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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 06 Dec 2007 07:06:53 -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/2007/Dec/06/t1196949230hmm4c89qojgk6u3.htm/, Retrieved Fri, 03 May 2024 06:30:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2612, Retrieved Fri, 03 May 2024 06:30:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsreeks 4
Estimated Impact192
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Workshop 4 Q4] [2007-12-06 14:06:53] [e38ae300fa323c405e42b78372d772d6] [Current]
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Dataseries X:
-0.0161470029182524 
-0.00217918117242405 
-0.00101681243724944 
0.0302647334318750 
-0.0103707758693905 
-0.0316283943452303 
0.0482250575030986 
-0.00778388058255816 
0.0739213560071713 
-0.0355219211705796 
-0.0465860499530978 
-0.0183359518482659 
0.0849309396182536 
-0.00472883479485204 
-0.0457663996097076 
0.0194892368208509 
-0.0844586838805345 
0.0158438070140536 
0.0249353169266053 
-0.0154862497940329 
-0.0570963231046569 
0.0194811649211625 
0.05542357887686 
-0.0184271136655211 
0.0550211854847744 
0.0139860059849044 
0.0180850001205276 
0.0113435104270672 
-0.00975914295057982 
0.0183856587950422 
0.0651601806871196 
-0.00180131284799998 
-0.0380454828469899 
0.0227023476550891 
-0.0233128896761908 
-0.0333407722698318 
-0.0775215156899833 
0.0279606227704031 
-0.0189672425012947 
0.0261649400887914 
0.0280801227662849 
-0.00982841149575672 
0.0757245409696279 
-0.0456789455501814 
-0.0274673712585132 
-0.0363291869956202 
0.0677351537467136 
0.0477360963481313 
0.0230282564519755 
0.0387067842378921 
0.0417253858710914 
0.0146246322736662 
0.0227143621321611 
0.0433601386275023 
-0.00274115692977646 
-0.0129603851411029 
-0.00934895009209842 
-0.0515257082121934 
0.00443386032185225 
0.0518640157456822 
0.0171664295790064 
0.0376182080442142 
0.0039243188528491 
-0.0577965899903973 
-0.0146157607324355 
-0.0184907295399863 
-0.0449466844100761 
0.0235491858576680 
-0.0513516327592869 




Summary of compuational 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 compuational 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=2612&T=0

[TABLE]
[ROW][C]Summary of compuational 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=2612&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2612&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 compuational 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
018.30660
1-0.028004-0.23260.591626
2-0.030959-0.25720.601093
3-0.009295-0.07720.53066
4-0.041325-0.34330.633782
50.0060470.05020.480042
6-0.022947-0.19060.575306
70.0207780.17260.431739
8-0.215852-1.7930.961322
90.2168991.80170.03798
10-0.127716-1.06090.85378
11-0.033209-0.27590.608257
120.0403590.33520.369229
13-0.038385-0.31890.624598
14-0.184706-1.53430.935234
15-0.118373-0.98330.835548
160.0243130.2020.420271
17-0.158609-1.31750.903987
180.1002420.83270.20395
19-0.006135-0.0510.520249
200.0664990.55240.291234
210.0233080.19360.423525
220.1056860.87790.191524
23-0.020811-0.17290.568371
24-0.065202-0.54160.705084
250.1566011.30080.098823
26-0.18802-1.56180.938546
270.0842990.70020.243066
28-0.017818-0.1480.558615
290.0803930.66780.253246
30-0.004074-0.03380.513449
310.0283360.23540.407306
32-0.022625-0.18790.574262
33-0.180996-1.50350.931359
340.1665471.38340.085495
35-0.026552-0.22060.586954
36-0.015955-0.13250.552524
37-0.059264-0.49230.68796
380.0180180.14970.440733
39-0.069107-0.5740.716099
400.0097070.08060.467984
410.0226810.18840.425556
42-0.087082-0.72340.764046
430.0299240.24860.402217
44-0.022748-0.1890.57466
45-0.045562-0.37850.646877
460.0009020.00750.49702
470.0871140.72360.235871

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 8.3066 & 0 \tabularnewline
1 & -0.028004 & -0.2326 & 0.591626 \tabularnewline
2 & -0.030959 & -0.2572 & 0.601093 \tabularnewline
3 & -0.009295 & -0.0772 & 0.53066 \tabularnewline
4 & -0.041325 & -0.3433 & 0.633782 \tabularnewline
5 & 0.006047 & 0.0502 & 0.480042 \tabularnewline
6 & -0.022947 & -0.1906 & 0.575306 \tabularnewline
7 & 0.020778 & 0.1726 & 0.431739 \tabularnewline
8 & -0.215852 & -1.793 & 0.961322 \tabularnewline
9 & 0.216899 & 1.8017 & 0.03798 \tabularnewline
10 & -0.127716 & -1.0609 & 0.85378 \tabularnewline
11 & -0.033209 & -0.2759 & 0.608257 \tabularnewline
12 & 0.040359 & 0.3352 & 0.369229 \tabularnewline
13 & -0.038385 & -0.3189 & 0.624598 \tabularnewline
14 & -0.184706 & -1.5343 & 0.935234 \tabularnewline
15 & -0.118373 & -0.9833 & 0.835548 \tabularnewline
16 & 0.024313 & 0.202 & 0.420271 \tabularnewline
17 & -0.158609 & -1.3175 & 0.903987 \tabularnewline
18 & 0.100242 & 0.8327 & 0.20395 \tabularnewline
19 & -0.006135 & -0.051 & 0.520249 \tabularnewline
20 & 0.066499 & 0.5524 & 0.291234 \tabularnewline
21 & 0.023308 & 0.1936 & 0.423525 \tabularnewline
22 & 0.105686 & 0.8779 & 0.191524 \tabularnewline
23 & -0.020811 & -0.1729 & 0.568371 \tabularnewline
24 & -0.065202 & -0.5416 & 0.705084 \tabularnewline
25 & 0.156601 & 1.3008 & 0.098823 \tabularnewline
26 & -0.18802 & -1.5618 & 0.938546 \tabularnewline
27 & 0.084299 & 0.7002 & 0.243066 \tabularnewline
28 & -0.017818 & -0.148 & 0.558615 \tabularnewline
29 & 0.080393 & 0.6678 & 0.253246 \tabularnewline
30 & -0.004074 & -0.0338 & 0.513449 \tabularnewline
31 & 0.028336 & 0.2354 & 0.407306 \tabularnewline
32 & -0.022625 & -0.1879 & 0.574262 \tabularnewline
33 & -0.180996 & -1.5035 & 0.931359 \tabularnewline
34 & 0.166547 & 1.3834 & 0.085495 \tabularnewline
35 & -0.026552 & -0.2206 & 0.586954 \tabularnewline
36 & -0.015955 & -0.1325 & 0.552524 \tabularnewline
37 & -0.059264 & -0.4923 & 0.68796 \tabularnewline
38 & 0.018018 & 0.1497 & 0.440733 \tabularnewline
39 & -0.069107 & -0.574 & 0.716099 \tabularnewline
40 & 0.009707 & 0.0806 & 0.467984 \tabularnewline
41 & 0.022681 & 0.1884 & 0.425556 \tabularnewline
42 & -0.087082 & -0.7234 & 0.764046 \tabularnewline
43 & 0.029924 & 0.2486 & 0.402217 \tabularnewline
44 & -0.022748 & -0.189 & 0.57466 \tabularnewline
45 & -0.045562 & -0.3785 & 0.646877 \tabularnewline
46 & 0.000902 & 0.0075 & 0.49702 \tabularnewline
47 & 0.087114 & 0.7236 & 0.235871 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2612&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]0[/C][C]1[/C][C]8.3066[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]-0.028004[/C][C]-0.2326[/C][C]0.591626[/C][/ROW]
[ROW][C]2[/C][C]-0.030959[/C][C]-0.2572[/C][C]0.601093[/C][/ROW]
[ROW][C]3[/C][C]-0.009295[/C][C]-0.0772[/C][C]0.53066[/C][/ROW]
[ROW][C]4[/C][C]-0.041325[/C][C]-0.3433[/C][C]0.633782[/C][/ROW]
[ROW][C]5[/C][C]0.006047[/C][C]0.0502[/C][C]0.480042[/C][/ROW]
[ROW][C]6[/C][C]-0.022947[/C][C]-0.1906[/C][C]0.575306[/C][/ROW]
[ROW][C]7[/C][C]0.020778[/C][C]0.1726[/C][C]0.431739[/C][/ROW]
[ROW][C]8[/C][C]-0.215852[/C][C]-1.793[/C][C]0.961322[/C][/ROW]
[ROW][C]9[/C][C]0.216899[/C][C]1.8017[/C][C]0.03798[/C][/ROW]
[ROW][C]10[/C][C]-0.127716[/C][C]-1.0609[/C][C]0.85378[/C][/ROW]
[ROW][C]11[/C][C]-0.033209[/C][C]-0.2759[/C][C]0.608257[/C][/ROW]
[ROW][C]12[/C][C]0.040359[/C][C]0.3352[/C][C]0.369229[/C][/ROW]
[ROW][C]13[/C][C]-0.038385[/C][C]-0.3189[/C][C]0.624598[/C][/ROW]
[ROW][C]14[/C][C]-0.184706[/C][C]-1.5343[/C][C]0.935234[/C][/ROW]
[ROW][C]15[/C][C]-0.118373[/C][C]-0.9833[/C][C]0.835548[/C][/ROW]
[ROW][C]16[/C][C]0.024313[/C][C]0.202[/C][C]0.420271[/C][/ROW]
[ROW][C]17[/C][C]-0.158609[/C][C]-1.3175[/C][C]0.903987[/C][/ROW]
[ROW][C]18[/C][C]0.100242[/C][C]0.8327[/C][C]0.20395[/C][/ROW]
[ROW][C]19[/C][C]-0.006135[/C][C]-0.051[/C][C]0.520249[/C][/ROW]
[ROW][C]20[/C][C]0.066499[/C][C]0.5524[/C][C]0.291234[/C][/ROW]
[ROW][C]21[/C][C]0.023308[/C][C]0.1936[/C][C]0.423525[/C][/ROW]
[ROW][C]22[/C][C]0.105686[/C][C]0.8779[/C][C]0.191524[/C][/ROW]
[ROW][C]23[/C][C]-0.020811[/C][C]-0.1729[/C][C]0.568371[/C][/ROW]
[ROW][C]24[/C][C]-0.065202[/C][C]-0.5416[/C][C]0.705084[/C][/ROW]
[ROW][C]25[/C][C]0.156601[/C][C]1.3008[/C][C]0.098823[/C][/ROW]
[ROW][C]26[/C][C]-0.18802[/C][C]-1.5618[/C][C]0.938546[/C][/ROW]
[ROW][C]27[/C][C]0.084299[/C][C]0.7002[/C][C]0.243066[/C][/ROW]
[ROW][C]28[/C][C]-0.017818[/C][C]-0.148[/C][C]0.558615[/C][/ROW]
[ROW][C]29[/C][C]0.080393[/C][C]0.6678[/C][C]0.253246[/C][/ROW]
[ROW][C]30[/C][C]-0.004074[/C][C]-0.0338[/C][C]0.513449[/C][/ROW]
[ROW][C]31[/C][C]0.028336[/C][C]0.2354[/C][C]0.407306[/C][/ROW]
[ROW][C]32[/C][C]-0.022625[/C][C]-0.1879[/C][C]0.574262[/C][/ROW]
[ROW][C]33[/C][C]-0.180996[/C][C]-1.5035[/C][C]0.931359[/C][/ROW]
[ROW][C]34[/C][C]0.166547[/C][C]1.3834[/C][C]0.085495[/C][/ROW]
[ROW][C]35[/C][C]-0.026552[/C][C]-0.2206[/C][C]0.586954[/C][/ROW]
[ROW][C]36[/C][C]-0.015955[/C][C]-0.1325[/C][C]0.552524[/C][/ROW]
[ROW][C]37[/C][C]-0.059264[/C][C]-0.4923[/C][C]0.68796[/C][/ROW]
[ROW][C]38[/C][C]0.018018[/C][C]0.1497[/C][C]0.440733[/C][/ROW]
[ROW][C]39[/C][C]-0.069107[/C][C]-0.574[/C][C]0.716099[/C][/ROW]
[ROW][C]40[/C][C]0.009707[/C][C]0.0806[/C][C]0.467984[/C][/ROW]
[ROW][C]41[/C][C]0.022681[/C][C]0.1884[/C][C]0.425556[/C][/ROW]
[ROW][C]42[/C][C]-0.087082[/C][C]-0.7234[/C][C]0.764046[/C][/ROW]
[ROW][C]43[/C][C]0.029924[/C][C]0.2486[/C][C]0.402217[/C][/ROW]
[ROW][C]44[/C][C]-0.022748[/C][C]-0.189[/C][C]0.57466[/C][/ROW]
[ROW][C]45[/C][C]-0.045562[/C][C]-0.3785[/C][C]0.646877[/C][/ROW]
[ROW][C]46[/C][C]0.000902[/C][C]0.0075[/C][C]0.49702[/C][/ROW]
[ROW][C]47[/C][C]0.087114[/C][C]0.7236[/C][C]0.235871[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2612&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2612&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
018.30660
1-0.028004-0.23260.591626
2-0.030959-0.25720.601093
3-0.009295-0.07720.53066
4-0.041325-0.34330.633782
50.0060470.05020.480042
6-0.022947-0.19060.575306
70.0207780.17260.431739
8-0.215852-1.7930.961322
90.2168991.80170.03798
10-0.127716-1.06090.85378
11-0.033209-0.27590.608257
120.0403590.33520.369229
13-0.038385-0.31890.624598
14-0.184706-1.53430.935234
15-0.118373-0.98330.835548
160.0243130.2020.420271
17-0.158609-1.31750.903987
180.1002420.83270.20395
19-0.006135-0.0510.520249
200.0664990.55240.291234
210.0233080.19360.423525
220.1056860.87790.191524
23-0.020811-0.17290.568371
24-0.065202-0.54160.705084
250.1566011.30080.098823
26-0.18802-1.56180.938546
270.0842990.70020.243066
28-0.017818-0.1480.558615
290.0803930.66780.253246
30-0.004074-0.03380.513449
310.0283360.23540.407306
32-0.022625-0.18790.574262
33-0.180996-1.50350.931359
340.1665471.38340.085495
35-0.026552-0.22060.586954
36-0.015955-0.13250.552524
37-0.059264-0.49230.68796
380.0180180.14970.440733
39-0.069107-0.5740.716099
400.0097070.08060.467984
410.0226810.18840.425556
42-0.087082-0.72340.764046
430.0299240.24860.402217
44-0.022748-0.1890.57466
45-0.045562-0.37850.646877
460.0009020.00750.49702
470.0871140.72360.235871







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
0-0.028004-0.23260.591626
1-0.031768-0.26390.603674
2-0.011099-0.09220.536595
3-0.042984-0.35710.638928
40.0029320.02440.490318
5-0.025606-0.21270.583906
60.0188160.15630.438127
7-0.219037-1.81950.96341
80.2178171.80930.037378
9-0.160286-1.33140.906286
10-0.007223-0.060.523835
110.0080930.06720.473297
12-0.020938-0.17390.568782
13-0.239095-1.98610.9745
14-0.094345-0.78370.782047
15-0.070263-0.58360.71932
16-0.101943-0.84680.799984
17-0.040015-0.33240.629697
180.015880.13190.447721
190.059070.49070.312607
20-0.036614-0.30410.61903
210.0717920.59630.276447
22-0.006956-0.05780.522956
23-0.072881-0.60540.726547
240.0803760.66770.253292
25-0.149041-1.2380.890049
260.0455630.37850.353119
27-0.079575-0.6610.744592
280.0531990.44190.32997
29-0.035605-0.29580.615849
30-0.019226-0.15970.563209
31-0.075365-0.6260.733319
32-0.102759-0.85360.801854
330.0549180.45620.324847
340.10940.90870.183324
35-0.06301-0.52340.698815
360.0033370.02770.488984
37-0.007536-0.06260.524866
38-0.05301-0.44030.669465
39-0.067688-0.56230.712118
40-0.053104-0.44110.669745
41-0.009526-0.07910.531419
42-0.088276-0.73330.767062
43-0.014166-0.11770.546665
44-0.068492-0.56890.714378
450.0068740.05710.477314
46-0.061201-0.50840.693593
470.0822510.68320.248375

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & -0.028004 & -0.2326 & 0.591626 \tabularnewline
1 & -0.031768 & -0.2639 & 0.603674 \tabularnewline
2 & -0.011099 & -0.0922 & 0.536595 \tabularnewline
3 & -0.042984 & -0.3571 & 0.638928 \tabularnewline
4 & 0.002932 & 0.0244 & 0.490318 \tabularnewline
5 & -0.025606 & -0.2127 & 0.583906 \tabularnewline
6 & 0.018816 & 0.1563 & 0.438127 \tabularnewline
7 & -0.219037 & -1.8195 & 0.96341 \tabularnewline
8 & 0.217817 & 1.8093 & 0.037378 \tabularnewline
9 & -0.160286 & -1.3314 & 0.906286 \tabularnewline
10 & -0.007223 & -0.06 & 0.523835 \tabularnewline
11 & 0.008093 & 0.0672 & 0.473297 \tabularnewline
12 & -0.020938 & -0.1739 & 0.568782 \tabularnewline
13 & -0.239095 & -1.9861 & 0.9745 \tabularnewline
14 & -0.094345 & -0.7837 & 0.782047 \tabularnewline
15 & -0.070263 & -0.5836 & 0.71932 \tabularnewline
16 & -0.101943 & -0.8468 & 0.799984 \tabularnewline
17 & -0.040015 & -0.3324 & 0.629697 \tabularnewline
18 & 0.01588 & 0.1319 & 0.447721 \tabularnewline
19 & 0.05907 & 0.4907 & 0.312607 \tabularnewline
20 & -0.036614 & -0.3041 & 0.61903 \tabularnewline
21 & 0.071792 & 0.5963 & 0.276447 \tabularnewline
22 & -0.006956 & -0.0578 & 0.522956 \tabularnewline
23 & -0.072881 & -0.6054 & 0.726547 \tabularnewline
24 & 0.080376 & 0.6677 & 0.253292 \tabularnewline
25 & -0.149041 & -1.238 & 0.890049 \tabularnewline
26 & 0.045563 & 0.3785 & 0.353119 \tabularnewline
27 & -0.079575 & -0.661 & 0.744592 \tabularnewline
28 & 0.053199 & 0.4419 & 0.32997 \tabularnewline
29 & -0.035605 & -0.2958 & 0.615849 \tabularnewline
30 & -0.019226 & -0.1597 & 0.563209 \tabularnewline
31 & -0.075365 & -0.626 & 0.733319 \tabularnewline
32 & -0.102759 & -0.8536 & 0.801854 \tabularnewline
33 & 0.054918 & 0.4562 & 0.324847 \tabularnewline
34 & 0.1094 & 0.9087 & 0.183324 \tabularnewline
35 & -0.06301 & -0.5234 & 0.698815 \tabularnewline
36 & 0.003337 & 0.0277 & 0.488984 \tabularnewline
37 & -0.007536 & -0.0626 & 0.524866 \tabularnewline
38 & -0.05301 & -0.4403 & 0.669465 \tabularnewline
39 & -0.067688 & -0.5623 & 0.712118 \tabularnewline
40 & -0.053104 & -0.4411 & 0.669745 \tabularnewline
41 & -0.009526 & -0.0791 & 0.531419 \tabularnewline
42 & -0.088276 & -0.7333 & 0.767062 \tabularnewline
43 & -0.014166 & -0.1177 & 0.546665 \tabularnewline
44 & -0.068492 & -0.5689 & 0.714378 \tabularnewline
45 & 0.006874 & 0.0571 & 0.477314 \tabularnewline
46 & -0.061201 & -0.5084 & 0.693593 \tabularnewline
47 & 0.082251 & 0.6832 & 0.248375 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2612&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]0[/C][C]-0.028004[/C][C]-0.2326[/C][C]0.591626[/C][/ROW]
[ROW][C]1[/C][C]-0.031768[/C][C]-0.2639[/C][C]0.603674[/C][/ROW]
[ROW][C]2[/C][C]-0.011099[/C][C]-0.0922[/C][C]0.536595[/C][/ROW]
[ROW][C]3[/C][C]-0.042984[/C][C]-0.3571[/C][C]0.638928[/C][/ROW]
[ROW][C]4[/C][C]0.002932[/C][C]0.0244[/C][C]0.490318[/C][/ROW]
[ROW][C]5[/C][C]-0.025606[/C][C]-0.2127[/C][C]0.583906[/C][/ROW]
[ROW][C]6[/C][C]0.018816[/C][C]0.1563[/C][C]0.438127[/C][/ROW]
[ROW][C]7[/C][C]-0.219037[/C][C]-1.8195[/C][C]0.96341[/C][/ROW]
[ROW][C]8[/C][C]0.217817[/C][C]1.8093[/C][C]0.037378[/C][/ROW]
[ROW][C]9[/C][C]-0.160286[/C][C]-1.3314[/C][C]0.906286[/C][/ROW]
[ROW][C]10[/C][C]-0.007223[/C][C]-0.06[/C][C]0.523835[/C][/ROW]
[ROW][C]11[/C][C]0.008093[/C][C]0.0672[/C][C]0.473297[/C][/ROW]
[ROW][C]12[/C][C]-0.020938[/C][C]-0.1739[/C][C]0.568782[/C][/ROW]
[ROW][C]13[/C][C]-0.239095[/C][C]-1.9861[/C][C]0.9745[/C][/ROW]
[ROW][C]14[/C][C]-0.094345[/C][C]-0.7837[/C][C]0.782047[/C][/ROW]
[ROW][C]15[/C][C]-0.070263[/C][C]-0.5836[/C][C]0.71932[/C][/ROW]
[ROW][C]16[/C][C]-0.101943[/C][C]-0.8468[/C][C]0.799984[/C][/ROW]
[ROW][C]17[/C][C]-0.040015[/C][C]-0.3324[/C][C]0.629697[/C][/ROW]
[ROW][C]18[/C][C]0.01588[/C][C]0.1319[/C][C]0.447721[/C][/ROW]
[ROW][C]19[/C][C]0.05907[/C][C]0.4907[/C][C]0.312607[/C][/ROW]
[ROW][C]20[/C][C]-0.036614[/C][C]-0.3041[/C][C]0.61903[/C][/ROW]
[ROW][C]21[/C][C]0.071792[/C][C]0.5963[/C][C]0.276447[/C][/ROW]
[ROW][C]22[/C][C]-0.006956[/C][C]-0.0578[/C][C]0.522956[/C][/ROW]
[ROW][C]23[/C][C]-0.072881[/C][C]-0.6054[/C][C]0.726547[/C][/ROW]
[ROW][C]24[/C][C]0.080376[/C][C]0.6677[/C][C]0.253292[/C][/ROW]
[ROW][C]25[/C][C]-0.149041[/C][C]-1.238[/C][C]0.890049[/C][/ROW]
[ROW][C]26[/C][C]0.045563[/C][C]0.3785[/C][C]0.353119[/C][/ROW]
[ROW][C]27[/C][C]-0.079575[/C][C]-0.661[/C][C]0.744592[/C][/ROW]
[ROW][C]28[/C][C]0.053199[/C][C]0.4419[/C][C]0.32997[/C][/ROW]
[ROW][C]29[/C][C]-0.035605[/C][C]-0.2958[/C][C]0.615849[/C][/ROW]
[ROW][C]30[/C][C]-0.019226[/C][C]-0.1597[/C][C]0.563209[/C][/ROW]
[ROW][C]31[/C][C]-0.075365[/C][C]-0.626[/C][C]0.733319[/C][/ROW]
[ROW][C]32[/C][C]-0.102759[/C][C]-0.8536[/C][C]0.801854[/C][/ROW]
[ROW][C]33[/C][C]0.054918[/C][C]0.4562[/C][C]0.324847[/C][/ROW]
[ROW][C]34[/C][C]0.1094[/C][C]0.9087[/C][C]0.183324[/C][/ROW]
[ROW][C]35[/C][C]-0.06301[/C][C]-0.5234[/C][C]0.698815[/C][/ROW]
[ROW][C]36[/C][C]0.003337[/C][C]0.0277[/C][C]0.488984[/C][/ROW]
[ROW][C]37[/C][C]-0.007536[/C][C]-0.0626[/C][C]0.524866[/C][/ROW]
[ROW][C]38[/C][C]-0.05301[/C][C]-0.4403[/C][C]0.669465[/C][/ROW]
[ROW][C]39[/C][C]-0.067688[/C][C]-0.5623[/C][C]0.712118[/C][/ROW]
[ROW][C]40[/C][C]-0.053104[/C][C]-0.4411[/C][C]0.669745[/C][/ROW]
[ROW][C]41[/C][C]-0.009526[/C][C]-0.0791[/C][C]0.531419[/C][/ROW]
[ROW][C]42[/C][C]-0.088276[/C][C]-0.7333[/C][C]0.767062[/C][/ROW]
[ROW][C]43[/C][C]-0.014166[/C][C]-0.1177[/C][C]0.546665[/C][/ROW]
[ROW][C]44[/C][C]-0.068492[/C][C]-0.5689[/C][C]0.714378[/C][/ROW]
[ROW][C]45[/C][C]0.006874[/C][C]0.0571[/C][C]0.477314[/C][/ROW]
[ROW][C]46[/C][C]-0.061201[/C][C]-0.5084[/C][C]0.693593[/C][/ROW]
[ROW][C]47[/C][C]0.082251[/C][C]0.6832[/C][C]0.248375[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2612&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2612&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
0-0.028004-0.23260.591626
1-0.031768-0.26390.603674
2-0.011099-0.09220.536595
3-0.042984-0.35710.638928
40.0029320.02440.490318
5-0.025606-0.21270.583906
60.0188160.15630.438127
7-0.219037-1.81950.96341
80.2178171.80930.037378
9-0.160286-1.33140.906286
10-0.007223-0.060.523835
110.0080930.06720.473297
12-0.020938-0.17390.568782
13-0.239095-1.98610.9745
14-0.094345-0.78370.782047
15-0.070263-0.58360.71932
16-0.101943-0.84680.799984
17-0.040015-0.33240.629697
180.015880.13190.447721
190.059070.49070.312607
20-0.036614-0.30410.61903
210.0717920.59630.276447
22-0.006956-0.05780.522956
23-0.072881-0.60540.726547
240.0803760.66770.253292
25-0.149041-1.2380.890049
260.0455630.37850.353119
27-0.079575-0.6610.744592
280.0531990.44190.32997
29-0.035605-0.29580.615849
30-0.019226-0.15970.563209
31-0.075365-0.6260.733319
32-0.102759-0.85360.801854
330.0549180.45620.324847
340.10940.90870.183324
35-0.06301-0.52340.698815
360.0033370.02770.488984
37-0.007536-0.06260.524866
38-0.05301-0.44030.669465
39-0.067688-0.56230.712118
40-0.053104-0.44110.669745
41-0.009526-0.07910.531419
42-0.088276-0.73330.767062
43-0.014166-0.11770.546665
44-0.068492-0.56890.714378
450.0068740.05710.477314
46-0.061201-0.50840.693593
470.0822510.68320.248375



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; 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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')