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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, 12 Dec 2009 06:36:00 -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/2009/Dec/12/t1260625033ejqxlyl9mqjvbqz.htm/, Retrieved Mon, 29 Apr 2024 13:47:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66950, Retrieved Mon, 29 Apr 2024 13:47:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelation] [2009-12-12 13:36:00] [99bf2a1e962091d45abf4c2600a412f9] [Current]
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Dataseries X:
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570




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=66950&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=66950&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66950&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
10.2201731.70550.046641
2-0.222616-1.72440.044894
3-0.262838-2.03590.023089
4-0.181764-1.40790.082155
50.0815470.63170.265004
60.2184721.69230.047891
70.080470.62330.267719
8-0.226669-1.75580.042116
9-0.263116-2.03810.022978
10-0.209417-1.62210.055009
110.287682.22840.014808
120.730145.65560
130.0957840.74190.230509
14-0.226375-1.75350.042312
15-0.233897-1.81180.037514
16-0.177837-1.37750.086735
170.0446020.34550.365469
180.1341411.0390.151475
190.0233510.18090.428536
20-0.232716-1.80260.038236
21-0.240087-1.85970.033916
22-0.163883-1.26940.104595
230.2360421.82840.036233
240.4977533.85560.000142
250.0165880.12850.449096
26-0.199679-1.54670.063596
27-0.17113-1.32560.095004
28-0.119586-0.92630.178998
290.0431650.33440.369639
300.0749360.58040.281893
310.0010850.00840.496662
32-0.191374-1.48240.071736
33-0.17799-1.37870.086553
34-0.067865-0.52570.300525
350.1695391.31320.09705
360.290062.24680.014172
37-0.004493-0.03480.486176
38-0.092735-0.71830.237673
39-0.100969-0.78210.218616
40-0.027524-0.21320.415947
410.0343950.26640.395412
420.0447930.3470.364916
430.0042850.03320.486816
44-0.093231-0.72220.236499
45-0.077837-0.60290.274416
46-0.011318-0.08770.465217
470.0987420.76490.223678
480.1369921.06110.146441
49-0.018841-0.14590.44223
50-0.039544-0.30630.380215
51-0.036402-0.2820.389468
52-4e-0600.499987
530.0032560.02520.489982
540.0047250.03660.485462
55-0.003167-0.02450.490254
56-0.043885-0.33990.367546
57-0.01259-0.09750.461319
580.0157060.12170.451789
590.0429590.33280.370239
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.220173 & 1.7055 & 0.046641 \tabularnewline
2 & -0.222616 & -1.7244 & 0.044894 \tabularnewline
3 & -0.262838 & -2.0359 & 0.023089 \tabularnewline
4 & -0.181764 & -1.4079 & 0.082155 \tabularnewline
5 & 0.081547 & 0.6317 & 0.265004 \tabularnewline
6 & 0.218472 & 1.6923 & 0.047891 \tabularnewline
7 & 0.08047 & 0.6233 & 0.267719 \tabularnewline
8 & -0.226669 & -1.7558 & 0.042116 \tabularnewline
9 & -0.263116 & -2.0381 & 0.022978 \tabularnewline
10 & -0.209417 & -1.6221 & 0.055009 \tabularnewline
11 & 0.28768 & 2.2284 & 0.014808 \tabularnewline
12 & 0.73014 & 5.6556 & 0 \tabularnewline
13 & 0.095784 & 0.7419 & 0.230509 \tabularnewline
14 & -0.226375 & -1.7535 & 0.042312 \tabularnewline
15 & -0.233897 & -1.8118 & 0.037514 \tabularnewline
16 & -0.177837 & -1.3775 & 0.086735 \tabularnewline
17 & 0.044602 & 0.3455 & 0.365469 \tabularnewline
18 & 0.134141 & 1.039 & 0.151475 \tabularnewline
19 & 0.023351 & 0.1809 & 0.428536 \tabularnewline
20 & -0.232716 & -1.8026 & 0.038236 \tabularnewline
21 & -0.240087 & -1.8597 & 0.033916 \tabularnewline
22 & -0.163883 & -1.2694 & 0.104595 \tabularnewline
23 & 0.236042 & 1.8284 & 0.036233 \tabularnewline
24 & 0.497753 & 3.8556 & 0.000142 \tabularnewline
25 & 0.016588 & 0.1285 & 0.449096 \tabularnewline
26 & -0.199679 & -1.5467 & 0.063596 \tabularnewline
27 & -0.17113 & -1.3256 & 0.095004 \tabularnewline
28 & -0.119586 & -0.9263 & 0.178998 \tabularnewline
29 & 0.043165 & 0.3344 & 0.369639 \tabularnewline
30 & 0.074936 & 0.5804 & 0.281893 \tabularnewline
31 & 0.001085 & 0.0084 & 0.496662 \tabularnewline
32 & -0.191374 & -1.4824 & 0.071736 \tabularnewline
33 & -0.17799 & -1.3787 & 0.086553 \tabularnewline
34 & -0.067865 & -0.5257 & 0.300525 \tabularnewline
35 & 0.169539 & 1.3132 & 0.09705 \tabularnewline
36 & 0.29006 & 2.2468 & 0.014172 \tabularnewline
37 & -0.004493 & -0.0348 & 0.486176 \tabularnewline
38 & -0.092735 & -0.7183 & 0.237673 \tabularnewline
39 & -0.100969 & -0.7821 & 0.218616 \tabularnewline
40 & -0.027524 & -0.2132 & 0.415947 \tabularnewline
41 & 0.034395 & 0.2664 & 0.395412 \tabularnewline
42 & 0.044793 & 0.347 & 0.364916 \tabularnewline
43 & 0.004285 & 0.0332 & 0.486816 \tabularnewline
44 & -0.093231 & -0.7222 & 0.236499 \tabularnewline
45 & -0.077837 & -0.6029 & 0.274416 \tabularnewline
46 & -0.011318 & -0.0877 & 0.465217 \tabularnewline
47 & 0.098742 & 0.7649 & 0.223678 \tabularnewline
48 & 0.136992 & 1.0611 & 0.146441 \tabularnewline
49 & -0.018841 & -0.1459 & 0.44223 \tabularnewline
50 & -0.039544 & -0.3063 & 0.380215 \tabularnewline
51 & -0.036402 & -0.282 & 0.389468 \tabularnewline
52 & -4e-06 & 0 & 0.499987 \tabularnewline
53 & 0.003256 & 0.0252 & 0.489982 \tabularnewline
54 & 0.004725 & 0.0366 & 0.485462 \tabularnewline
55 & -0.003167 & -0.0245 & 0.490254 \tabularnewline
56 & -0.043885 & -0.3399 & 0.367546 \tabularnewline
57 & -0.01259 & -0.0975 & 0.461319 \tabularnewline
58 & 0.015706 & 0.1217 & 0.451789 \tabularnewline
59 & 0.042959 & 0.3328 & 0.370239 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66950&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]0.220173[/C][C]1.7055[/C][C]0.046641[/C][/ROW]
[ROW][C]2[/C][C]-0.222616[/C][C]-1.7244[/C][C]0.044894[/C][/ROW]
[ROW][C]3[/C][C]-0.262838[/C][C]-2.0359[/C][C]0.023089[/C][/ROW]
[ROW][C]4[/C][C]-0.181764[/C][C]-1.4079[/C][C]0.082155[/C][/ROW]
[ROW][C]5[/C][C]0.081547[/C][C]0.6317[/C][C]0.265004[/C][/ROW]
[ROW][C]6[/C][C]0.218472[/C][C]1.6923[/C][C]0.047891[/C][/ROW]
[ROW][C]7[/C][C]0.08047[/C][C]0.6233[/C][C]0.267719[/C][/ROW]
[ROW][C]8[/C][C]-0.226669[/C][C]-1.7558[/C][C]0.042116[/C][/ROW]
[ROW][C]9[/C][C]-0.263116[/C][C]-2.0381[/C][C]0.022978[/C][/ROW]
[ROW][C]10[/C][C]-0.209417[/C][C]-1.6221[/C][C]0.055009[/C][/ROW]
[ROW][C]11[/C][C]0.28768[/C][C]2.2284[/C][C]0.014808[/C][/ROW]
[ROW][C]12[/C][C]0.73014[/C][C]5.6556[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.095784[/C][C]0.7419[/C][C]0.230509[/C][/ROW]
[ROW][C]14[/C][C]-0.226375[/C][C]-1.7535[/C][C]0.042312[/C][/ROW]
[ROW][C]15[/C][C]-0.233897[/C][C]-1.8118[/C][C]0.037514[/C][/ROW]
[ROW][C]16[/C][C]-0.177837[/C][C]-1.3775[/C][C]0.086735[/C][/ROW]
[ROW][C]17[/C][C]0.044602[/C][C]0.3455[/C][C]0.365469[/C][/ROW]
[ROW][C]18[/C][C]0.134141[/C][C]1.039[/C][C]0.151475[/C][/ROW]
[ROW][C]19[/C][C]0.023351[/C][C]0.1809[/C][C]0.428536[/C][/ROW]
[ROW][C]20[/C][C]-0.232716[/C][C]-1.8026[/C][C]0.038236[/C][/ROW]
[ROW][C]21[/C][C]-0.240087[/C][C]-1.8597[/C][C]0.033916[/C][/ROW]
[ROW][C]22[/C][C]-0.163883[/C][C]-1.2694[/C][C]0.104595[/C][/ROW]
[ROW][C]23[/C][C]0.236042[/C][C]1.8284[/C][C]0.036233[/C][/ROW]
[ROW][C]24[/C][C]0.497753[/C][C]3.8556[/C][C]0.000142[/C][/ROW]
[ROW][C]25[/C][C]0.016588[/C][C]0.1285[/C][C]0.449096[/C][/ROW]
[ROW][C]26[/C][C]-0.199679[/C][C]-1.5467[/C][C]0.063596[/C][/ROW]
[ROW][C]27[/C][C]-0.17113[/C][C]-1.3256[/C][C]0.095004[/C][/ROW]
[ROW][C]28[/C][C]-0.119586[/C][C]-0.9263[/C][C]0.178998[/C][/ROW]
[ROW][C]29[/C][C]0.043165[/C][C]0.3344[/C][C]0.369639[/C][/ROW]
[ROW][C]30[/C][C]0.074936[/C][C]0.5804[/C][C]0.281893[/C][/ROW]
[ROW][C]31[/C][C]0.001085[/C][C]0.0084[/C][C]0.496662[/C][/ROW]
[ROW][C]32[/C][C]-0.191374[/C][C]-1.4824[/C][C]0.071736[/C][/ROW]
[ROW][C]33[/C][C]-0.17799[/C][C]-1.3787[/C][C]0.086553[/C][/ROW]
[ROW][C]34[/C][C]-0.067865[/C][C]-0.5257[/C][C]0.300525[/C][/ROW]
[ROW][C]35[/C][C]0.169539[/C][C]1.3132[/C][C]0.09705[/C][/ROW]
[ROW][C]36[/C][C]0.29006[/C][C]2.2468[/C][C]0.014172[/C][/ROW]
[ROW][C]37[/C][C]-0.004493[/C][C]-0.0348[/C][C]0.486176[/C][/ROW]
[ROW][C]38[/C][C]-0.092735[/C][C]-0.7183[/C][C]0.237673[/C][/ROW]
[ROW][C]39[/C][C]-0.100969[/C][C]-0.7821[/C][C]0.218616[/C][/ROW]
[ROW][C]40[/C][C]-0.027524[/C][C]-0.2132[/C][C]0.415947[/C][/ROW]
[ROW][C]41[/C][C]0.034395[/C][C]0.2664[/C][C]0.395412[/C][/ROW]
[ROW][C]42[/C][C]0.044793[/C][C]0.347[/C][C]0.364916[/C][/ROW]
[ROW][C]43[/C][C]0.004285[/C][C]0.0332[/C][C]0.486816[/C][/ROW]
[ROW][C]44[/C][C]-0.093231[/C][C]-0.7222[/C][C]0.236499[/C][/ROW]
[ROW][C]45[/C][C]-0.077837[/C][C]-0.6029[/C][C]0.274416[/C][/ROW]
[ROW][C]46[/C][C]-0.011318[/C][C]-0.0877[/C][C]0.465217[/C][/ROW]
[ROW][C]47[/C][C]0.098742[/C][C]0.7649[/C][C]0.223678[/C][/ROW]
[ROW][C]48[/C][C]0.136992[/C][C]1.0611[/C][C]0.146441[/C][/ROW]
[ROW][C]49[/C][C]-0.018841[/C][C]-0.1459[/C][C]0.44223[/C][/ROW]
[ROW][C]50[/C][C]-0.039544[/C][C]-0.3063[/C][C]0.380215[/C][/ROW]
[ROW][C]51[/C][C]-0.036402[/C][C]-0.282[/C][C]0.389468[/C][/ROW]
[ROW][C]52[/C][C]-4e-06[/C][C]0[/C][C]0.499987[/C][/ROW]
[ROW][C]53[/C][C]0.003256[/C][C]0.0252[/C][C]0.489982[/C][/ROW]
[ROW][C]54[/C][C]0.004725[/C][C]0.0366[/C][C]0.485462[/C][/ROW]
[ROW][C]55[/C][C]-0.003167[/C][C]-0.0245[/C][C]0.490254[/C][/ROW]
[ROW][C]56[/C][C]-0.043885[/C][C]-0.3399[/C][C]0.367546[/C][/ROW]
[ROW][C]57[/C][C]-0.01259[/C][C]-0.0975[/C][C]0.461319[/C][/ROW]
[ROW][C]58[/C][C]0.015706[/C][C]0.1217[/C][C]0.451789[/C][/ROW]
[ROW][C]59[/C][C]0.042959[/C][C]0.3328[/C][C]0.370239[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66950&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66950&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
10.2201731.70550.046641
2-0.222616-1.72440.044894
3-0.262838-2.03590.023089
4-0.181764-1.40790.082155
50.0815470.63170.265004
60.2184721.69230.047891
70.080470.62330.267719
8-0.226669-1.75580.042116
9-0.263116-2.03810.022978
10-0.209417-1.62210.055009
110.287682.22840.014808
120.730145.65560
130.0957840.74190.230509
14-0.226375-1.75350.042312
15-0.233897-1.81180.037514
16-0.177837-1.37750.086735
170.0446020.34550.365469
180.1341411.0390.151475
190.0233510.18090.428536
20-0.232716-1.80260.038236
21-0.240087-1.85970.033916
22-0.163883-1.26940.104595
230.2360421.82840.036233
240.4977533.85560.000142
250.0165880.12850.449096
26-0.199679-1.54670.063596
27-0.17113-1.32560.095004
28-0.119586-0.92630.178998
290.0431650.33440.369639
300.0749360.58040.281893
310.0010850.00840.496662
32-0.191374-1.48240.071736
33-0.17799-1.37870.086553
34-0.067865-0.52570.300525
350.1695391.31320.09705
360.290062.24680.014172
37-0.004493-0.03480.486176
38-0.092735-0.71830.237673
39-0.100969-0.78210.218616
40-0.027524-0.21320.415947
410.0343950.26640.395412
420.0447930.3470.364916
430.0042850.03320.486816
44-0.093231-0.72220.236499
45-0.077837-0.60290.274416
46-0.011318-0.08770.465217
470.0987420.76490.223678
480.1369921.06110.146441
49-0.018841-0.14590.44223
50-0.039544-0.30630.380215
51-0.036402-0.2820.389468
52-4e-0600.499987
530.0032560.02520.489982
540.0047250.03660.485462
55-0.003167-0.02450.490254
56-0.043885-0.33990.367546
57-0.01259-0.09750.461319
580.0157060.12170.451789
590.0429590.33280.370239
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2201731.70550.046641
2-0.284904-2.20690.015581
3-0.15685-1.2150.114572
4-0.162016-1.2550.107177
50.0675690.52340.301315
60.0854240.66170.255352
7-0.013463-0.10430.458647
8-0.21263-1.6470.052391
9-0.119785-0.92790.178601
10-0.226946-1.75790.041931
110.2927472.26760.013484
120.6056024.6918e-06
13-0.146714-1.13640.130145
140.0063690.04930.480407
150.0235760.18260.427857
16-0.113897-0.88220.190583
17-0.088853-0.68830.246972
18-0.20925-1.62080.055148
19-0.049231-0.38130.352149
20-0.021852-0.16930.433078
21-0.011949-0.09260.463282
22-0.031729-0.24580.403349
23-0.162685-1.26020.106246
24-0.046898-0.36330.358841
25-0.030329-0.23490.407531
26-0.079172-0.61330.27101
270.0399870.30970.378917
280.0257720.19960.421223
290.0536130.41530.339708
30-0.041093-0.31830.37568
31-0.006143-0.04760.481104
32-0.007151-0.05540.478005
33-0.024299-0.18820.42567
340.0645110.49970.309557
35-0.127028-0.9840.164544
36-0.148193-1.14790.127783
370.0562420.43560.332327
380.052080.40340.344042
39-0.066966-0.51870.302933
400.0477770.37010.356315
41-0.039771-0.30810.379549
420.0502550.38930.349227
43-0.008133-0.0630.474987
440.0690660.5350.29732
450.0209540.16230.435805
46-0.008475-0.06560.47394
470.0391190.3030.381462
48-0.06034-0.46740.320956
49-0.112085-0.86820.194371
50-0.029321-0.22710.41055
51-0.058939-0.45650.324826
52-0.084602-0.65530.257383
53-0.056502-0.43770.331601
54-0.007023-0.05440.478399
55-0.047234-0.36590.357874
56-0.053147-0.41170.341022
570.0108930.08440.466518
58-0.002678-0.02070.491759
590.0476410.3690.356703
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.220173 & 1.7055 & 0.046641 \tabularnewline
2 & -0.284904 & -2.2069 & 0.015581 \tabularnewline
3 & -0.15685 & -1.215 & 0.114572 \tabularnewline
4 & -0.162016 & -1.255 & 0.107177 \tabularnewline
5 & 0.067569 & 0.5234 & 0.301315 \tabularnewline
6 & 0.085424 & 0.6617 & 0.255352 \tabularnewline
7 & -0.013463 & -0.1043 & 0.458647 \tabularnewline
8 & -0.21263 & -1.647 & 0.052391 \tabularnewline
9 & -0.119785 & -0.9279 & 0.178601 \tabularnewline
10 & -0.226946 & -1.7579 & 0.041931 \tabularnewline
11 & 0.292747 & 2.2676 & 0.013484 \tabularnewline
12 & 0.605602 & 4.691 & 8e-06 \tabularnewline
13 & -0.146714 & -1.1364 & 0.130145 \tabularnewline
14 & 0.006369 & 0.0493 & 0.480407 \tabularnewline
15 & 0.023576 & 0.1826 & 0.427857 \tabularnewline
16 & -0.113897 & -0.8822 & 0.190583 \tabularnewline
17 & -0.088853 & -0.6883 & 0.246972 \tabularnewline
18 & -0.20925 & -1.6208 & 0.055148 \tabularnewline
19 & -0.049231 & -0.3813 & 0.352149 \tabularnewline
20 & -0.021852 & -0.1693 & 0.433078 \tabularnewline
21 & -0.011949 & -0.0926 & 0.463282 \tabularnewline
22 & -0.031729 & -0.2458 & 0.403349 \tabularnewline
23 & -0.162685 & -1.2602 & 0.106246 \tabularnewline
24 & -0.046898 & -0.3633 & 0.358841 \tabularnewline
25 & -0.030329 & -0.2349 & 0.407531 \tabularnewline
26 & -0.079172 & -0.6133 & 0.27101 \tabularnewline
27 & 0.039987 & 0.3097 & 0.378917 \tabularnewline
28 & 0.025772 & 0.1996 & 0.421223 \tabularnewline
29 & 0.053613 & 0.4153 & 0.339708 \tabularnewline
30 & -0.041093 & -0.3183 & 0.37568 \tabularnewline
31 & -0.006143 & -0.0476 & 0.481104 \tabularnewline
32 & -0.007151 & -0.0554 & 0.478005 \tabularnewline
33 & -0.024299 & -0.1882 & 0.42567 \tabularnewline
34 & 0.064511 & 0.4997 & 0.309557 \tabularnewline
35 & -0.127028 & -0.984 & 0.164544 \tabularnewline
36 & -0.148193 & -1.1479 & 0.127783 \tabularnewline
37 & 0.056242 & 0.4356 & 0.332327 \tabularnewline
38 & 0.05208 & 0.4034 & 0.344042 \tabularnewline
39 & -0.066966 & -0.5187 & 0.302933 \tabularnewline
40 & 0.047777 & 0.3701 & 0.356315 \tabularnewline
41 & -0.039771 & -0.3081 & 0.379549 \tabularnewline
42 & 0.050255 & 0.3893 & 0.349227 \tabularnewline
43 & -0.008133 & -0.063 & 0.474987 \tabularnewline
44 & 0.069066 & 0.535 & 0.29732 \tabularnewline
45 & 0.020954 & 0.1623 & 0.435805 \tabularnewline
46 & -0.008475 & -0.0656 & 0.47394 \tabularnewline
47 & 0.039119 & 0.303 & 0.381462 \tabularnewline
48 & -0.06034 & -0.4674 & 0.320956 \tabularnewline
49 & -0.112085 & -0.8682 & 0.194371 \tabularnewline
50 & -0.029321 & -0.2271 & 0.41055 \tabularnewline
51 & -0.058939 & -0.4565 & 0.324826 \tabularnewline
52 & -0.084602 & -0.6553 & 0.257383 \tabularnewline
53 & -0.056502 & -0.4377 & 0.331601 \tabularnewline
54 & -0.007023 & -0.0544 & 0.478399 \tabularnewline
55 & -0.047234 & -0.3659 & 0.357874 \tabularnewline
56 & -0.053147 & -0.4117 & 0.341022 \tabularnewline
57 & 0.010893 & 0.0844 & 0.466518 \tabularnewline
58 & -0.002678 & -0.0207 & 0.491759 \tabularnewline
59 & 0.047641 & 0.369 & 0.356703 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66950&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]0.220173[/C][C]1.7055[/C][C]0.046641[/C][/ROW]
[ROW][C]2[/C][C]-0.284904[/C][C]-2.2069[/C][C]0.015581[/C][/ROW]
[ROW][C]3[/C][C]-0.15685[/C][C]-1.215[/C][C]0.114572[/C][/ROW]
[ROW][C]4[/C][C]-0.162016[/C][C]-1.255[/C][C]0.107177[/C][/ROW]
[ROW][C]5[/C][C]0.067569[/C][C]0.5234[/C][C]0.301315[/C][/ROW]
[ROW][C]6[/C][C]0.085424[/C][C]0.6617[/C][C]0.255352[/C][/ROW]
[ROW][C]7[/C][C]-0.013463[/C][C]-0.1043[/C][C]0.458647[/C][/ROW]
[ROW][C]8[/C][C]-0.21263[/C][C]-1.647[/C][C]0.052391[/C][/ROW]
[ROW][C]9[/C][C]-0.119785[/C][C]-0.9279[/C][C]0.178601[/C][/ROW]
[ROW][C]10[/C][C]-0.226946[/C][C]-1.7579[/C][C]0.041931[/C][/ROW]
[ROW][C]11[/C][C]0.292747[/C][C]2.2676[/C][C]0.013484[/C][/ROW]
[ROW][C]12[/C][C]0.605602[/C][C]4.691[/C][C]8e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.146714[/C][C]-1.1364[/C][C]0.130145[/C][/ROW]
[ROW][C]14[/C][C]0.006369[/C][C]0.0493[/C][C]0.480407[/C][/ROW]
[ROW][C]15[/C][C]0.023576[/C][C]0.1826[/C][C]0.427857[/C][/ROW]
[ROW][C]16[/C][C]-0.113897[/C][C]-0.8822[/C][C]0.190583[/C][/ROW]
[ROW][C]17[/C][C]-0.088853[/C][C]-0.6883[/C][C]0.246972[/C][/ROW]
[ROW][C]18[/C][C]-0.20925[/C][C]-1.6208[/C][C]0.055148[/C][/ROW]
[ROW][C]19[/C][C]-0.049231[/C][C]-0.3813[/C][C]0.352149[/C][/ROW]
[ROW][C]20[/C][C]-0.021852[/C][C]-0.1693[/C][C]0.433078[/C][/ROW]
[ROW][C]21[/C][C]-0.011949[/C][C]-0.0926[/C][C]0.463282[/C][/ROW]
[ROW][C]22[/C][C]-0.031729[/C][C]-0.2458[/C][C]0.403349[/C][/ROW]
[ROW][C]23[/C][C]-0.162685[/C][C]-1.2602[/C][C]0.106246[/C][/ROW]
[ROW][C]24[/C][C]-0.046898[/C][C]-0.3633[/C][C]0.358841[/C][/ROW]
[ROW][C]25[/C][C]-0.030329[/C][C]-0.2349[/C][C]0.407531[/C][/ROW]
[ROW][C]26[/C][C]-0.079172[/C][C]-0.6133[/C][C]0.27101[/C][/ROW]
[ROW][C]27[/C][C]0.039987[/C][C]0.3097[/C][C]0.378917[/C][/ROW]
[ROW][C]28[/C][C]0.025772[/C][C]0.1996[/C][C]0.421223[/C][/ROW]
[ROW][C]29[/C][C]0.053613[/C][C]0.4153[/C][C]0.339708[/C][/ROW]
[ROW][C]30[/C][C]-0.041093[/C][C]-0.3183[/C][C]0.37568[/C][/ROW]
[ROW][C]31[/C][C]-0.006143[/C][C]-0.0476[/C][C]0.481104[/C][/ROW]
[ROW][C]32[/C][C]-0.007151[/C][C]-0.0554[/C][C]0.478005[/C][/ROW]
[ROW][C]33[/C][C]-0.024299[/C][C]-0.1882[/C][C]0.42567[/C][/ROW]
[ROW][C]34[/C][C]0.064511[/C][C]0.4997[/C][C]0.309557[/C][/ROW]
[ROW][C]35[/C][C]-0.127028[/C][C]-0.984[/C][C]0.164544[/C][/ROW]
[ROW][C]36[/C][C]-0.148193[/C][C]-1.1479[/C][C]0.127783[/C][/ROW]
[ROW][C]37[/C][C]0.056242[/C][C]0.4356[/C][C]0.332327[/C][/ROW]
[ROW][C]38[/C][C]0.05208[/C][C]0.4034[/C][C]0.344042[/C][/ROW]
[ROW][C]39[/C][C]-0.066966[/C][C]-0.5187[/C][C]0.302933[/C][/ROW]
[ROW][C]40[/C][C]0.047777[/C][C]0.3701[/C][C]0.356315[/C][/ROW]
[ROW][C]41[/C][C]-0.039771[/C][C]-0.3081[/C][C]0.379549[/C][/ROW]
[ROW][C]42[/C][C]0.050255[/C][C]0.3893[/C][C]0.349227[/C][/ROW]
[ROW][C]43[/C][C]-0.008133[/C][C]-0.063[/C][C]0.474987[/C][/ROW]
[ROW][C]44[/C][C]0.069066[/C][C]0.535[/C][C]0.29732[/C][/ROW]
[ROW][C]45[/C][C]0.020954[/C][C]0.1623[/C][C]0.435805[/C][/ROW]
[ROW][C]46[/C][C]-0.008475[/C][C]-0.0656[/C][C]0.47394[/C][/ROW]
[ROW][C]47[/C][C]0.039119[/C][C]0.303[/C][C]0.381462[/C][/ROW]
[ROW][C]48[/C][C]-0.06034[/C][C]-0.4674[/C][C]0.320956[/C][/ROW]
[ROW][C]49[/C][C]-0.112085[/C][C]-0.8682[/C][C]0.194371[/C][/ROW]
[ROW][C]50[/C][C]-0.029321[/C][C]-0.2271[/C][C]0.41055[/C][/ROW]
[ROW][C]51[/C][C]-0.058939[/C][C]-0.4565[/C][C]0.324826[/C][/ROW]
[ROW][C]52[/C][C]-0.084602[/C][C]-0.6553[/C][C]0.257383[/C][/ROW]
[ROW][C]53[/C][C]-0.056502[/C][C]-0.4377[/C][C]0.331601[/C][/ROW]
[ROW][C]54[/C][C]-0.007023[/C][C]-0.0544[/C][C]0.478399[/C][/ROW]
[ROW][C]55[/C][C]-0.047234[/C][C]-0.3659[/C][C]0.357874[/C][/ROW]
[ROW][C]56[/C][C]-0.053147[/C][C]-0.4117[/C][C]0.341022[/C][/ROW]
[ROW][C]57[/C][C]0.010893[/C][C]0.0844[/C][C]0.466518[/C][/ROW]
[ROW][C]58[/C][C]-0.002678[/C][C]-0.0207[/C][C]0.491759[/C][/ROW]
[ROW][C]59[/C][C]0.047641[/C][C]0.369[/C][C]0.356703[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66950&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66950&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
10.2201731.70550.046641
2-0.284904-2.20690.015581
3-0.15685-1.2150.114572
4-0.162016-1.2550.107177
50.0675690.52340.301315
60.0854240.66170.255352
7-0.013463-0.10430.458647
8-0.21263-1.6470.052391
9-0.119785-0.92790.178601
10-0.226946-1.75790.041931
110.2927472.26760.013484
120.6056024.6918e-06
13-0.146714-1.13640.130145
140.0063690.04930.480407
150.0235760.18260.427857
16-0.113897-0.88220.190583
17-0.088853-0.68830.246972
18-0.20925-1.62080.055148
19-0.049231-0.38130.352149
20-0.021852-0.16930.433078
21-0.011949-0.09260.463282
22-0.031729-0.24580.403349
23-0.162685-1.26020.106246
24-0.046898-0.36330.358841
25-0.030329-0.23490.407531
26-0.079172-0.61330.27101
270.0399870.30970.378917
280.0257720.19960.421223
290.0536130.41530.339708
30-0.041093-0.31830.37568
31-0.006143-0.04760.481104
32-0.007151-0.05540.478005
33-0.024299-0.18820.42567
340.0645110.49970.309557
35-0.127028-0.9840.164544
36-0.148193-1.14790.127783
370.0562420.43560.332327
380.052080.40340.344042
39-0.066966-0.51870.302933
400.0477770.37010.356315
41-0.039771-0.30810.379549
420.0502550.38930.349227
43-0.008133-0.0630.474987
440.0690660.5350.29732
450.0209540.16230.435805
46-0.008475-0.06560.47394
470.0391190.3030.381462
48-0.06034-0.46740.320956
49-0.112085-0.86820.194371
50-0.029321-0.22710.41055
51-0.058939-0.45650.324826
52-0.084602-0.65530.257383
53-0.056502-0.43770.331601
54-0.007023-0.05440.478399
55-0.047234-0.36590.357874
56-0.053147-0.41170.341022
570.0108930.08440.466518
58-0.002678-0.02070.491759
590.0476410.3690.356703
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')