Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 14 May 2009 07:58:58 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/14/t1242309575jtnr4kx801tt4ix.htm/, Retrieved Mon, 29 Apr 2024 06:48:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40001, Retrieved Mon, 29 Apr 2024 06:48:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [opgave 6 bis oef ...] [2009-05-14 13:58:58] [35929c65abb99b6a5fe7f94d9e3dcf69] [Current]
Feedback Forum

Post a new message
Dataseries X:
580
579
572
560
551
537
541
588
607
599
578
563
566
561
554
540
526
512
505
554
584
569
540
522
526
527
516
503
489
479
475
524
552
532
511
492
492
493
481
462
457
442
439
488
521
501
485
464
460
467
460
448
443
436
431
484
510
513
503
471
471
476
475
470
461
455
456
517
525
523
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516




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=40001&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=40001&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40001&T=0

As an alternative you can also use a QR Code:  

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

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







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3055993.66720.000172
2-0.234266-2.81120.002812
3-0.348944-4.18732.4e-05
4-0.267478-3.20970.000819
50.0659890.79190.214868
60.1889542.26740.012426
70.0462430.55490.289905
8-0.250134-3.00160.001583
9-0.31583-3.790.00011
10-0.213672-2.56410.005685
110.3054273.66510.000173
120.86349710.3620
130.2610553.13270.001049
14-0.20045-2.40540.008712
15-0.330434-3.96525.8e-05
16-0.259598-3.11520.001109
170.0565820.6790.24912
180.1548181.85780.032618
190.0316510.37980.352321
20-0.243594-2.92310.002013
21-0.28984-3.47810.000334
22-0.175878-2.11050.01827
230.2859933.43190.000391
240.7384638.86160
250.2165012.5980.005176
26-0.186679-2.24020.013306
27-0.306193-3.67430.000168
28-0.249855-2.99830.0016
290.0390880.46910.319871
300.125561.50670.067037
310.0220150.26420.39601
32-0.226692-2.72030.003663
33-0.255212-3.06250.00131
34-0.164685-1.97620.02502
350.2446462.93570.001937
360.6551927.86230
370.1868082.24170.013255
38-0.161913-1.9430.026986
39-0.298072-3.57690.000237
40-0.235775-2.82930.002666
410.0223850.26860.394303
420.1162851.39540.082519
430.0220520.26460.395841
44-0.2157-2.58840.005315
45-0.232981-2.79580.002942
46-0.142538-1.71050.044668
470.2210022.6520.004449
480.5665836.7990

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.305599 & 3.6672 & 0.000172 \tabularnewline
2 & -0.234266 & -2.8112 & 0.002812 \tabularnewline
3 & -0.348944 & -4.1873 & 2.4e-05 \tabularnewline
4 & -0.267478 & -3.2097 & 0.000819 \tabularnewline
5 & 0.065989 & 0.7919 & 0.214868 \tabularnewline
6 & 0.188954 & 2.2674 & 0.012426 \tabularnewline
7 & 0.046243 & 0.5549 & 0.289905 \tabularnewline
8 & -0.250134 & -3.0016 & 0.001583 \tabularnewline
9 & -0.31583 & -3.79 & 0.00011 \tabularnewline
10 & -0.213672 & -2.5641 & 0.005685 \tabularnewline
11 & 0.305427 & 3.6651 & 0.000173 \tabularnewline
12 & 0.863497 & 10.362 & 0 \tabularnewline
13 & 0.261055 & 3.1327 & 0.001049 \tabularnewline
14 & -0.20045 & -2.4054 & 0.008712 \tabularnewline
15 & -0.330434 & -3.9652 & 5.8e-05 \tabularnewline
16 & -0.259598 & -3.1152 & 0.001109 \tabularnewline
17 & 0.056582 & 0.679 & 0.24912 \tabularnewline
18 & 0.154818 & 1.8578 & 0.032618 \tabularnewline
19 & 0.031651 & 0.3798 & 0.352321 \tabularnewline
20 & -0.243594 & -2.9231 & 0.002013 \tabularnewline
21 & -0.28984 & -3.4781 & 0.000334 \tabularnewline
22 & -0.175878 & -2.1105 & 0.01827 \tabularnewline
23 & 0.285993 & 3.4319 & 0.000391 \tabularnewline
24 & 0.738463 & 8.8616 & 0 \tabularnewline
25 & 0.216501 & 2.598 & 0.005176 \tabularnewline
26 & -0.186679 & -2.2402 & 0.013306 \tabularnewline
27 & -0.306193 & -3.6743 & 0.000168 \tabularnewline
28 & -0.249855 & -2.9983 & 0.0016 \tabularnewline
29 & 0.039088 & 0.4691 & 0.319871 \tabularnewline
30 & 0.12556 & 1.5067 & 0.067037 \tabularnewline
31 & 0.022015 & 0.2642 & 0.39601 \tabularnewline
32 & -0.226692 & -2.7203 & 0.003663 \tabularnewline
33 & -0.255212 & -3.0625 & 0.00131 \tabularnewline
34 & -0.164685 & -1.9762 & 0.02502 \tabularnewline
35 & 0.244646 & 2.9357 & 0.001937 \tabularnewline
36 & 0.655192 & 7.8623 & 0 \tabularnewline
37 & 0.186808 & 2.2417 & 0.013255 \tabularnewline
38 & -0.161913 & -1.943 & 0.026986 \tabularnewline
39 & -0.298072 & -3.5769 & 0.000237 \tabularnewline
40 & -0.235775 & -2.8293 & 0.002666 \tabularnewline
41 & 0.022385 & 0.2686 & 0.394303 \tabularnewline
42 & 0.116285 & 1.3954 & 0.082519 \tabularnewline
43 & 0.022052 & 0.2646 & 0.395841 \tabularnewline
44 & -0.2157 & -2.5884 & 0.005315 \tabularnewline
45 & -0.232981 & -2.7958 & 0.002942 \tabularnewline
46 & -0.142538 & -1.7105 & 0.044668 \tabularnewline
47 & 0.221002 & 2.652 & 0.004449 \tabularnewline
48 & 0.566583 & 6.799 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40001&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]0.305599[/C][C]3.6672[/C][C]0.000172[/C][/ROW]
[ROW][C]2[/C][C]-0.234266[/C][C]-2.8112[/C][C]0.002812[/C][/ROW]
[ROW][C]3[/C][C]-0.348944[/C][C]-4.1873[/C][C]2.4e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.267478[/C][C]-3.2097[/C][C]0.000819[/C][/ROW]
[ROW][C]5[/C][C]0.065989[/C][C]0.7919[/C][C]0.214868[/C][/ROW]
[ROW][C]6[/C][C]0.188954[/C][C]2.2674[/C][C]0.012426[/C][/ROW]
[ROW][C]7[/C][C]0.046243[/C][C]0.5549[/C][C]0.289905[/C][/ROW]
[ROW][C]8[/C][C]-0.250134[/C][C]-3.0016[/C][C]0.001583[/C][/ROW]
[ROW][C]9[/C][C]-0.31583[/C][C]-3.79[/C][C]0.00011[/C][/ROW]
[ROW][C]10[/C][C]-0.213672[/C][C]-2.5641[/C][C]0.005685[/C][/ROW]
[ROW][C]11[/C][C]0.305427[/C][C]3.6651[/C][C]0.000173[/C][/ROW]
[ROW][C]12[/C][C]0.863497[/C][C]10.362[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.261055[/C][C]3.1327[/C][C]0.001049[/C][/ROW]
[ROW][C]14[/C][C]-0.20045[/C][C]-2.4054[/C][C]0.008712[/C][/ROW]
[ROW][C]15[/C][C]-0.330434[/C][C]-3.9652[/C][C]5.8e-05[/C][/ROW]
[ROW][C]16[/C][C]-0.259598[/C][C]-3.1152[/C][C]0.001109[/C][/ROW]
[ROW][C]17[/C][C]0.056582[/C][C]0.679[/C][C]0.24912[/C][/ROW]
[ROW][C]18[/C][C]0.154818[/C][C]1.8578[/C][C]0.032618[/C][/ROW]
[ROW][C]19[/C][C]0.031651[/C][C]0.3798[/C][C]0.352321[/C][/ROW]
[ROW][C]20[/C][C]-0.243594[/C][C]-2.9231[/C][C]0.002013[/C][/ROW]
[ROW][C]21[/C][C]-0.28984[/C][C]-3.4781[/C][C]0.000334[/C][/ROW]
[ROW][C]22[/C][C]-0.175878[/C][C]-2.1105[/C][C]0.01827[/C][/ROW]
[ROW][C]23[/C][C]0.285993[/C][C]3.4319[/C][C]0.000391[/C][/ROW]
[ROW][C]24[/C][C]0.738463[/C][C]8.8616[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.216501[/C][C]2.598[/C][C]0.005176[/C][/ROW]
[ROW][C]26[/C][C]-0.186679[/C][C]-2.2402[/C][C]0.013306[/C][/ROW]
[ROW][C]27[/C][C]-0.306193[/C][C]-3.6743[/C][C]0.000168[/C][/ROW]
[ROW][C]28[/C][C]-0.249855[/C][C]-2.9983[/C][C]0.0016[/C][/ROW]
[ROW][C]29[/C][C]0.039088[/C][C]0.4691[/C][C]0.319871[/C][/ROW]
[ROW][C]30[/C][C]0.12556[/C][C]1.5067[/C][C]0.067037[/C][/ROW]
[ROW][C]31[/C][C]0.022015[/C][C]0.2642[/C][C]0.39601[/C][/ROW]
[ROW][C]32[/C][C]-0.226692[/C][C]-2.7203[/C][C]0.003663[/C][/ROW]
[ROW][C]33[/C][C]-0.255212[/C][C]-3.0625[/C][C]0.00131[/C][/ROW]
[ROW][C]34[/C][C]-0.164685[/C][C]-1.9762[/C][C]0.02502[/C][/ROW]
[ROW][C]35[/C][C]0.244646[/C][C]2.9357[/C][C]0.001937[/C][/ROW]
[ROW][C]36[/C][C]0.655192[/C][C]7.8623[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.186808[/C][C]2.2417[/C][C]0.013255[/C][/ROW]
[ROW][C]38[/C][C]-0.161913[/C][C]-1.943[/C][C]0.026986[/C][/ROW]
[ROW][C]39[/C][C]-0.298072[/C][C]-3.5769[/C][C]0.000237[/C][/ROW]
[ROW][C]40[/C][C]-0.235775[/C][C]-2.8293[/C][C]0.002666[/C][/ROW]
[ROW][C]41[/C][C]0.022385[/C][C]0.2686[/C][C]0.394303[/C][/ROW]
[ROW][C]42[/C][C]0.116285[/C][C]1.3954[/C][C]0.082519[/C][/ROW]
[ROW][C]43[/C][C]0.022052[/C][C]0.2646[/C][C]0.395841[/C][/ROW]
[ROW][C]44[/C][C]-0.2157[/C][C]-2.5884[/C][C]0.005315[/C][/ROW]
[ROW][C]45[/C][C]-0.232981[/C][C]-2.7958[/C][C]0.002942[/C][/ROW]
[ROW][C]46[/C][C]-0.142538[/C][C]-1.7105[/C][C]0.044668[/C][/ROW]
[ROW][C]47[/C][C]0.221002[/C][C]2.652[/C][C]0.004449[/C][/ROW]
[ROW][C]48[/C][C]0.566583[/C][C]6.799[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40001&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40001&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
10.3055993.66720.000172
2-0.234266-2.81120.002812
3-0.348944-4.18732.4e-05
4-0.267478-3.20970.000819
50.0659890.79190.214868
60.1889542.26740.012426
70.0462430.55490.289905
8-0.250134-3.00160.001583
9-0.31583-3.790.00011
10-0.213672-2.56410.005685
110.3054273.66510.000173
120.86349710.3620
130.2610553.13270.001049
14-0.20045-2.40540.008712
15-0.330434-3.96525.8e-05
16-0.259598-3.11520.001109
170.0565820.6790.24912
180.1548181.85780.032618
190.0316510.37980.352321
20-0.243594-2.92310.002013
21-0.28984-3.47810.000334
22-0.175878-2.11050.01827
230.2859933.43190.000391
240.7384638.86160
250.2165012.5980.005176
26-0.186679-2.24020.013306
27-0.306193-3.67430.000168
28-0.249855-2.99830.0016
290.0390880.46910.319871
300.125561.50670.067037
310.0220150.26420.39601
32-0.226692-2.72030.003663
33-0.255212-3.06250.00131
34-0.164685-1.97620.02502
350.2446462.93570.001937
360.6551927.86230
370.1868082.24170.013255
38-0.161913-1.9430.026986
39-0.298072-3.57690.000237
40-0.235775-2.82930.002666
410.0223850.26860.394303
420.1162851.39540.082519
430.0220520.26460.395841
44-0.2157-2.58840.005315
45-0.232981-2.79580.002942
46-0.142538-1.71050.044668
470.2210022.6520.004449
480.5665836.7990







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3055993.66720.000172
2-0.361409-4.33691.4e-05
3-0.178932-2.14720.016727
4-0.206318-2.47580.007226
50.0922991.10760.134943
6-0.044666-0.5360.296394
7-0.088651-1.06380.144598
8-0.298018-3.57620.000238
9-0.184704-2.21640.014115
10-0.32476-3.89717.4e-05
110.2687723.22530.000779
120.7437758.92530
13-0.133928-1.60710.055107
140.1958582.35030.010058
150.0850981.02120.154442
160.0393450.47210.318769
17-0.066135-0.79360.214362
18-0.066909-0.80290.211675
190.0113260.13590.446038
20-0.131075-1.57290.058968
21-0.014393-0.17270.43156
220.0183940.22070.412807
23-0.102183-1.22620.111063
24-0.013433-0.16120.436082
25-0.050631-0.60760.272213
26-0.069009-0.82810.20449
27-0.004979-0.05970.476219
28-0.073904-0.88680.18832
29-0.03029-0.36350.358388
30-0.045685-0.54820.292194
310.0004410.00530.497892
320.0007650.00920.496342
330.0013870.01660.493372
34-0.096709-1.16050.123881
35-0.060603-0.72720.234129
360.07280.87360.191894
37-0.063289-0.75950.224408
380.0216850.26020.397533
39-0.083143-0.99770.160045
400.0705960.84720.199158
41-0.09016-1.08190.140549
420.0623980.74880.227607
43-0.014882-0.17860.429259
44-0.063159-0.75790.224871
45-0.029937-0.35920.35997
460.0506860.60820.271997
47-0.04202-0.50420.307432
48-0.089703-1.07640.141765

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.305599 & 3.6672 & 0.000172 \tabularnewline
2 & -0.361409 & -4.3369 & 1.4e-05 \tabularnewline
3 & -0.178932 & -2.1472 & 0.016727 \tabularnewline
4 & -0.206318 & -2.4758 & 0.007226 \tabularnewline
5 & 0.092299 & 1.1076 & 0.134943 \tabularnewline
6 & -0.044666 & -0.536 & 0.296394 \tabularnewline
7 & -0.088651 & -1.0638 & 0.144598 \tabularnewline
8 & -0.298018 & -3.5762 & 0.000238 \tabularnewline
9 & -0.184704 & -2.2164 & 0.014115 \tabularnewline
10 & -0.32476 & -3.8971 & 7.4e-05 \tabularnewline
11 & 0.268772 & 3.2253 & 0.000779 \tabularnewline
12 & 0.743775 & 8.9253 & 0 \tabularnewline
13 & -0.133928 & -1.6071 & 0.055107 \tabularnewline
14 & 0.195858 & 2.3503 & 0.010058 \tabularnewline
15 & 0.085098 & 1.0212 & 0.154442 \tabularnewline
16 & 0.039345 & 0.4721 & 0.318769 \tabularnewline
17 & -0.066135 & -0.7936 & 0.214362 \tabularnewline
18 & -0.066909 & -0.8029 & 0.211675 \tabularnewline
19 & 0.011326 & 0.1359 & 0.446038 \tabularnewline
20 & -0.131075 & -1.5729 & 0.058968 \tabularnewline
21 & -0.014393 & -0.1727 & 0.43156 \tabularnewline
22 & 0.018394 & 0.2207 & 0.412807 \tabularnewline
23 & -0.102183 & -1.2262 & 0.111063 \tabularnewline
24 & -0.013433 & -0.1612 & 0.436082 \tabularnewline
25 & -0.050631 & -0.6076 & 0.272213 \tabularnewline
26 & -0.069009 & -0.8281 & 0.20449 \tabularnewline
27 & -0.004979 & -0.0597 & 0.476219 \tabularnewline
28 & -0.073904 & -0.8868 & 0.18832 \tabularnewline
29 & -0.03029 & -0.3635 & 0.358388 \tabularnewline
30 & -0.045685 & -0.5482 & 0.292194 \tabularnewline
31 & 0.000441 & 0.0053 & 0.497892 \tabularnewline
32 & 0.000765 & 0.0092 & 0.496342 \tabularnewline
33 & 0.001387 & 0.0166 & 0.493372 \tabularnewline
34 & -0.096709 & -1.1605 & 0.123881 \tabularnewline
35 & -0.060603 & -0.7272 & 0.234129 \tabularnewline
36 & 0.0728 & 0.8736 & 0.191894 \tabularnewline
37 & -0.063289 & -0.7595 & 0.224408 \tabularnewline
38 & 0.021685 & 0.2602 & 0.397533 \tabularnewline
39 & -0.083143 & -0.9977 & 0.160045 \tabularnewline
40 & 0.070596 & 0.8472 & 0.199158 \tabularnewline
41 & -0.09016 & -1.0819 & 0.140549 \tabularnewline
42 & 0.062398 & 0.7488 & 0.227607 \tabularnewline
43 & -0.014882 & -0.1786 & 0.429259 \tabularnewline
44 & -0.063159 & -0.7579 & 0.224871 \tabularnewline
45 & -0.029937 & -0.3592 & 0.35997 \tabularnewline
46 & 0.050686 & 0.6082 & 0.271997 \tabularnewline
47 & -0.04202 & -0.5042 & 0.307432 \tabularnewline
48 & -0.089703 & -1.0764 & 0.141765 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40001&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]0.305599[/C][C]3.6672[/C][C]0.000172[/C][/ROW]
[ROW][C]2[/C][C]-0.361409[/C][C]-4.3369[/C][C]1.4e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.178932[/C][C]-2.1472[/C][C]0.016727[/C][/ROW]
[ROW][C]4[/C][C]-0.206318[/C][C]-2.4758[/C][C]0.007226[/C][/ROW]
[ROW][C]5[/C][C]0.092299[/C][C]1.1076[/C][C]0.134943[/C][/ROW]
[ROW][C]6[/C][C]-0.044666[/C][C]-0.536[/C][C]0.296394[/C][/ROW]
[ROW][C]7[/C][C]-0.088651[/C][C]-1.0638[/C][C]0.144598[/C][/ROW]
[ROW][C]8[/C][C]-0.298018[/C][C]-3.5762[/C][C]0.000238[/C][/ROW]
[ROW][C]9[/C][C]-0.184704[/C][C]-2.2164[/C][C]0.014115[/C][/ROW]
[ROW][C]10[/C][C]-0.32476[/C][C]-3.8971[/C][C]7.4e-05[/C][/ROW]
[ROW][C]11[/C][C]0.268772[/C][C]3.2253[/C][C]0.000779[/C][/ROW]
[ROW][C]12[/C][C]0.743775[/C][C]8.9253[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.133928[/C][C]-1.6071[/C][C]0.055107[/C][/ROW]
[ROW][C]14[/C][C]0.195858[/C][C]2.3503[/C][C]0.010058[/C][/ROW]
[ROW][C]15[/C][C]0.085098[/C][C]1.0212[/C][C]0.154442[/C][/ROW]
[ROW][C]16[/C][C]0.039345[/C][C]0.4721[/C][C]0.318769[/C][/ROW]
[ROW][C]17[/C][C]-0.066135[/C][C]-0.7936[/C][C]0.214362[/C][/ROW]
[ROW][C]18[/C][C]-0.066909[/C][C]-0.8029[/C][C]0.211675[/C][/ROW]
[ROW][C]19[/C][C]0.011326[/C][C]0.1359[/C][C]0.446038[/C][/ROW]
[ROW][C]20[/C][C]-0.131075[/C][C]-1.5729[/C][C]0.058968[/C][/ROW]
[ROW][C]21[/C][C]-0.014393[/C][C]-0.1727[/C][C]0.43156[/C][/ROW]
[ROW][C]22[/C][C]0.018394[/C][C]0.2207[/C][C]0.412807[/C][/ROW]
[ROW][C]23[/C][C]-0.102183[/C][C]-1.2262[/C][C]0.111063[/C][/ROW]
[ROW][C]24[/C][C]-0.013433[/C][C]-0.1612[/C][C]0.436082[/C][/ROW]
[ROW][C]25[/C][C]-0.050631[/C][C]-0.6076[/C][C]0.272213[/C][/ROW]
[ROW][C]26[/C][C]-0.069009[/C][C]-0.8281[/C][C]0.20449[/C][/ROW]
[ROW][C]27[/C][C]-0.004979[/C][C]-0.0597[/C][C]0.476219[/C][/ROW]
[ROW][C]28[/C][C]-0.073904[/C][C]-0.8868[/C][C]0.18832[/C][/ROW]
[ROW][C]29[/C][C]-0.03029[/C][C]-0.3635[/C][C]0.358388[/C][/ROW]
[ROW][C]30[/C][C]-0.045685[/C][C]-0.5482[/C][C]0.292194[/C][/ROW]
[ROW][C]31[/C][C]0.000441[/C][C]0.0053[/C][C]0.497892[/C][/ROW]
[ROW][C]32[/C][C]0.000765[/C][C]0.0092[/C][C]0.496342[/C][/ROW]
[ROW][C]33[/C][C]0.001387[/C][C]0.0166[/C][C]0.493372[/C][/ROW]
[ROW][C]34[/C][C]-0.096709[/C][C]-1.1605[/C][C]0.123881[/C][/ROW]
[ROW][C]35[/C][C]-0.060603[/C][C]-0.7272[/C][C]0.234129[/C][/ROW]
[ROW][C]36[/C][C]0.0728[/C][C]0.8736[/C][C]0.191894[/C][/ROW]
[ROW][C]37[/C][C]-0.063289[/C][C]-0.7595[/C][C]0.224408[/C][/ROW]
[ROW][C]38[/C][C]0.021685[/C][C]0.2602[/C][C]0.397533[/C][/ROW]
[ROW][C]39[/C][C]-0.083143[/C][C]-0.9977[/C][C]0.160045[/C][/ROW]
[ROW][C]40[/C][C]0.070596[/C][C]0.8472[/C][C]0.199158[/C][/ROW]
[ROW][C]41[/C][C]-0.09016[/C][C]-1.0819[/C][C]0.140549[/C][/ROW]
[ROW][C]42[/C][C]0.062398[/C][C]0.7488[/C][C]0.227607[/C][/ROW]
[ROW][C]43[/C][C]-0.014882[/C][C]-0.1786[/C][C]0.429259[/C][/ROW]
[ROW][C]44[/C][C]-0.063159[/C][C]-0.7579[/C][C]0.224871[/C][/ROW]
[ROW][C]45[/C][C]-0.029937[/C][C]-0.3592[/C][C]0.35997[/C][/ROW]
[ROW][C]46[/C][C]0.050686[/C][C]0.6082[/C][C]0.271997[/C][/ROW]
[ROW][C]47[/C][C]-0.04202[/C][C]-0.5042[/C][C]0.307432[/C][/ROW]
[ROW][C]48[/C][C]-0.089703[/C][C]-1.0764[/C][C]0.141765[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40001&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40001&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
10.3055993.66720.000172
2-0.361409-4.33691.4e-05
3-0.178932-2.14720.016727
4-0.206318-2.47580.007226
50.0922991.10760.134943
6-0.044666-0.5360.296394
7-0.088651-1.06380.144598
8-0.298018-3.57620.000238
9-0.184704-2.21640.014115
10-0.32476-3.89717.4e-05
110.2687723.22530.000779
120.7437758.92530
13-0.133928-1.60710.055107
140.1958582.35030.010058
150.0850981.02120.154442
160.0393450.47210.318769
17-0.066135-0.79360.214362
18-0.066909-0.80290.211675
190.0113260.13590.446038
20-0.131075-1.57290.058968
21-0.014393-0.17270.43156
220.0183940.22070.412807
23-0.102183-1.22620.111063
24-0.013433-0.16120.436082
25-0.050631-0.60760.272213
26-0.069009-0.82810.20449
27-0.004979-0.05970.476219
28-0.073904-0.88680.18832
29-0.03029-0.36350.358388
30-0.045685-0.54820.292194
310.0004410.00530.497892
320.0007650.00920.496342
330.0013870.01660.493372
34-0.096709-1.16050.123881
35-0.060603-0.72720.234129
360.07280.87360.191894
37-0.063289-0.75950.224408
380.0216850.26020.397533
39-0.083143-0.99770.160045
400.0705960.84720.199158
41-0.09016-1.08190.140549
420.0623980.74880.227607
43-0.014882-0.17860.429259
44-0.063159-0.75790.224871
45-0.029937-0.35920.35997
460.0506860.60820.271997
47-0.04202-0.50420.307432
48-0.089703-1.07640.141765



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