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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 14 Nov 2010 22:36:11 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/14/t1289774114j7iwz1n6pa2ouq6.htm/, Retrieved Fri, 29 Mar 2024 12:52:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=94671, Retrieved Fri, 29 Mar 2024 12:52:43 +0000
QR Codes:

Original text written by user:De juiste versie van mijn cijferreeks.
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W11
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Opgave 6 Stap 1] [2010-11-14 22:36:11] [cf38f7df7be58a8c28b053c2e6c1601e] [Current]
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Dataseries X:
361.58
363.19
363.61
364.14
365.51
365.51
365.5
365.5
364.59
364.63
364.54
363.67
365.22
369.05
370.45
370.46
370.46
370.58
370.58
370.22
370.21
370.29
370.29
370.2
370.2
372.55
374.51
375.58
375.75
375.75
375.75
375.69
375.76
377.5
377.51
377.74
369.82
373.1
374.55
375.01
374.81
375.31
375.31
375.39
375.59
376.26
377.18
377.26
377.26
381.87
387.09
387.14
388.78
389.16
389.16
389.42
389.49
388.97
388.97
389.09
389.09
391.76
390.96
391.76
392.8
393.06
393.06
393.26
393.87
394.47
394.57
394.57
394.57
399.57
406.13
407.03
409.46
409.9
409.9
410.14
410.54
410.69
410.79
410.97




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94671&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94671&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9547888.75080
20.9080688.32260
30.8604617.88630
40.812627.44780
50.7656997.01770
60.7184716.58490
70.6703466.14380
80.6225235.70550
90.5768945.28730
100.5321114.87693e-06
110.4987914.57158e-06
120.4716174.32242.1e-05
130.4418394.04955.7e-05
140.4152613.80590.000134
150.3917483.59040.000277
160.3679183.3720.000565
170.3451493.16330.001086
180.3223522.95440.002032
190.2991532.74180.003733
200.2752942.52310.006758
210.2522382.31180.011618
220.2291792.10050.019343
230.2039461.86920.03254
240.1817611.66590.049733
250.1537181.40880.081286
260.1258251.15320.126049
270.0981740.89980.185406
280.0697430.63920.262215
290.0404430.37070.355911
300.0111920.10260.45927
31-0.018615-0.17060.432469
32-0.048359-0.44320.329375
33-0.075046-0.68780.246734
34-0.099858-0.91520.181349
35-0.115986-1.0630.145408
36-0.124582-1.14180.128388
37-0.146482-1.34250.09152
38-0.165217-1.51420.066859
39-0.178634-1.63720.052664
40-0.190814-1.74880.041986
41-0.202708-1.85780.033347
42-0.214277-1.96390.026426
43-0.225994-2.07130.020701
44-0.237201-2.1740.01626
45-0.248398-2.27660.012677
46-0.258386-2.36810.010087
47-0.265771-2.43580.008486
48-0.26882-2.46380.007894

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.954788 & 8.7508 & 0 \tabularnewline
2 & 0.908068 & 8.3226 & 0 \tabularnewline
3 & 0.860461 & 7.8863 & 0 \tabularnewline
4 & 0.81262 & 7.4478 & 0 \tabularnewline
5 & 0.765699 & 7.0177 & 0 \tabularnewline
6 & 0.718471 & 6.5849 & 0 \tabularnewline
7 & 0.670346 & 6.1438 & 0 \tabularnewline
8 & 0.622523 & 5.7055 & 0 \tabularnewline
9 & 0.576894 & 5.2873 & 0 \tabularnewline
10 & 0.532111 & 4.8769 & 3e-06 \tabularnewline
11 & 0.498791 & 4.5715 & 8e-06 \tabularnewline
12 & 0.471617 & 4.3224 & 2.1e-05 \tabularnewline
13 & 0.441839 & 4.0495 & 5.7e-05 \tabularnewline
14 & 0.415261 & 3.8059 & 0.000134 \tabularnewline
15 & 0.391748 & 3.5904 & 0.000277 \tabularnewline
16 & 0.367918 & 3.372 & 0.000565 \tabularnewline
17 & 0.345149 & 3.1633 & 0.001086 \tabularnewline
18 & 0.322352 & 2.9544 & 0.002032 \tabularnewline
19 & 0.299153 & 2.7418 & 0.003733 \tabularnewline
20 & 0.275294 & 2.5231 & 0.006758 \tabularnewline
21 & 0.252238 & 2.3118 & 0.011618 \tabularnewline
22 & 0.229179 & 2.1005 & 0.019343 \tabularnewline
23 & 0.203946 & 1.8692 & 0.03254 \tabularnewline
24 & 0.181761 & 1.6659 & 0.049733 \tabularnewline
25 & 0.153718 & 1.4088 & 0.081286 \tabularnewline
26 & 0.125825 & 1.1532 & 0.126049 \tabularnewline
27 & 0.098174 & 0.8998 & 0.185406 \tabularnewline
28 & 0.069743 & 0.6392 & 0.262215 \tabularnewline
29 & 0.040443 & 0.3707 & 0.355911 \tabularnewline
30 & 0.011192 & 0.1026 & 0.45927 \tabularnewline
31 & -0.018615 & -0.1706 & 0.432469 \tabularnewline
32 & -0.048359 & -0.4432 & 0.329375 \tabularnewline
33 & -0.075046 & -0.6878 & 0.246734 \tabularnewline
34 & -0.099858 & -0.9152 & 0.181349 \tabularnewline
35 & -0.115986 & -1.063 & 0.145408 \tabularnewline
36 & -0.124582 & -1.1418 & 0.128388 \tabularnewline
37 & -0.146482 & -1.3425 & 0.09152 \tabularnewline
38 & -0.165217 & -1.5142 & 0.066859 \tabularnewline
39 & -0.178634 & -1.6372 & 0.052664 \tabularnewline
40 & -0.190814 & -1.7488 & 0.041986 \tabularnewline
41 & -0.202708 & -1.8578 & 0.033347 \tabularnewline
42 & -0.214277 & -1.9639 & 0.026426 \tabularnewline
43 & -0.225994 & -2.0713 & 0.020701 \tabularnewline
44 & -0.237201 & -2.174 & 0.01626 \tabularnewline
45 & -0.248398 & -2.2766 & 0.012677 \tabularnewline
46 & -0.258386 & -2.3681 & 0.010087 \tabularnewline
47 & -0.265771 & -2.4358 & 0.008486 \tabularnewline
48 & -0.26882 & -2.4638 & 0.007894 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94671&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]0.954788[/C][C]8.7508[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.908068[/C][C]8.3226[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.860461[/C][C]7.8863[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.81262[/C][C]7.4478[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.765699[/C][C]7.0177[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.718471[/C][C]6.5849[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.670346[/C][C]6.1438[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.622523[/C][C]5.7055[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.576894[/C][C]5.2873[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.532111[/C][C]4.8769[/C][C]3e-06[/C][/ROW]
[ROW][C]11[/C][C]0.498791[/C][C]4.5715[/C][C]8e-06[/C][/ROW]
[ROW][C]12[/C][C]0.471617[/C][C]4.3224[/C][C]2.1e-05[/C][/ROW]
[ROW][C]13[/C][C]0.441839[/C][C]4.0495[/C][C]5.7e-05[/C][/ROW]
[ROW][C]14[/C][C]0.415261[/C][C]3.8059[/C][C]0.000134[/C][/ROW]
[ROW][C]15[/C][C]0.391748[/C][C]3.5904[/C][C]0.000277[/C][/ROW]
[ROW][C]16[/C][C]0.367918[/C][C]3.372[/C][C]0.000565[/C][/ROW]
[ROW][C]17[/C][C]0.345149[/C][C]3.1633[/C][C]0.001086[/C][/ROW]
[ROW][C]18[/C][C]0.322352[/C][C]2.9544[/C][C]0.002032[/C][/ROW]
[ROW][C]19[/C][C]0.299153[/C][C]2.7418[/C][C]0.003733[/C][/ROW]
[ROW][C]20[/C][C]0.275294[/C][C]2.5231[/C][C]0.006758[/C][/ROW]
[ROW][C]21[/C][C]0.252238[/C][C]2.3118[/C][C]0.011618[/C][/ROW]
[ROW][C]22[/C][C]0.229179[/C][C]2.1005[/C][C]0.019343[/C][/ROW]
[ROW][C]23[/C][C]0.203946[/C][C]1.8692[/C][C]0.03254[/C][/ROW]
[ROW][C]24[/C][C]0.181761[/C][C]1.6659[/C][C]0.049733[/C][/ROW]
[ROW][C]25[/C][C]0.153718[/C][C]1.4088[/C][C]0.081286[/C][/ROW]
[ROW][C]26[/C][C]0.125825[/C][C]1.1532[/C][C]0.126049[/C][/ROW]
[ROW][C]27[/C][C]0.098174[/C][C]0.8998[/C][C]0.185406[/C][/ROW]
[ROW][C]28[/C][C]0.069743[/C][C]0.6392[/C][C]0.262215[/C][/ROW]
[ROW][C]29[/C][C]0.040443[/C][C]0.3707[/C][C]0.355911[/C][/ROW]
[ROW][C]30[/C][C]0.011192[/C][C]0.1026[/C][C]0.45927[/C][/ROW]
[ROW][C]31[/C][C]-0.018615[/C][C]-0.1706[/C][C]0.432469[/C][/ROW]
[ROW][C]32[/C][C]-0.048359[/C][C]-0.4432[/C][C]0.329375[/C][/ROW]
[ROW][C]33[/C][C]-0.075046[/C][C]-0.6878[/C][C]0.246734[/C][/ROW]
[ROW][C]34[/C][C]-0.099858[/C][C]-0.9152[/C][C]0.181349[/C][/ROW]
[ROW][C]35[/C][C]-0.115986[/C][C]-1.063[/C][C]0.145408[/C][/ROW]
[ROW][C]36[/C][C]-0.124582[/C][C]-1.1418[/C][C]0.128388[/C][/ROW]
[ROW][C]37[/C][C]-0.146482[/C][C]-1.3425[/C][C]0.09152[/C][/ROW]
[ROW][C]38[/C][C]-0.165217[/C][C]-1.5142[/C][C]0.066859[/C][/ROW]
[ROW][C]39[/C][C]-0.178634[/C][C]-1.6372[/C][C]0.052664[/C][/ROW]
[ROW][C]40[/C][C]-0.190814[/C][C]-1.7488[/C][C]0.041986[/C][/ROW]
[ROW][C]41[/C][C]-0.202708[/C][C]-1.8578[/C][C]0.033347[/C][/ROW]
[ROW][C]42[/C][C]-0.214277[/C][C]-1.9639[/C][C]0.026426[/C][/ROW]
[ROW][C]43[/C][C]-0.225994[/C][C]-2.0713[/C][C]0.020701[/C][/ROW]
[ROW][C]44[/C][C]-0.237201[/C][C]-2.174[/C][C]0.01626[/C][/ROW]
[ROW][C]45[/C][C]-0.248398[/C][C]-2.2766[/C][C]0.012677[/C][/ROW]
[ROW][C]46[/C][C]-0.258386[/C][C]-2.3681[/C][C]0.010087[/C][/ROW]
[ROW][C]47[/C][C]-0.265771[/C][C]-2.4358[/C][C]0.008486[/C][/ROW]
[ROW][C]48[/C][C]-0.26882[/C][C]-2.4638[/C][C]0.007894[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94671&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
10.9547888.75080
20.9080688.32260
30.8604617.88630
40.812627.44780
50.7656997.01770
60.7184716.58490
70.6703466.14380
80.6225235.70550
90.5768945.28730
100.5321114.87693e-06
110.4987914.57158e-06
120.4716174.32242.1e-05
130.4418394.04955.7e-05
140.4152613.80590.000134
150.3917483.59040.000277
160.3679183.3720.000565
170.3451493.16330.001086
180.3223522.95440.002032
190.2991532.74180.003733
200.2752942.52310.006758
210.2522382.31180.011618
220.2291792.10050.019343
230.2039461.86920.03254
240.1817611.66590.049733
250.1537181.40880.081286
260.1258251.15320.126049
270.0981740.89980.185406
280.0697430.63920.262215
290.0404430.37070.355911
300.0111920.10260.45927
31-0.018615-0.17060.432469
32-0.048359-0.44320.329375
33-0.075046-0.68780.246734
34-0.099858-0.91520.181349
35-0.115986-1.0630.145408
36-0.124582-1.14180.128388
37-0.146482-1.34250.09152
38-0.165217-1.51420.066859
39-0.178634-1.63720.052664
40-0.190814-1.74880.041986
41-0.202708-1.85780.033347
42-0.214277-1.96390.026426
43-0.225994-2.07130.020701
44-0.237201-2.1740.01626
45-0.248398-2.27660.012677
46-0.258386-2.36810.010087
47-0.265771-2.43580.008486
48-0.26882-2.46380.007894







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9547888.75080
2-0.040203-0.36850.356725
3-0.034253-0.31390.377174
4-0.027953-0.25620.399214
5-0.015763-0.14450.442738
6-0.030344-0.27810.390805
7-0.037772-0.34620.365034
8-0.025033-0.22940.409545
9-0.004287-0.03930.484376
10-0.02017-0.18490.426892
110.1003980.92020.18006
120.0432410.39630.346441
13-0.05407-0.49560.31075
140.0131760.12080.452086
150.0155280.14230.443584
16-0.025182-0.23080.409017
17-0.012378-0.11340.454974
18-0.02043-0.18720.425962
19-0.018693-0.17130.432189
20-0.025506-0.23380.407868
210.0029340.02690.489306
22-0.003283-0.03010.488032
23-0.04898-0.44890.327325
240.0178160.16330.435344
25-0.074171-0.67980.249253
26-0.021125-0.19360.423474
27-0.021107-0.19340.423537
28-0.03069-0.28130.389595
29-0.037437-0.34310.366186
30-0.027943-0.25610.39925
31-0.03055-0.280.390086
32-0.023789-0.2180.413969
33-0.003948-0.03620.485609
34-0.002337-0.02140.49148
350.064920.5950.276721
360.05060.46380.322011
37-0.174683-1.6010.056566
380.0083440.07650.469612
390.032230.29540.384212
40-0.015196-0.13930.444784
41-0.030926-0.28340.388768
42-0.019886-0.18230.427909
43-0.013446-0.12320.451109
44-0.007373-0.06760.473141
45-0.007516-0.06890.472623
460.0186960.17140.432179
47-0.018555-0.17010.432686
480.0157590.14440.442753

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.954788 & 8.7508 & 0 \tabularnewline
2 & -0.040203 & -0.3685 & 0.356725 \tabularnewline
3 & -0.034253 & -0.3139 & 0.377174 \tabularnewline
4 & -0.027953 & -0.2562 & 0.399214 \tabularnewline
5 & -0.015763 & -0.1445 & 0.442738 \tabularnewline
6 & -0.030344 & -0.2781 & 0.390805 \tabularnewline
7 & -0.037772 & -0.3462 & 0.365034 \tabularnewline
8 & -0.025033 & -0.2294 & 0.409545 \tabularnewline
9 & -0.004287 & -0.0393 & 0.484376 \tabularnewline
10 & -0.02017 & -0.1849 & 0.426892 \tabularnewline
11 & 0.100398 & 0.9202 & 0.18006 \tabularnewline
12 & 0.043241 & 0.3963 & 0.346441 \tabularnewline
13 & -0.05407 & -0.4956 & 0.31075 \tabularnewline
14 & 0.013176 & 0.1208 & 0.452086 \tabularnewline
15 & 0.015528 & 0.1423 & 0.443584 \tabularnewline
16 & -0.025182 & -0.2308 & 0.409017 \tabularnewline
17 & -0.012378 & -0.1134 & 0.454974 \tabularnewline
18 & -0.02043 & -0.1872 & 0.425962 \tabularnewline
19 & -0.018693 & -0.1713 & 0.432189 \tabularnewline
20 & -0.025506 & -0.2338 & 0.407868 \tabularnewline
21 & 0.002934 & 0.0269 & 0.489306 \tabularnewline
22 & -0.003283 & -0.0301 & 0.488032 \tabularnewline
23 & -0.04898 & -0.4489 & 0.327325 \tabularnewline
24 & 0.017816 & 0.1633 & 0.435344 \tabularnewline
25 & -0.074171 & -0.6798 & 0.249253 \tabularnewline
26 & -0.021125 & -0.1936 & 0.423474 \tabularnewline
27 & -0.021107 & -0.1934 & 0.423537 \tabularnewline
28 & -0.03069 & -0.2813 & 0.389595 \tabularnewline
29 & -0.037437 & -0.3431 & 0.366186 \tabularnewline
30 & -0.027943 & -0.2561 & 0.39925 \tabularnewline
31 & -0.03055 & -0.28 & 0.390086 \tabularnewline
32 & -0.023789 & -0.218 & 0.413969 \tabularnewline
33 & -0.003948 & -0.0362 & 0.485609 \tabularnewline
34 & -0.002337 & -0.0214 & 0.49148 \tabularnewline
35 & 0.06492 & 0.595 & 0.276721 \tabularnewline
36 & 0.0506 & 0.4638 & 0.322011 \tabularnewline
37 & -0.174683 & -1.601 & 0.056566 \tabularnewline
38 & 0.008344 & 0.0765 & 0.469612 \tabularnewline
39 & 0.03223 & 0.2954 & 0.384212 \tabularnewline
40 & -0.015196 & -0.1393 & 0.444784 \tabularnewline
41 & -0.030926 & -0.2834 & 0.388768 \tabularnewline
42 & -0.019886 & -0.1823 & 0.427909 \tabularnewline
43 & -0.013446 & -0.1232 & 0.451109 \tabularnewline
44 & -0.007373 & -0.0676 & 0.473141 \tabularnewline
45 & -0.007516 & -0.0689 & 0.472623 \tabularnewline
46 & 0.018696 & 0.1714 & 0.432179 \tabularnewline
47 & -0.018555 & -0.1701 & 0.432686 \tabularnewline
48 & 0.015759 & 0.1444 & 0.442753 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94671&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]0.954788[/C][C]8.7508[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.040203[/C][C]-0.3685[/C][C]0.356725[/C][/ROW]
[ROW][C]3[/C][C]-0.034253[/C][C]-0.3139[/C][C]0.377174[/C][/ROW]
[ROW][C]4[/C][C]-0.027953[/C][C]-0.2562[/C][C]0.399214[/C][/ROW]
[ROW][C]5[/C][C]-0.015763[/C][C]-0.1445[/C][C]0.442738[/C][/ROW]
[ROW][C]6[/C][C]-0.030344[/C][C]-0.2781[/C][C]0.390805[/C][/ROW]
[ROW][C]7[/C][C]-0.037772[/C][C]-0.3462[/C][C]0.365034[/C][/ROW]
[ROW][C]8[/C][C]-0.025033[/C][C]-0.2294[/C][C]0.409545[/C][/ROW]
[ROW][C]9[/C][C]-0.004287[/C][C]-0.0393[/C][C]0.484376[/C][/ROW]
[ROW][C]10[/C][C]-0.02017[/C][C]-0.1849[/C][C]0.426892[/C][/ROW]
[ROW][C]11[/C][C]0.100398[/C][C]0.9202[/C][C]0.18006[/C][/ROW]
[ROW][C]12[/C][C]0.043241[/C][C]0.3963[/C][C]0.346441[/C][/ROW]
[ROW][C]13[/C][C]-0.05407[/C][C]-0.4956[/C][C]0.31075[/C][/ROW]
[ROW][C]14[/C][C]0.013176[/C][C]0.1208[/C][C]0.452086[/C][/ROW]
[ROW][C]15[/C][C]0.015528[/C][C]0.1423[/C][C]0.443584[/C][/ROW]
[ROW][C]16[/C][C]-0.025182[/C][C]-0.2308[/C][C]0.409017[/C][/ROW]
[ROW][C]17[/C][C]-0.012378[/C][C]-0.1134[/C][C]0.454974[/C][/ROW]
[ROW][C]18[/C][C]-0.02043[/C][C]-0.1872[/C][C]0.425962[/C][/ROW]
[ROW][C]19[/C][C]-0.018693[/C][C]-0.1713[/C][C]0.432189[/C][/ROW]
[ROW][C]20[/C][C]-0.025506[/C][C]-0.2338[/C][C]0.407868[/C][/ROW]
[ROW][C]21[/C][C]0.002934[/C][C]0.0269[/C][C]0.489306[/C][/ROW]
[ROW][C]22[/C][C]-0.003283[/C][C]-0.0301[/C][C]0.488032[/C][/ROW]
[ROW][C]23[/C][C]-0.04898[/C][C]-0.4489[/C][C]0.327325[/C][/ROW]
[ROW][C]24[/C][C]0.017816[/C][C]0.1633[/C][C]0.435344[/C][/ROW]
[ROW][C]25[/C][C]-0.074171[/C][C]-0.6798[/C][C]0.249253[/C][/ROW]
[ROW][C]26[/C][C]-0.021125[/C][C]-0.1936[/C][C]0.423474[/C][/ROW]
[ROW][C]27[/C][C]-0.021107[/C][C]-0.1934[/C][C]0.423537[/C][/ROW]
[ROW][C]28[/C][C]-0.03069[/C][C]-0.2813[/C][C]0.389595[/C][/ROW]
[ROW][C]29[/C][C]-0.037437[/C][C]-0.3431[/C][C]0.366186[/C][/ROW]
[ROW][C]30[/C][C]-0.027943[/C][C]-0.2561[/C][C]0.39925[/C][/ROW]
[ROW][C]31[/C][C]-0.03055[/C][C]-0.28[/C][C]0.390086[/C][/ROW]
[ROW][C]32[/C][C]-0.023789[/C][C]-0.218[/C][C]0.413969[/C][/ROW]
[ROW][C]33[/C][C]-0.003948[/C][C]-0.0362[/C][C]0.485609[/C][/ROW]
[ROW][C]34[/C][C]-0.002337[/C][C]-0.0214[/C][C]0.49148[/C][/ROW]
[ROW][C]35[/C][C]0.06492[/C][C]0.595[/C][C]0.276721[/C][/ROW]
[ROW][C]36[/C][C]0.0506[/C][C]0.4638[/C][C]0.322011[/C][/ROW]
[ROW][C]37[/C][C]-0.174683[/C][C]-1.601[/C][C]0.056566[/C][/ROW]
[ROW][C]38[/C][C]0.008344[/C][C]0.0765[/C][C]0.469612[/C][/ROW]
[ROW][C]39[/C][C]0.03223[/C][C]0.2954[/C][C]0.384212[/C][/ROW]
[ROW][C]40[/C][C]-0.015196[/C][C]-0.1393[/C][C]0.444784[/C][/ROW]
[ROW][C]41[/C][C]-0.030926[/C][C]-0.2834[/C][C]0.388768[/C][/ROW]
[ROW][C]42[/C][C]-0.019886[/C][C]-0.1823[/C][C]0.427909[/C][/ROW]
[ROW][C]43[/C][C]-0.013446[/C][C]-0.1232[/C][C]0.451109[/C][/ROW]
[ROW][C]44[/C][C]-0.007373[/C][C]-0.0676[/C][C]0.473141[/C][/ROW]
[ROW][C]45[/C][C]-0.007516[/C][C]-0.0689[/C][C]0.472623[/C][/ROW]
[ROW][C]46[/C][C]0.018696[/C][C]0.1714[/C][C]0.432179[/C][/ROW]
[ROW][C]47[/C][C]-0.018555[/C][C]-0.1701[/C][C]0.432686[/C][/ROW]
[ROW][C]48[/C][C]0.015759[/C][C]0.1444[/C][C]0.442753[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94671&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94671&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
10.9547888.75080
2-0.040203-0.36850.356725
3-0.034253-0.31390.377174
4-0.027953-0.25620.399214
5-0.015763-0.14450.442738
6-0.030344-0.27810.390805
7-0.037772-0.34620.365034
8-0.025033-0.22940.409545
9-0.004287-0.03930.484376
10-0.02017-0.18490.426892
110.1003980.92020.18006
120.0432410.39630.346441
13-0.05407-0.49560.31075
140.0131760.12080.452086
150.0155280.14230.443584
16-0.025182-0.23080.409017
17-0.012378-0.11340.454974
18-0.02043-0.18720.425962
19-0.018693-0.17130.432189
20-0.025506-0.23380.407868
210.0029340.02690.489306
22-0.003283-0.03010.488032
23-0.04898-0.44890.327325
240.0178160.16330.435344
25-0.074171-0.67980.249253
26-0.021125-0.19360.423474
27-0.021107-0.19340.423537
28-0.03069-0.28130.389595
29-0.037437-0.34310.366186
30-0.027943-0.25610.39925
31-0.03055-0.280.390086
32-0.023789-0.2180.413969
33-0.003948-0.03620.485609
34-0.002337-0.02140.49148
350.064920.5950.276721
360.05060.46380.322011
37-0.174683-1.6010.056566
380.0083440.07650.469612
390.032230.29540.384212
40-0.015196-0.13930.444784
41-0.030926-0.28340.388768
42-0.019886-0.18230.427909
43-0.013446-0.12320.451109
44-0.007373-0.06760.473141
45-0.007516-0.06890.472623
460.0186960.17140.432179
47-0.018555-0.17010.432686
480.0157590.14440.442753



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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')