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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 computationSun, 14 Dec 2008 15:33:34 -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/14/t1229294086xws679nprj9mce7.htm/, Retrieved Sat, 27 Apr 2024 22:59:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33581, Retrieved Sat, 27 Apr 2024 22:59:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact234
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   P   [Univariate Data Series] [Herproducering ti...] [2008-12-03 14:38:00] [6fea0e9a9b3b29a63badf2c274e82506]
- RMP     [Variance Reduction Matrix] [VRM airline data ...] [2008-12-14 22:20:27] [82d201ca7b4e7cd2c6f885d29b5b6937]
- RMP         [(Partial) Autocorrelation Function] [ACF : airline dat...] [2008-12-14 22:33:34] [00a0a665d7a07edd2e460056b0c0c354] [Current]
-   P           [(Partial) Autocorrelation Function] [ACF airline data ...] [2008-12-14 22:37:57] [82d201ca7b4e7cd2c6f885d29b5b6937]
-   P             [(Partial) Autocorrelation Function] [ACF airline data:...] [2008-12-14 22:40:26] [82d201ca7b4e7cd2c6f885d29b5b6937]
- RMP               [Spectral Analysis] [spectrum airline ...] [2008-12-14 22:51:59] [82d201ca7b4e7cd2c6f885d29b5b6937]
-   P                 [Spectral Analysis] [spectrum airline ...] [2008-12-14 22:54:22] [82d201ca7b4e7cd2c6f885d29b5b6937]
-   P                   [Spectral Analysis] [spectrum airline ...] [2008-12-14 22:57:41] [82d201ca7b4e7cd2c6f885d29b5b6937]
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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 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=33581&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=33581&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33581&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
10.95646918.44770
20.91206517.59130
30.87738416.92240
40.8614416.61490
50.85101116.41370
60.82017315.81890
70.79878615.40640
80.76029814.66410
90.73019114.08340
100.71951313.87750
110.72369113.95810
120.72797714.04070
130.67541413.02690
140.62508912.05630
150.58990311.37760
160.57672911.12350
170.57407211.07230
180.55541410.71240
190.54837410.57670
200.52446510.11550
210.5091849.82080
220.5132769.89970
230.52890110.20110
240.54631810.5370
250.5083149.8040
260.471179.08760
270.4468998.61950
280.4418218.52150
290.4436518.55680
300.4280028.2550
310.4219928.13910
320.3992257.70
330.3859187.44330
340.3891567.50580
350.4041127.79420
360.4212918.12560
370.3841347.40890
380.3481746.71530
390.3229496.22880
400.3161526.09770
410.3172086.11810
420.3030495.8450
430.2982995.75340
440.2785145.37180
450.268295.17460
460.2758575.32050
470.2953455.69640
480.3143356.06270
490.2824125.4470
500.2500924.82361e-06
510.2279294.39617e-06
520.2221674.2851.2e-05
530.2235234.31121e-05
540.2074414.0013.8e-05
550.2001543.86046.7e-05
560.1760043.39460.000381
570.1596923.080.001112
580.1583343.05380.001211
590.166613.21350.000713
600.1740883.35770.000434

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.956469 & 18.4477 & 0 \tabularnewline
2 & 0.912065 & 17.5913 & 0 \tabularnewline
3 & 0.877384 & 16.9224 & 0 \tabularnewline
4 & 0.86144 & 16.6149 & 0 \tabularnewline
5 & 0.851011 & 16.4137 & 0 \tabularnewline
6 & 0.820173 & 15.8189 & 0 \tabularnewline
7 & 0.798786 & 15.4064 & 0 \tabularnewline
8 & 0.760298 & 14.6641 & 0 \tabularnewline
9 & 0.730191 & 14.0834 & 0 \tabularnewline
10 & 0.719513 & 13.8775 & 0 \tabularnewline
11 & 0.723691 & 13.9581 & 0 \tabularnewline
12 & 0.727977 & 14.0407 & 0 \tabularnewline
13 & 0.675414 & 13.0269 & 0 \tabularnewline
14 & 0.625089 & 12.0563 & 0 \tabularnewline
15 & 0.589903 & 11.3776 & 0 \tabularnewline
16 & 0.576729 & 11.1235 & 0 \tabularnewline
17 & 0.574072 & 11.0723 & 0 \tabularnewline
18 & 0.555414 & 10.7124 & 0 \tabularnewline
19 & 0.548374 & 10.5767 & 0 \tabularnewline
20 & 0.524465 & 10.1155 & 0 \tabularnewline
21 & 0.509184 & 9.8208 & 0 \tabularnewline
22 & 0.513276 & 9.8997 & 0 \tabularnewline
23 & 0.528901 & 10.2011 & 0 \tabularnewline
24 & 0.546318 & 10.537 & 0 \tabularnewline
25 & 0.508314 & 9.804 & 0 \tabularnewline
26 & 0.47117 & 9.0876 & 0 \tabularnewline
27 & 0.446899 & 8.6195 & 0 \tabularnewline
28 & 0.441821 & 8.5215 & 0 \tabularnewline
29 & 0.443651 & 8.5568 & 0 \tabularnewline
30 & 0.428002 & 8.255 & 0 \tabularnewline
31 & 0.421992 & 8.1391 & 0 \tabularnewline
32 & 0.399225 & 7.7 & 0 \tabularnewline
33 & 0.385918 & 7.4433 & 0 \tabularnewline
34 & 0.389156 & 7.5058 & 0 \tabularnewline
35 & 0.404112 & 7.7942 & 0 \tabularnewline
36 & 0.421291 & 8.1256 & 0 \tabularnewline
37 & 0.384134 & 7.4089 & 0 \tabularnewline
38 & 0.348174 & 6.7153 & 0 \tabularnewline
39 & 0.322949 & 6.2288 & 0 \tabularnewline
40 & 0.316152 & 6.0977 & 0 \tabularnewline
41 & 0.317208 & 6.1181 & 0 \tabularnewline
42 & 0.303049 & 5.845 & 0 \tabularnewline
43 & 0.298299 & 5.7534 & 0 \tabularnewline
44 & 0.278514 & 5.3718 & 0 \tabularnewline
45 & 0.26829 & 5.1746 & 0 \tabularnewline
46 & 0.275857 & 5.3205 & 0 \tabularnewline
47 & 0.295345 & 5.6964 & 0 \tabularnewline
48 & 0.314335 & 6.0627 & 0 \tabularnewline
49 & 0.282412 & 5.447 & 0 \tabularnewline
50 & 0.250092 & 4.8236 & 1e-06 \tabularnewline
51 & 0.227929 & 4.3961 & 7e-06 \tabularnewline
52 & 0.222167 & 4.285 & 1.2e-05 \tabularnewline
53 & 0.223523 & 4.3112 & 1e-05 \tabularnewline
54 & 0.207441 & 4.001 & 3.8e-05 \tabularnewline
55 & 0.200154 & 3.8604 & 6.7e-05 \tabularnewline
56 & 0.176004 & 3.3946 & 0.000381 \tabularnewline
57 & 0.159692 & 3.08 & 0.001112 \tabularnewline
58 & 0.158334 & 3.0538 & 0.001211 \tabularnewline
59 & 0.16661 & 3.2135 & 0.000713 \tabularnewline
60 & 0.174088 & 3.3577 & 0.000434 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33581&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]0.956469[/C][C]18.4477[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.912065[/C][C]17.5913[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.877384[/C][C]16.9224[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.86144[/C][C]16.6149[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.851011[/C][C]16.4137[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.820173[/C][C]15.8189[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.798786[/C][C]15.4064[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.760298[/C][C]14.6641[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.730191[/C][C]14.0834[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.719513[/C][C]13.8775[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.723691[/C][C]13.9581[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.727977[/C][C]14.0407[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.675414[/C][C]13.0269[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.625089[/C][C]12.0563[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.589903[/C][C]11.3776[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.576729[/C][C]11.1235[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.574072[/C][C]11.0723[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.555414[/C][C]10.7124[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.548374[/C][C]10.5767[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.524465[/C][C]10.1155[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.509184[/C][C]9.8208[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.513276[/C][C]9.8997[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.528901[/C][C]10.2011[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.546318[/C][C]10.537[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.508314[/C][C]9.804[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.47117[/C][C]9.0876[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.446899[/C][C]8.6195[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.441821[/C][C]8.5215[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]0.443651[/C][C]8.5568[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.428002[/C][C]8.255[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0.421992[/C][C]8.1391[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0.399225[/C][C]7.7[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]0.385918[/C][C]7.4433[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]0.389156[/C][C]7.5058[/C][C]0[/C][/ROW]
[ROW][C]35[/C][C]0.404112[/C][C]7.7942[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.421291[/C][C]8.1256[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.384134[/C][C]7.4089[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]0.348174[/C][C]6.7153[/C][C]0[/C][/ROW]
[ROW][C]39[/C][C]0.322949[/C][C]6.2288[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]0.316152[/C][C]6.0977[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]0.317208[/C][C]6.1181[/C][C]0[/C][/ROW]
[ROW][C]42[/C][C]0.303049[/C][C]5.845[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]0.298299[/C][C]5.7534[/C][C]0[/C][/ROW]
[ROW][C]44[/C][C]0.278514[/C][C]5.3718[/C][C]0[/C][/ROW]
[ROW][C]45[/C][C]0.26829[/C][C]5.1746[/C][C]0[/C][/ROW]
[ROW][C]46[/C][C]0.275857[/C][C]5.3205[/C][C]0[/C][/ROW]
[ROW][C]47[/C][C]0.295345[/C][C]5.6964[/C][C]0[/C][/ROW]
[ROW][C]48[/C][C]0.314335[/C][C]6.0627[/C][C]0[/C][/ROW]
[ROW][C]49[/C][C]0.282412[/C][C]5.447[/C][C]0[/C][/ROW]
[ROW][C]50[/C][C]0.250092[/C][C]4.8236[/C][C]1e-06[/C][/ROW]
[ROW][C]51[/C][C]0.227929[/C][C]4.3961[/C][C]7e-06[/C][/ROW]
[ROW][C]52[/C][C]0.222167[/C][C]4.285[/C][C]1.2e-05[/C][/ROW]
[ROW][C]53[/C][C]0.223523[/C][C]4.3112[/C][C]1e-05[/C][/ROW]
[ROW][C]54[/C][C]0.207441[/C][C]4.001[/C][C]3.8e-05[/C][/ROW]
[ROW][C]55[/C][C]0.200154[/C][C]3.8604[/C][C]6.7e-05[/C][/ROW]
[ROW][C]56[/C][C]0.176004[/C][C]3.3946[/C][C]0.000381[/C][/ROW]
[ROW][C]57[/C][C]0.159692[/C][C]3.08[/C][C]0.001112[/C][/ROW]
[ROW][C]58[/C][C]0.158334[/C][C]3.0538[/C][C]0.001211[/C][/ROW]
[ROW][C]59[/C][C]0.16661[/C][C]3.2135[/C][C]0.000713[/C][/ROW]
[ROW][C]60[/C][C]0.174088[/C][C]3.3577[/C][C]0.000434[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33581&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33581&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
10.95646918.44770
20.91206517.59130
30.87738416.92240
40.8614416.61490
50.85101116.41370
60.82017315.81890
70.79878615.40640
80.76029814.66410
90.73019114.08340
100.71951313.87750
110.72369113.95810
120.72797714.04070
130.67541413.02690
140.62508912.05630
150.58990311.37760
160.57672911.12350
170.57407211.07230
180.55541410.71240
190.54837410.57670
200.52446510.11550
210.5091849.82080
220.5132769.89970
230.52890110.20110
240.54631810.5370
250.5083149.8040
260.471179.08760
270.4468998.61950
280.4418218.52150
290.4436518.55680
300.4280028.2550
310.4219928.13910
320.3992257.70
330.3859187.44330
340.3891567.50580
350.4041127.79420
360.4212918.12560
370.3841347.40890
380.3481746.71530
390.3229496.22880
400.3161526.09770
410.3172086.11810
420.3030495.8450
430.2982995.75340
440.2785145.37180
450.268295.17460
460.2758575.32050
470.2953455.69640
480.3143356.06270
490.2824125.4470
500.2500924.82361e-06
510.2279294.39617e-06
520.2221674.2851.2e-05
530.2235234.31121e-05
540.2074414.0013.8e-05
550.2001543.86046.7e-05
560.1760043.39460.000381
570.1596923.080.001112
580.1583343.05380.001211
590.166613.21350.000713
600.1740883.35770.000434







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95646918.44770
2-0.032497-0.62680.265592
30.0911711.75840.039747
40.200723.87136.4e-05
50.0695611.34160.090265
6-0.209037-4.03183.4e-05
70.1668573.21820.000702
8-0.254774-4.91391e-06
90.0483560.93270.175803
100.2322084.47875e-06
110.1668253.21760.000703
12-0.034933-0.67380.250442
13-0.556401-10.73150
140.0447460.8630.194337
150.1402232.70450.003577
160.0809851.5620.05957
170.1502622.89820.001988
180.0537431.03660.150306
190.1052052.02910.021579
20-0.072138-1.39140.082475
210.002760.05320.47879
220.0629611.21430.112692
23-0.032876-0.63410.263205
240.0655851.2650.10334
25-0.266582-5.14170
26-0.005407-0.10430.458498
270.0469980.90650.182637
28-0.001174-0.02260.490971
29-0.009349-0.18030.428501
300.0169350.32660.372067
310.0478870.92360.178143
32-0.000869-0.01680.493319
330.0621271.19830.11579
340.0122230.23570.406878
350.0098340.18970.424833
360.044830.86470.193892
37-0.209126-4.03353.3e-05
38-0.002877-0.05550.477892
39-0.020752-0.40030.3446
40-0.019189-0.37010.35576
410.036080.69590.243465
420.0787251.51840.064882
430.0125850.24270.404177
440.0190960.36830.356428
450.0319430.61610.269103
460.0349720.67450.250203
470.0020220.0390.484452
48-0.048842-0.9420.173395
49-0.090877-1.75280.040233
50-0.036081-0.69590.24346
51-0.011875-0.2290.409483
52-0.042367-0.81710.207185
530.0041280.07960.468293
54-0.031275-0.60320.273371
55-0.000872-0.01680.493299
56-0.020536-0.39610.346132
57-0.024868-0.47960.315887
58-0.032514-0.62710.265487
59-0.010155-0.19590.422416
60-0.029745-0.57370.28326

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.956469 & 18.4477 & 0 \tabularnewline
2 & -0.032497 & -0.6268 & 0.265592 \tabularnewline
3 & 0.091171 & 1.7584 & 0.039747 \tabularnewline
4 & 0.20072 & 3.8713 & 6.4e-05 \tabularnewline
5 & 0.069561 & 1.3416 & 0.090265 \tabularnewline
6 & -0.209037 & -4.0318 & 3.4e-05 \tabularnewline
7 & 0.166857 & 3.2182 & 0.000702 \tabularnewline
8 & -0.254774 & -4.9139 & 1e-06 \tabularnewline
9 & 0.048356 & 0.9327 & 0.175803 \tabularnewline
10 & 0.232208 & 4.4787 & 5e-06 \tabularnewline
11 & 0.166825 & 3.2176 & 0.000703 \tabularnewline
12 & -0.034933 & -0.6738 & 0.250442 \tabularnewline
13 & -0.556401 & -10.7315 & 0 \tabularnewline
14 & 0.044746 & 0.863 & 0.194337 \tabularnewline
15 & 0.140223 & 2.7045 & 0.003577 \tabularnewline
16 & 0.080985 & 1.562 & 0.05957 \tabularnewline
17 & 0.150262 & 2.8982 & 0.001988 \tabularnewline
18 & 0.053743 & 1.0366 & 0.150306 \tabularnewline
19 & 0.105205 & 2.0291 & 0.021579 \tabularnewline
20 & -0.072138 & -1.3914 & 0.082475 \tabularnewline
21 & 0.00276 & 0.0532 & 0.47879 \tabularnewline
22 & 0.062961 & 1.2143 & 0.112692 \tabularnewline
23 & -0.032876 & -0.6341 & 0.263205 \tabularnewline
24 & 0.065585 & 1.265 & 0.10334 \tabularnewline
25 & -0.266582 & -5.1417 & 0 \tabularnewline
26 & -0.005407 & -0.1043 & 0.458498 \tabularnewline
27 & 0.046998 & 0.9065 & 0.182637 \tabularnewline
28 & -0.001174 & -0.0226 & 0.490971 \tabularnewline
29 & -0.009349 & -0.1803 & 0.428501 \tabularnewline
30 & 0.016935 & 0.3266 & 0.372067 \tabularnewline
31 & 0.047887 & 0.9236 & 0.178143 \tabularnewline
32 & -0.000869 & -0.0168 & 0.493319 \tabularnewline
33 & 0.062127 & 1.1983 & 0.11579 \tabularnewline
34 & 0.012223 & 0.2357 & 0.406878 \tabularnewline
35 & 0.009834 & 0.1897 & 0.424833 \tabularnewline
36 & 0.04483 & 0.8647 & 0.193892 \tabularnewline
37 & -0.209126 & -4.0335 & 3.3e-05 \tabularnewline
38 & -0.002877 & -0.0555 & 0.477892 \tabularnewline
39 & -0.020752 & -0.4003 & 0.3446 \tabularnewline
40 & -0.019189 & -0.3701 & 0.35576 \tabularnewline
41 & 0.03608 & 0.6959 & 0.243465 \tabularnewline
42 & 0.078725 & 1.5184 & 0.064882 \tabularnewline
43 & 0.012585 & 0.2427 & 0.404177 \tabularnewline
44 & 0.019096 & 0.3683 & 0.356428 \tabularnewline
45 & 0.031943 & 0.6161 & 0.269103 \tabularnewline
46 & 0.034972 & 0.6745 & 0.250203 \tabularnewline
47 & 0.002022 & 0.039 & 0.484452 \tabularnewline
48 & -0.048842 & -0.942 & 0.173395 \tabularnewline
49 & -0.090877 & -1.7528 & 0.040233 \tabularnewline
50 & -0.036081 & -0.6959 & 0.24346 \tabularnewline
51 & -0.011875 & -0.229 & 0.409483 \tabularnewline
52 & -0.042367 & -0.8171 & 0.207185 \tabularnewline
53 & 0.004128 & 0.0796 & 0.468293 \tabularnewline
54 & -0.031275 & -0.6032 & 0.273371 \tabularnewline
55 & -0.000872 & -0.0168 & 0.493299 \tabularnewline
56 & -0.020536 & -0.3961 & 0.346132 \tabularnewline
57 & -0.024868 & -0.4796 & 0.315887 \tabularnewline
58 & -0.032514 & -0.6271 & 0.265487 \tabularnewline
59 & -0.010155 & -0.1959 & 0.422416 \tabularnewline
60 & -0.029745 & -0.5737 & 0.28326 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33581&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]0.956469[/C][C]18.4477[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.032497[/C][C]-0.6268[/C][C]0.265592[/C][/ROW]
[ROW][C]3[/C][C]0.091171[/C][C]1.7584[/C][C]0.039747[/C][/ROW]
[ROW][C]4[/C][C]0.20072[/C][C]3.8713[/C][C]6.4e-05[/C][/ROW]
[ROW][C]5[/C][C]0.069561[/C][C]1.3416[/C][C]0.090265[/C][/ROW]
[ROW][C]6[/C][C]-0.209037[/C][C]-4.0318[/C][C]3.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.166857[/C][C]3.2182[/C][C]0.000702[/C][/ROW]
[ROW][C]8[/C][C]-0.254774[/C][C]-4.9139[/C][C]1e-06[/C][/ROW]
[ROW][C]9[/C][C]0.048356[/C][C]0.9327[/C][C]0.175803[/C][/ROW]
[ROW][C]10[/C][C]0.232208[/C][C]4.4787[/C][C]5e-06[/C][/ROW]
[ROW][C]11[/C][C]0.166825[/C][C]3.2176[/C][C]0.000703[/C][/ROW]
[ROW][C]12[/C][C]-0.034933[/C][C]-0.6738[/C][C]0.250442[/C][/ROW]
[ROW][C]13[/C][C]-0.556401[/C][C]-10.7315[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.044746[/C][C]0.863[/C][C]0.194337[/C][/ROW]
[ROW][C]15[/C][C]0.140223[/C][C]2.7045[/C][C]0.003577[/C][/ROW]
[ROW][C]16[/C][C]0.080985[/C][C]1.562[/C][C]0.05957[/C][/ROW]
[ROW][C]17[/C][C]0.150262[/C][C]2.8982[/C][C]0.001988[/C][/ROW]
[ROW][C]18[/C][C]0.053743[/C][C]1.0366[/C][C]0.150306[/C][/ROW]
[ROW][C]19[/C][C]0.105205[/C][C]2.0291[/C][C]0.021579[/C][/ROW]
[ROW][C]20[/C][C]-0.072138[/C][C]-1.3914[/C][C]0.082475[/C][/ROW]
[ROW][C]21[/C][C]0.00276[/C][C]0.0532[/C][C]0.47879[/C][/ROW]
[ROW][C]22[/C][C]0.062961[/C][C]1.2143[/C][C]0.112692[/C][/ROW]
[ROW][C]23[/C][C]-0.032876[/C][C]-0.6341[/C][C]0.263205[/C][/ROW]
[ROW][C]24[/C][C]0.065585[/C][C]1.265[/C][C]0.10334[/C][/ROW]
[ROW][C]25[/C][C]-0.266582[/C][C]-5.1417[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]-0.005407[/C][C]-0.1043[/C][C]0.458498[/C][/ROW]
[ROW][C]27[/C][C]0.046998[/C][C]0.9065[/C][C]0.182637[/C][/ROW]
[ROW][C]28[/C][C]-0.001174[/C][C]-0.0226[/C][C]0.490971[/C][/ROW]
[ROW][C]29[/C][C]-0.009349[/C][C]-0.1803[/C][C]0.428501[/C][/ROW]
[ROW][C]30[/C][C]0.016935[/C][C]0.3266[/C][C]0.372067[/C][/ROW]
[ROW][C]31[/C][C]0.047887[/C][C]0.9236[/C][C]0.178143[/C][/ROW]
[ROW][C]32[/C][C]-0.000869[/C][C]-0.0168[/C][C]0.493319[/C][/ROW]
[ROW][C]33[/C][C]0.062127[/C][C]1.1983[/C][C]0.11579[/C][/ROW]
[ROW][C]34[/C][C]0.012223[/C][C]0.2357[/C][C]0.406878[/C][/ROW]
[ROW][C]35[/C][C]0.009834[/C][C]0.1897[/C][C]0.424833[/C][/ROW]
[ROW][C]36[/C][C]0.04483[/C][C]0.8647[/C][C]0.193892[/C][/ROW]
[ROW][C]37[/C][C]-0.209126[/C][C]-4.0335[/C][C]3.3e-05[/C][/ROW]
[ROW][C]38[/C][C]-0.002877[/C][C]-0.0555[/C][C]0.477892[/C][/ROW]
[ROW][C]39[/C][C]-0.020752[/C][C]-0.4003[/C][C]0.3446[/C][/ROW]
[ROW][C]40[/C][C]-0.019189[/C][C]-0.3701[/C][C]0.35576[/C][/ROW]
[ROW][C]41[/C][C]0.03608[/C][C]0.6959[/C][C]0.243465[/C][/ROW]
[ROW][C]42[/C][C]0.078725[/C][C]1.5184[/C][C]0.064882[/C][/ROW]
[ROW][C]43[/C][C]0.012585[/C][C]0.2427[/C][C]0.404177[/C][/ROW]
[ROW][C]44[/C][C]0.019096[/C][C]0.3683[/C][C]0.356428[/C][/ROW]
[ROW][C]45[/C][C]0.031943[/C][C]0.6161[/C][C]0.269103[/C][/ROW]
[ROW][C]46[/C][C]0.034972[/C][C]0.6745[/C][C]0.250203[/C][/ROW]
[ROW][C]47[/C][C]0.002022[/C][C]0.039[/C][C]0.484452[/C][/ROW]
[ROW][C]48[/C][C]-0.048842[/C][C]-0.942[/C][C]0.173395[/C][/ROW]
[ROW][C]49[/C][C]-0.090877[/C][C]-1.7528[/C][C]0.040233[/C][/ROW]
[ROW][C]50[/C][C]-0.036081[/C][C]-0.6959[/C][C]0.24346[/C][/ROW]
[ROW][C]51[/C][C]-0.011875[/C][C]-0.229[/C][C]0.409483[/C][/ROW]
[ROW][C]52[/C][C]-0.042367[/C][C]-0.8171[/C][C]0.207185[/C][/ROW]
[ROW][C]53[/C][C]0.004128[/C][C]0.0796[/C][C]0.468293[/C][/ROW]
[ROW][C]54[/C][C]-0.031275[/C][C]-0.6032[/C][C]0.273371[/C][/ROW]
[ROW][C]55[/C][C]-0.000872[/C][C]-0.0168[/C][C]0.493299[/C][/ROW]
[ROW][C]56[/C][C]-0.020536[/C][C]-0.3961[/C][C]0.346132[/C][/ROW]
[ROW][C]57[/C][C]-0.024868[/C][C]-0.4796[/C][C]0.315887[/C][/ROW]
[ROW][C]58[/C][C]-0.032514[/C][C]-0.6271[/C][C]0.265487[/C][/ROW]
[ROW][C]59[/C][C]-0.010155[/C][C]-0.1959[/C][C]0.422416[/C][/ROW]
[ROW][C]60[/C][C]-0.029745[/C][C]-0.5737[/C][C]0.28326[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33581&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33581&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
10.95646918.44770
2-0.032497-0.62680.265592
30.0911711.75840.039747
40.200723.87136.4e-05
50.0695611.34160.090265
6-0.209037-4.03183.4e-05
70.1668573.21820.000702
8-0.254774-4.91391e-06
90.0483560.93270.175803
100.2322084.47875e-06
110.1668253.21760.000703
12-0.034933-0.67380.250442
13-0.556401-10.73150
140.0447460.8630.194337
150.1402232.70450.003577
160.0809851.5620.05957
170.1502622.89820.001988
180.0537431.03660.150306
190.1052052.02910.021579
20-0.072138-1.39140.082475
210.002760.05320.47879
220.0629611.21430.112692
23-0.032876-0.63410.263205
240.0655851.2650.10334
25-0.266582-5.14170
26-0.005407-0.10430.458498
270.0469980.90650.182637
28-0.001174-0.02260.490971
29-0.009349-0.18030.428501
300.0169350.32660.372067
310.0478870.92360.178143
32-0.000869-0.01680.493319
330.0621271.19830.11579
340.0122230.23570.406878
350.0098340.18970.424833
360.044830.86470.193892
37-0.209126-4.03353.3e-05
38-0.002877-0.05550.477892
39-0.020752-0.40030.3446
40-0.019189-0.37010.35576
410.036080.69590.243465
420.0787251.51840.064882
430.0125850.24270.404177
440.0190960.36830.356428
450.0319430.61610.269103
460.0349720.67450.250203
470.0020220.0390.484452
48-0.048842-0.9420.173395
49-0.090877-1.75280.040233
50-0.036081-0.69590.24346
51-0.011875-0.2290.409483
52-0.042367-0.81710.207185
530.0041280.07960.468293
54-0.031275-0.60320.273371
55-0.000872-0.01680.493299
56-0.020536-0.39610.346132
57-0.024868-0.47960.315887
58-0.032514-0.62710.265487
59-0.010155-0.19590.422416
60-0.029745-0.57370.28326



Parameters (Session):
par1 = 60 ; par2 = 0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 0.5 ; 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')