Free Statistics

of Irreproducible Research!

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 computationSat, 06 Dec 2008 01:40:07 -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/06/t12285529291xx0kjvoqpnerii.htm/, Retrieved Sun, 10 Nov 2024 19:40:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29422, Retrieved Sun, 10 Nov 2024 19:40:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsjulie
Estimated Impact268
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [(Partial) Autocorrelation Function] [employment] [2008-12-06 08:40:07] [ff1af8c6f1c2f1c0e8def9bfc9355be9] [Current]
Feedback Forum
2008-12-11 16:06:48 [Katrijn Truyman] [reply
Om te onderzoeken of er AR processen zijn, moeten we kijken naar de ACF. Dit patroon vertoont overeenkomsten met de theoretische voorstellingen, dus er is sprake van een AR proces. De eerste 3 staafjes zijn significant (boven betrouwbaarheidsinterval) dus p=3. er is geen seizonaliteit dus P=0.
Vervolgens kijken we naar de PACF om te onderzoeken of er MA processen zijn.
er is geen patroon dat overeenkomt met de theoretische voorstellingen, dus q=0.
er is wel seizonaliteit (lag 12,24,36,48,...) dus Q=1.

Post a new message
Dataseries X:
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 12 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29422&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29422&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29422&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 time12 seconds
R Server'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1875523.55360.000215
20.3177946.02130
30.1795633.40220.000372
40.1553032.94260.001733
50.1275962.41760.008061
60.063711.20710.114087
7-0.054701-1.03640.150347
8-0.011735-0.22240.412083
9-0.080833-1.53160.063255
10-0.174708-3.31020.000513
11-0.055263-1.04710.147883
12-0.480698-9.10790
13-0.168514-3.19290.000767
14-0.172913-3.27620.000577
15-0.128287-2.43070.007779
16-0.163167-3.09160.001073
17-0.121097-2.29450.01117
18-0.103099-1.95340.025772
190.0201280.38140.351578
20-0.002775-0.05260.479049
21-0.006426-0.12170.451583
22-0.006358-0.12050.45209
23-0.004364-0.08270.467075
24-0.006343-0.12020.452205
250.0949111.79830.036484
26-0.008505-0.16110.436036
270.0176610.33460.369052
280.0770351.45960.072638
290.0680231.28880.09914
300.0416320.78880.215369
310.0328950.62330.266752
32-0.068171-1.29170.098653
330.0113230.21450.415122
340.0026740.05070.479811
35-0.0721-1.36610.08638
36-0.031172-0.59060.277571
37-0.113841-2.1570.015835
38-0.00152-0.02880.488517
39-0.046567-0.88230.189098
40-0.067976-1.2880.099295
41-0.105451-1.9980.023234
42-0.033256-0.63010.264511
43-0.158298-2.99930.001447
440.018370.34810.364001
45-0.043872-0.83130.203191
460.0211620.4010.34434
470.0421790.79920.21236
480.0976751.85070.032519

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.187552 & 3.5536 & 0.000215 \tabularnewline
2 & 0.317794 & 6.0213 & 0 \tabularnewline
3 & 0.179563 & 3.4022 & 0.000372 \tabularnewline
4 & 0.155303 & 2.9426 & 0.001733 \tabularnewline
5 & 0.127596 & 2.4176 & 0.008061 \tabularnewline
6 & 0.06371 & 1.2071 & 0.114087 \tabularnewline
7 & -0.054701 & -1.0364 & 0.150347 \tabularnewline
8 & -0.011735 & -0.2224 & 0.412083 \tabularnewline
9 & -0.080833 & -1.5316 & 0.063255 \tabularnewline
10 & -0.174708 & -3.3102 & 0.000513 \tabularnewline
11 & -0.055263 & -1.0471 & 0.147883 \tabularnewline
12 & -0.480698 & -9.1079 & 0 \tabularnewline
13 & -0.168514 & -3.1929 & 0.000767 \tabularnewline
14 & -0.172913 & -3.2762 & 0.000577 \tabularnewline
15 & -0.128287 & -2.4307 & 0.007779 \tabularnewline
16 & -0.163167 & -3.0916 & 0.001073 \tabularnewline
17 & -0.121097 & -2.2945 & 0.01117 \tabularnewline
18 & -0.103099 & -1.9534 & 0.025772 \tabularnewline
19 & 0.020128 & 0.3814 & 0.351578 \tabularnewline
20 & -0.002775 & -0.0526 & 0.479049 \tabularnewline
21 & -0.006426 & -0.1217 & 0.451583 \tabularnewline
22 & -0.006358 & -0.1205 & 0.45209 \tabularnewline
23 & -0.004364 & -0.0827 & 0.467075 \tabularnewline
24 & -0.006343 & -0.1202 & 0.452205 \tabularnewline
25 & 0.094911 & 1.7983 & 0.036484 \tabularnewline
26 & -0.008505 & -0.1611 & 0.436036 \tabularnewline
27 & 0.017661 & 0.3346 & 0.369052 \tabularnewline
28 & 0.077035 & 1.4596 & 0.072638 \tabularnewline
29 & 0.068023 & 1.2888 & 0.09914 \tabularnewline
30 & 0.041632 & 0.7888 & 0.215369 \tabularnewline
31 & 0.032895 & 0.6233 & 0.266752 \tabularnewline
32 & -0.068171 & -1.2917 & 0.098653 \tabularnewline
33 & 0.011323 & 0.2145 & 0.415122 \tabularnewline
34 & 0.002674 & 0.0507 & 0.479811 \tabularnewline
35 & -0.0721 & -1.3661 & 0.08638 \tabularnewline
36 & -0.031172 & -0.5906 & 0.277571 \tabularnewline
37 & -0.113841 & -2.157 & 0.015835 \tabularnewline
38 & -0.00152 & -0.0288 & 0.488517 \tabularnewline
39 & -0.046567 & -0.8823 & 0.189098 \tabularnewline
40 & -0.067976 & -1.288 & 0.099295 \tabularnewline
41 & -0.105451 & -1.998 & 0.023234 \tabularnewline
42 & -0.033256 & -0.6301 & 0.264511 \tabularnewline
43 & -0.158298 & -2.9993 & 0.001447 \tabularnewline
44 & 0.01837 & 0.3481 & 0.364001 \tabularnewline
45 & -0.043872 & -0.8313 & 0.203191 \tabularnewline
46 & 0.021162 & 0.401 & 0.34434 \tabularnewline
47 & 0.042179 & 0.7992 & 0.21236 \tabularnewline
48 & 0.097675 & 1.8507 & 0.032519 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29422&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]0.187552[/C][C]3.5536[/C][C]0.000215[/C][/ROW]
[ROW][C]2[/C][C]0.317794[/C][C]6.0213[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.179563[/C][C]3.4022[/C][C]0.000372[/C][/ROW]
[ROW][C]4[/C][C]0.155303[/C][C]2.9426[/C][C]0.001733[/C][/ROW]
[ROW][C]5[/C][C]0.127596[/C][C]2.4176[/C][C]0.008061[/C][/ROW]
[ROW][C]6[/C][C]0.06371[/C][C]1.2071[/C][C]0.114087[/C][/ROW]
[ROW][C]7[/C][C]-0.054701[/C][C]-1.0364[/C][C]0.150347[/C][/ROW]
[ROW][C]8[/C][C]-0.011735[/C][C]-0.2224[/C][C]0.412083[/C][/ROW]
[ROW][C]9[/C][C]-0.080833[/C][C]-1.5316[/C][C]0.063255[/C][/ROW]
[ROW][C]10[/C][C]-0.174708[/C][C]-3.3102[/C][C]0.000513[/C][/ROW]
[ROW][C]11[/C][C]-0.055263[/C][C]-1.0471[/C][C]0.147883[/C][/ROW]
[ROW][C]12[/C][C]-0.480698[/C][C]-9.1079[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.168514[/C][C]-3.1929[/C][C]0.000767[/C][/ROW]
[ROW][C]14[/C][C]-0.172913[/C][C]-3.2762[/C][C]0.000577[/C][/ROW]
[ROW][C]15[/C][C]-0.128287[/C][C]-2.4307[/C][C]0.007779[/C][/ROW]
[ROW][C]16[/C][C]-0.163167[/C][C]-3.0916[/C][C]0.001073[/C][/ROW]
[ROW][C]17[/C][C]-0.121097[/C][C]-2.2945[/C][C]0.01117[/C][/ROW]
[ROW][C]18[/C][C]-0.103099[/C][C]-1.9534[/C][C]0.025772[/C][/ROW]
[ROW][C]19[/C][C]0.020128[/C][C]0.3814[/C][C]0.351578[/C][/ROW]
[ROW][C]20[/C][C]-0.002775[/C][C]-0.0526[/C][C]0.479049[/C][/ROW]
[ROW][C]21[/C][C]-0.006426[/C][C]-0.1217[/C][C]0.451583[/C][/ROW]
[ROW][C]22[/C][C]-0.006358[/C][C]-0.1205[/C][C]0.45209[/C][/ROW]
[ROW][C]23[/C][C]-0.004364[/C][C]-0.0827[/C][C]0.467075[/C][/ROW]
[ROW][C]24[/C][C]-0.006343[/C][C]-0.1202[/C][C]0.452205[/C][/ROW]
[ROW][C]25[/C][C]0.094911[/C][C]1.7983[/C][C]0.036484[/C][/ROW]
[ROW][C]26[/C][C]-0.008505[/C][C]-0.1611[/C][C]0.436036[/C][/ROW]
[ROW][C]27[/C][C]0.017661[/C][C]0.3346[/C][C]0.369052[/C][/ROW]
[ROW][C]28[/C][C]0.077035[/C][C]1.4596[/C][C]0.072638[/C][/ROW]
[ROW][C]29[/C][C]0.068023[/C][C]1.2888[/C][C]0.09914[/C][/ROW]
[ROW][C]30[/C][C]0.041632[/C][C]0.7888[/C][C]0.215369[/C][/ROW]
[ROW][C]31[/C][C]0.032895[/C][C]0.6233[/C][C]0.266752[/C][/ROW]
[ROW][C]32[/C][C]-0.068171[/C][C]-1.2917[/C][C]0.098653[/C][/ROW]
[ROW][C]33[/C][C]0.011323[/C][C]0.2145[/C][C]0.415122[/C][/ROW]
[ROW][C]34[/C][C]0.002674[/C][C]0.0507[/C][C]0.479811[/C][/ROW]
[ROW][C]35[/C][C]-0.0721[/C][C]-1.3661[/C][C]0.08638[/C][/ROW]
[ROW][C]36[/C][C]-0.031172[/C][C]-0.5906[/C][C]0.277571[/C][/ROW]
[ROW][C]37[/C][C]-0.113841[/C][C]-2.157[/C][C]0.015835[/C][/ROW]
[ROW][C]38[/C][C]-0.00152[/C][C]-0.0288[/C][C]0.488517[/C][/ROW]
[ROW][C]39[/C][C]-0.046567[/C][C]-0.8823[/C][C]0.189098[/C][/ROW]
[ROW][C]40[/C][C]-0.067976[/C][C]-1.288[/C][C]0.099295[/C][/ROW]
[ROW][C]41[/C][C]-0.105451[/C][C]-1.998[/C][C]0.023234[/C][/ROW]
[ROW][C]42[/C][C]-0.033256[/C][C]-0.6301[/C][C]0.264511[/C][/ROW]
[ROW][C]43[/C][C]-0.158298[/C][C]-2.9993[/C][C]0.001447[/C][/ROW]
[ROW][C]44[/C][C]0.01837[/C][C]0.3481[/C][C]0.364001[/C][/ROW]
[ROW][C]45[/C][C]-0.043872[/C][C]-0.8313[/C][C]0.203191[/C][/ROW]
[ROW][C]46[/C][C]0.021162[/C][C]0.401[/C][C]0.34434[/C][/ROW]
[ROW][C]47[/C][C]0.042179[/C][C]0.7992[/C][C]0.21236[/C][/ROW]
[ROW][C]48[/C][C]0.097675[/C][C]1.8507[/C][C]0.032519[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29422&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29422&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
10.1875523.55360.000215
20.3177946.02130
30.1795633.40220.000372
40.1553032.94260.001733
50.1275962.41760.008061
60.063711.20710.114087
7-0.054701-1.03640.150347
8-0.011735-0.22240.412083
9-0.080833-1.53160.063255
10-0.174708-3.31020.000513
11-0.055263-1.04710.147883
12-0.480698-9.10790
13-0.168514-3.19290.000767
14-0.172913-3.27620.000577
15-0.128287-2.43070.007779
16-0.163167-3.09160.001073
17-0.121097-2.29450.01117
18-0.103099-1.95340.025772
190.0201280.38140.351578
20-0.002775-0.05260.479049
21-0.006426-0.12170.451583
22-0.006358-0.12050.45209
23-0.004364-0.08270.467075
24-0.006343-0.12020.452205
250.0949111.79830.036484
26-0.008505-0.16110.436036
270.0176610.33460.369052
280.0770351.45960.072638
290.0680231.28880.09914
300.0416320.78880.215369
310.0328950.62330.266752
32-0.068171-1.29170.098653
330.0113230.21450.415122
340.0026740.05070.479811
35-0.0721-1.36610.08638
36-0.031172-0.59060.277571
37-0.113841-2.1570.015835
38-0.00152-0.02880.488517
39-0.046567-0.88230.189098
40-0.067976-1.2880.099295
41-0.105451-1.9980.023234
42-0.033256-0.63010.264511
43-0.158298-2.99930.001447
440.018370.34810.364001
45-0.043872-0.83130.203191
460.0211620.4010.34434
470.0421790.79920.21236
480.0976751.85070.032519







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1875523.55360.000215
20.2929225.55010
30.0935121.77180.038638
40.0339950.64410.259959
50.0322140.61040.271005
6-0.024285-0.46010.322846
7-0.139405-2.64140.004309
8-0.030697-0.58160.280592
9-0.045877-0.86930.192645
10-0.156693-2.96890.001595
110.0375910.71220.238389
12-0.427945-8.10840
13-0.036401-0.68970.245414
140.1233192.33660.010006
150.0471120.89260.186322
16-0.060609-1.14840.125789
17-0.017722-0.33580.368615
180.0078180.14810.44116
190.0233680.44280.329106
200.0479830.90910.181941
21-0.03962-0.75070.226664
22-0.157258-2.97960.001541
230.0101950.19320.42347
24-0.263321-4.98920
250.0569861.07970.140495
260.0174520.33070.370544
27-0.01152-0.21830.413674
280.0337610.63970.261394
290.0357460.67730.249331
30-0.027638-0.52370.300414
310.0375680.71180.238523
32-0.076586-1.45110.073812
33-0.04242-0.80370.211038
34-0.086262-1.63440.051522
35-0.078156-1.48080.069763
36-0.219062-4.15062.1e-05
37-0.029885-0.56620.285794
380.0624081.18250.118901
39-0.055153-1.0450.148363
40-0.019687-0.3730.354676
41-0.030763-0.58290.280174
42-0.01269-0.24040.405061
43-0.11499-2.17870.015
44-0.017441-0.33050.37062
45-0.006089-0.11540.454112
460.0027430.0520.479293
47-0.026375-0.49970.308785
48-0.056646-1.07330.141932

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.187552 & 3.5536 & 0.000215 \tabularnewline
2 & 0.292922 & 5.5501 & 0 \tabularnewline
3 & 0.093512 & 1.7718 & 0.038638 \tabularnewline
4 & 0.033995 & 0.6441 & 0.259959 \tabularnewline
5 & 0.032214 & 0.6104 & 0.271005 \tabularnewline
6 & -0.024285 & -0.4601 & 0.322846 \tabularnewline
7 & -0.139405 & -2.6414 & 0.004309 \tabularnewline
8 & -0.030697 & -0.5816 & 0.280592 \tabularnewline
9 & -0.045877 & -0.8693 & 0.192645 \tabularnewline
10 & -0.156693 & -2.9689 & 0.001595 \tabularnewline
11 & 0.037591 & 0.7122 & 0.238389 \tabularnewline
12 & -0.427945 & -8.1084 & 0 \tabularnewline
13 & -0.036401 & -0.6897 & 0.245414 \tabularnewline
14 & 0.123319 & 2.3366 & 0.010006 \tabularnewline
15 & 0.047112 & 0.8926 & 0.186322 \tabularnewline
16 & -0.060609 & -1.1484 & 0.125789 \tabularnewline
17 & -0.017722 & -0.3358 & 0.368615 \tabularnewline
18 & 0.007818 & 0.1481 & 0.44116 \tabularnewline
19 & 0.023368 & 0.4428 & 0.329106 \tabularnewline
20 & 0.047983 & 0.9091 & 0.181941 \tabularnewline
21 & -0.03962 & -0.7507 & 0.226664 \tabularnewline
22 & -0.157258 & -2.9796 & 0.001541 \tabularnewline
23 & 0.010195 & 0.1932 & 0.42347 \tabularnewline
24 & -0.263321 & -4.9892 & 0 \tabularnewline
25 & 0.056986 & 1.0797 & 0.140495 \tabularnewline
26 & 0.017452 & 0.3307 & 0.370544 \tabularnewline
27 & -0.01152 & -0.2183 & 0.413674 \tabularnewline
28 & 0.033761 & 0.6397 & 0.261394 \tabularnewline
29 & 0.035746 & 0.6773 & 0.249331 \tabularnewline
30 & -0.027638 & -0.5237 & 0.300414 \tabularnewline
31 & 0.037568 & 0.7118 & 0.238523 \tabularnewline
32 & -0.076586 & -1.4511 & 0.073812 \tabularnewline
33 & -0.04242 & -0.8037 & 0.211038 \tabularnewline
34 & -0.086262 & -1.6344 & 0.051522 \tabularnewline
35 & -0.078156 & -1.4808 & 0.069763 \tabularnewline
36 & -0.219062 & -4.1506 & 2.1e-05 \tabularnewline
37 & -0.029885 & -0.5662 & 0.285794 \tabularnewline
38 & 0.062408 & 1.1825 & 0.118901 \tabularnewline
39 & -0.055153 & -1.045 & 0.148363 \tabularnewline
40 & -0.019687 & -0.373 & 0.354676 \tabularnewline
41 & -0.030763 & -0.5829 & 0.280174 \tabularnewline
42 & -0.01269 & -0.2404 & 0.405061 \tabularnewline
43 & -0.11499 & -2.1787 & 0.015 \tabularnewline
44 & -0.017441 & -0.3305 & 0.37062 \tabularnewline
45 & -0.006089 & -0.1154 & 0.454112 \tabularnewline
46 & 0.002743 & 0.052 & 0.479293 \tabularnewline
47 & -0.026375 & -0.4997 & 0.308785 \tabularnewline
48 & -0.056646 & -1.0733 & 0.141932 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29422&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]0.187552[/C][C]3.5536[/C][C]0.000215[/C][/ROW]
[ROW][C]2[/C][C]0.292922[/C][C]5.5501[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.093512[/C][C]1.7718[/C][C]0.038638[/C][/ROW]
[ROW][C]4[/C][C]0.033995[/C][C]0.6441[/C][C]0.259959[/C][/ROW]
[ROW][C]5[/C][C]0.032214[/C][C]0.6104[/C][C]0.271005[/C][/ROW]
[ROW][C]6[/C][C]-0.024285[/C][C]-0.4601[/C][C]0.322846[/C][/ROW]
[ROW][C]7[/C][C]-0.139405[/C][C]-2.6414[/C][C]0.004309[/C][/ROW]
[ROW][C]8[/C][C]-0.030697[/C][C]-0.5816[/C][C]0.280592[/C][/ROW]
[ROW][C]9[/C][C]-0.045877[/C][C]-0.8693[/C][C]0.192645[/C][/ROW]
[ROW][C]10[/C][C]-0.156693[/C][C]-2.9689[/C][C]0.001595[/C][/ROW]
[ROW][C]11[/C][C]0.037591[/C][C]0.7122[/C][C]0.238389[/C][/ROW]
[ROW][C]12[/C][C]-0.427945[/C][C]-8.1084[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.036401[/C][C]-0.6897[/C][C]0.245414[/C][/ROW]
[ROW][C]14[/C][C]0.123319[/C][C]2.3366[/C][C]0.010006[/C][/ROW]
[ROW][C]15[/C][C]0.047112[/C][C]0.8926[/C][C]0.186322[/C][/ROW]
[ROW][C]16[/C][C]-0.060609[/C][C]-1.1484[/C][C]0.125789[/C][/ROW]
[ROW][C]17[/C][C]-0.017722[/C][C]-0.3358[/C][C]0.368615[/C][/ROW]
[ROW][C]18[/C][C]0.007818[/C][C]0.1481[/C][C]0.44116[/C][/ROW]
[ROW][C]19[/C][C]0.023368[/C][C]0.4428[/C][C]0.329106[/C][/ROW]
[ROW][C]20[/C][C]0.047983[/C][C]0.9091[/C][C]0.181941[/C][/ROW]
[ROW][C]21[/C][C]-0.03962[/C][C]-0.7507[/C][C]0.226664[/C][/ROW]
[ROW][C]22[/C][C]-0.157258[/C][C]-2.9796[/C][C]0.001541[/C][/ROW]
[ROW][C]23[/C][C]0.010195[/C][C]0.1932[/C][C]0.42347[/C][/ROW]
[ROW][C]24[/C][C]-0.263321[/C][C]-4.9892[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.056986[/C][C]1.0797[/C][C]0.140495[/C][/ROW]
[ROW][C]26[/C][C]0.017452[/C][C]0.3307[/C][C]0.370544[/C][/ROW]
[ROW][C]27[/C][C]-0.01152[/C][C]-0.2183[/C][C]0.413674[/C][/ROW]
[ROW][C]28[/C][C]0.033761[/C][C]0.6397[/C][C]0.261394[/C][/ROW]
[ROW][C]29[/C][C]0.035746[/C][C]0.6773[/C][C]0.249331[/C][/ROW]
[ROW][C]30[/C][C]-0.027638[/C][C]-0.5237[/C][C]0.300414[/C][/ROW]
[ROW][C]31[/C][C]0.037568[/C][C]0.7118[/C][C]0.238523[/C][/ROW]
[ROW][C]32[/C][C]-0.076586[/C][C]-1.4511[/C][C]0.073812[/C][/ROW]
[ROW][C]33[/C][C]-0.04242[/C][C]-0.8037[/C][C]0.211038[/C][/ROW]
[ROW][C]34[/C][C]-0.086262[/C][C]-1.6344[/C][C]0.051522[/C][/ROW]
[ROW][C]35[/C][C]-0.078156[/C][C]-1.4808[/C][C]0.069763[/C][/ROW]
[ROW][C]36[/C][C]-0.219062[/C][C]-4.1506[/C][C]2.1e-05[/C][/ROW]
[ROW][C]37[/C][C]-0.029885[/C][C]-0.5662[/C][C]0.285794[/C][/ROW]
[ROW][C]38[/C][C]0.062408[/C][C]1.1825[/C][C]0.118901[/C][/ROW]
[ROW][C]39[/C][C]-0.055153[/C][C]-1.045[/C][C]0.148363[/C][/ROW]
[ROW][C]40[/C][C]-0.019687[/C][C]-0.373[/C][C]0.354676[/C][/ROW]
[ROW][C]41[/C][C]-0.030763[/C][C]-0.5829[/C][C]0.280174[/C][/ROW]
[ROW][C]42[/C][C]-0.01269[/C][C]-0.2404[/C][C]0.405061[/C][/ROW]
[ROW][C]43[/C][C]-0.11499[/C][C]-2.1787[/C][C]0.015[/C][/ROW]
[ROW][C]44[/C][C]-0.017441[/C][C]-0.3305[/C][C]0.37062[/C][/ROW]
[ROW][C]45[/C][C]-0.006089[/C][C]-0.1154[/C][C]0.454112[/C][/ROW]
[ROW][C]46[/C][C]0.002743[/C][C]0.052[/C][C]0.479293[/C][/ROW]
[ROW][C]47[/C][C]-0.026375[/C][C]-0.4997[/C][C]0.308785[/C][/ROW]
[ROW][C]48[/C][C]-0.056646[/C][C]-1.0733[/C][C]0.141932[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29422&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29422&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
10.1875523.55360.000215
20.2929225.55010
30.0935121.77180.038638
40.0339950.64410.259959
50.0322140.61040.271005
6-0.024285-0.46010.322846
7-0.139405-2.64140.004309
8-0.030697-0.58160.280592
9-0.045877-0.86930.192645
10-0.156693-2.96890.001595
110.0375910.71220.238389
12-0.427945-8.10840
13-0.036401-0.68970.245414
140.1233192.33660.010006
150.0471120.89260.186322
16-0.060609-1.14840.125789
17-0.017722-0.33580.368615
180.0078180.14810.44116
190.0233680.44280.329106
200.0479830.90910.181941
21-0.03962-0.75070.226664
22-0.157258-2.97960.001541
230.0101950.19320.42347
24-0.263321-4.98920
250.0569861.07970.140495
260.0174520.33070.370544
27-0.01152-0.21830.413674
280.0337610.63970.261394
290.0357460.67730.249331
30-0.027638-0.52370.300414
310.0375680.71180.238523
32-0.076586-1.45110.073812
33-0.04242-0.80370.211038
34-0.086262-1.63440.051522
35-0.078156-1.48080.069763
36-0.219062-4.15062.1e-05
37-0.029885-0.56620.285794
380.0624081.18250.118901
39-0.055153-1.0450.148363
40-0.019687-0.3730.354676
41-0.030763-0.58290.280174
42-0.01269-0.24040.405061
43-0.11499-2.17870.015
44-0.017441-0.33050.37062
45-0.006089-0.11540.454112
460.0027430.0520.479293
47-0.026375-0.49970.308785
48-0.056646-1.07330.141932



Parameters (Session):
par1 = 48 ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; 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')