0.5995 & 0.274592 \tabularnewline
51 & -0.023084 & -0.4452 & 0.328206 \tabularnewline
52 & -0.061509 & -1.1863 & 0.118122 \tabularnewline
53 & -0.001646 & -0.0318 & 0.487343 \tabularnewline
54 & -0.002282 & -0.044 & 0.482462 \tabularnewline
55 & 0.001113 & 0.0215 & 0.491441 \tabularnewline
56 & -0.039442 & -0.7607 & 0.223649 \tabularnewline
57 & -0.0128 & -0.2469 & 0.402567 \tabularnewline
58 & -0.013281 & -0.2562 & 0.398983 \tabularnewline
59 & -0.018742 & -0.3615 & 0.358969 \tabularnewline
60 & -0.027922 & -0.5385 & 0.29526 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28728&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]0.958297[/C][C]18.483[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.038138[/C][C]-0.7356[/C][C]0.231227[/C][/ROW]
[ROW][C]3[/C][C]0.116008[/C][C]2.2375[/C][C]0.012923[/C][/ROW]
[ROW][C]4[/C][C]0.207345[/C][C]3.9991[/C][C]3.8e-05[/C][/ROW]
[ROW][C]5[/C][C]0.071295[/C][C]1.3751[/C][C]0.084967[/C][/ROW]
[ROW][C]6[/C][C]-0.216629[/C][C]-4.1782[/C][C]1.8e-05[/C][/ROW]
[ROW][C]7[/C][C]0.177843[/C][C]3.4301[/C][C]0.000336[/C][/ROW]
[ROW][C]8[/C][C]-0.280159[/C][C]-5.4035[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.051585[/C][C]0.9949[/C][C]0.160206[/C][/ROW]
[ROW][C]10[/C][C]0.221443[/C][C]4.271[/C][C]1.2e-05[/C][/ROW]
[ROW][C]11[/C][C]0.189049[/C][C]3.6462[/C][C]0.000152[/C][/ROW]
[ROW][C]12[/C][C]-0.045031[/C][C]-0.8685[/C][C]0.192833[/C][/ROW]
[ROW][C]13[/C][C]-0.550158[/C][C]-10.6111[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.048685[/C][C]0.939[/C][C]0.17417[/C][/ROW]
[ROW][C]15[/C][C]0.139152[/C][C]2.6839[/C][C]0.003802[/C][/ROW]
[ROW][C]16[/C][C]0.058966[/C][C]1.1373[/C][C]0.128074[/C][/ROW]
[ROW][C]17[/C][C]0.145015[/C][C]2.797[/C][C]0.002713[/C][/ROW]
[ROW][C]18[/C][C]0.056415[/C][C]1.0881[/C][C]0.13863[/C][/ROW]
[ROW][C]19[/C][C]0.089168[/C][C]1.7198[/C][C]0.04315[/C][/ROW]
[ROW][C]20[/C][C]-0.085304[/C][C]-1.6453[/C][C]0.050378[/C][/ROW]
[ROW][C]21[/C][C]0.010706[/C][C]0.2065[/C][C]0.418258[/C][/ROW]
[ROW][C]22[/C][C]0.020453[/C][C]0.3945[/C][C]0.346725[/C][/ROW]
[ROW][C]23[/C][C]-0.016396[/C][C]-0.3162[/C][C]0.376[/C][/ROW]
[ROW][C]24[/C][C]0.056489[/C][C]1.0895[/C][C]0.138315[/C][/ROW]
[ROW][C]25[/C][C]-0.235006[/C][C]-4.5326[/C][C]4e-06[/C][/ROW]
[ROW][C]26[/C][C]0.00889[/C][C]0.1715[/C][C]0.431974[/C][/ROW]
[ROW][C]27[/C][C]0.049098[/C][C]0.947[/C][C]0.172137[/C][/ROW]
[ROW][C]28[/C][C]-0.018295[/C][C]-0.3529[/C][C]0.362198[/C][/ROW]
[ROW][C]29[/C][C]-0.002463[/C][C]-0.0475[/C][C]0.481071[/C][/ROW]
[ROW][C]30[/C][C]0.029494[/C][C]0.5689[/C][C]0.284897[/C][/ROW]
[ROW][C]31[/C][C]0.050221[/C][C]0.9686[/C][C]0.16668[/C][/ROW]
[ROW][C]32[/C][C]-0.006361[/C][C]-0.1227[/C][C]0.45121[/C][/ROW]
[ROW][C]33[/C][C]0.043929[/C][C]0.8473[/C][C]0.198693[/C][/ROW]
[ROW][C]34[/C][C]0.01692[/C][C]0.3263[/C][C]0.372172[/C][/ROW]
[ROW][C]35[/C][C]-0.002393[/C][C]-0.0462[/C][C]0.481607[/C][/ROW]
[ROW][C]36[/C][C]0.020121[/C][C]0.3881[/C][C]0.349091[/C][/ROW]
[ROW][C]37[/C][C]-0.189406[/C][C]-3.6531[/C][C]0.000148[/C][/ROW]
[ROW][C]38[/C][C]0.012351[/C][C]0.2382[/C][C]0.405923[/C][/ROW]
[ROW][C]39[/C][C]-0.038849[/C][C]-0.7493[/C][C]0.227076[/C][/ROW]
[ROW][C]40[/C][C]-0.033337[/C][C]-0.643[/C][C]0.260319[/C][/ROW]
[ROW][C]41[/C][C]0.032614[/C][C]0.629[/C][C]0.264854[/C][/ROW]
[ROW][C]42[/C][C]0.092839[/C][C]1.7906[/C][C]0.037084[/C][/ROW]
[ROW][C]43[/C][C]-0.013284[/C][C]-0.2562[/C][C]0.398966[/C][/ROW]
[ROW][C]44[/C][C]0.023528[/C][C]0.4538[/C][C]0.325119[/C][/ROW]
[ROW][C]45[/C][C]0.033599[/C][C]0.648[/C][C]0.25868[/C][/ROW]
[ROW][C]46[/C][C]0.040374[/C][C]0.7787[/C][C]0.218321[/C][/ROW]
[ROW][C]47[/C][C]0.011645[/C][C]0.2246[/C][C]0.411208[/C][/ROW]
[ROW][C]48[/C][C]-0.024423[/C][C]-0.4711[/C][C]0.31894[/C][/ROW]
[ROW][C]49[/C][C]-0.06699[/C][C]-1.2921[/C][C]0.098569[/C][/ROW]
[ROW][C]50[/C][C]-0.031084[/C][C]-0.5995[/C][C]0.274592[/C][/ROW]
[ROW][C]51[/C][C]-0.023084[/C][C]-0.4452[/C][C]0.328206[/C][/ROW]
[ROW][C]52[/C][C]-0.061509[/C][C]-1.1863[/C][C]0.118122[/C][/ROW]
[ROW][C]53[/C][C]-0.001646[/C][C]-0.0318[/C][C]0.487343[/C][/ROW]
[ROW][C]54[/C][C]-0.002282[/C][C]-0.044[/C][C]0.482462[/C][/ROW]
[ROW][C]55[/C][C]0.001113[/C][C]0.0215[/C][C]0.491441[/C][/ROW]
[ROW][C]56[/C][C]-0.039442[/C][C]-0.7607[/C][C]0.223649[/C][/ROW]
[ROW][C]57[/C][C]-0.0128[/C][C]-0.2469[/C][C]0.402567[/C][/ROW]
[ROW][C]58[/C][C]-0.013281[/C][C]-0.2562[/C][C]0.398983[/C][/ROW]
[ROW][C]59[/C][C]-0.018742[/C][C]-0.3615[/C][C]0.358969[/C][/ROW]
[ROW][C]60[/C][C]-0.027922[/C][C]-0.5385[/C][C]0.29526[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28728&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28728&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95829718.4830
2-0.038138-0.73560.231227
30.1160082.23750.012923
40.2073453.99913.8e-05
50.0712951.37510.084967
6-0.216629-4.17821.8e-05
70.1778433.43010.000336
8-0.280159-5.40350
90.0515850.99490.160206
100.2214434.2711.2e-05
110.1890493.64620.000152
12-0.045031-0.86850.192833
13-0.550158-10.61110
140.0486850.9390.17417
150.1391522.68390.003802
160.0589661.13730.128074
170.1450152.7970.002713
180.0564151.08810.13863
190.0891681.71980.04315
20-0.085304-1.64530.050378
210.0107060.20650.418258
220.0204530.39450.346725
23-0.016396-0.31620.376
240.0564891.08950.138315
25-0.235006-4.53264e-06
260.008890.17150.431974
270.0490980.9470.172137
28-0.018295-0.35290.362198
29-0.002463-0.04750.481071
300.0294940.56890.284897
310.0502210.96860.16668
32-0.006361-0.12270.45121
330.0439290.84730.198693
340.016920.32630.372172
35-0.002393-0.04620.481607
360.0201210.38810.349091
37-0.189406-3.65310.000148
380.0123510.23820.405923
39-0.038849-0.74930.227076
40-0.033337-0.6430.260319
410.0326140.6290.264854
420.0928391.79060.037084
43-0.013284-0.25620.398966
440.0235280.45380.325119
450.0335990.6480.25868
460.0403740.77870.218321
470.0116450.22460.411208
48-0.024423-0.47110.31894
49-0.06699-1.29210.098569
50-0.031084-0.59950.274592
51-0.023084-0.44520.328206
52-0.061509-1.18630.118122
53-0.001646-0.03180.487343
54-0.002282-0.0440.482462
550.0011130.02150.491441
56-0.039442-0.76070.223649
57-0.0128-0.24690.402567
58-0.013281-0.25620.398983
59-0.018742-0.36150.358969
60-0.027922-0.53850.29526


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; 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')