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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 computationFri, 04 Dec 2009 05:34:59 -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/04/t1259930146tgubdqfdts7zqxp.htm/, Retrieved Sat, 27 Apr 2024 17:36:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63419, Retrieved Sat, 27 Apr 2024 17:36:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [ws9] [2009-12-04 12:34:59] [b243db81ea3e1f02fb3382887fb0f701] [Current]
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Dataseries X:
5594
5585
5710
5511
5403
5826
5884
5965
5960
6064
6046
5954
5952
5960
5983
5996
6021
6094
6202
6276
6306
6342
6345
6328
6191
6261
6253
6198
6247
6293
6381
6448
6470
6516
6532
6526
6533
6498
6507
6464
6453
6468
6497
6808
6793
6907
6792
6757
6734
6654
6589
6469
6521
6448
6410
6528
6445
6458
6215
6167




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=63419&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=63419&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63419&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
10.8140225.63970
20.654784.53641.9e-05
30.5346073.70390.000274
40.4073822.82240.003458
50.2754631.90850.031161
60.2032551.40820.082759
70.1710351.1850.120932
80.1159910.80360.212793
90.0493940.34220.366842
10-0.010368-0.07180.471517
11-0.061151-0.42370.336851
12-0.100135-0.69380.24559
13-0.101334-0.70210.243015
14-0.111871-0.77510.221051
15-0.075623-0.52390.301369
16-0.040468-0.28040.390198
17-0.005974-0.04140.48358
18-0.02957-0.20490.419272
19-0.049853-0.34540.365656
20-0.025586-0.17730.430024
21-0.015048-0.10430.4587
22-0.008008-0.05550.477992
230.0133420.09240.463369
240.046230.32030.37507
250.0320810.22230.412526
260.0126390.08760.465293
270.0186350.12910.448906
280.001960.01360.49461
29-0.016247-0.11260.455423
30-0.046542-0.32250.374254
31-0.072781-0.50420.3082
32-0.104059-0.72090.237221
33-0.145125-1.00550.159859
34-0.175674-1.21710.114757
35-0.200659-1.39020.085439
36-0.219314-1.51950.067605
37-0.210395-1.45770.075723
38-0.227727-1.57770.060597
39-0.254729-1.76480.041978
40-0.255171-1.76790.041719
41-0.263525-1.82580.037056
42-0.276355-1.91460.030754
43-0.287496-1.99180.026048
44-0.187296-1.29760.100309
45-0.120567-0.83530.203839
46-0.102649-0.71120.24021
47-0.049515-0.34310.366528
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.814022 & 5.6397 & 0 \tabularnewline
2 & 0.65478 & 4.5364 & 1.9e-05 \tabularnewline
3 & 0.534607 & 3.7039 & 0.000274 \tabularnewline
4 & 0.407382 & 2.8224 & 0.003458 \tabularnewline
5 & 0.275463 & 1.9085 & 0.031161 \tabularnewline
6 & 0.203255 & 1.4082 & 0.082759 \tabularnewline
7 & 0.171035 & 1.185 & 0.120932 \tabularnewline
8 & 0.115991 & 0.8036 & 0.212793 \tabularnewline
9 & 0.049394 & 0.3422 & 0.366842 \tabularnewline
10 & -0.010368 & -0.0718 & 0.471517 \tabularnewline
11 & -0.061151 & -0.4237 & 0.336851 \tabularnewline
12 & -0.100135 & -0.6938 & 0.24559 \tabularnewline
13 & -0.101334 & -0.7021 & 0.243015 \tabularnewline
14 & -0.111871 & -0.7751 & 0.221051 \tabularnewline
15 & -0.075623 & -0.5239 & 0.301369 \tabularnewline
16 & -0.040468 & -0.2804 & 0.390198 \tabularnewline
17 & -0.005974 & -0.0414 & 0.48358 \tabularnewline
18 & -0.02957 & -0.2049 & 0.419272 \tabularnewline
19 & -0.049853 & -0.3454 & 0.365656 \tabularnewline
20 & -0.025586 & -0.1773 & 0.430024 \tabularnewline
21 & -0.015048 & -0.1043 & 0.4587 \tabularnewline
22 & -0.008008 & -0.0555 & 0.477992 \tabularnewline
23 & 0.013342 & 0.0924 & 0.463369 \tabularnewline
24 & 0.04623 & 0.3203 & 0.37507 \tabularnewline
25 & 0.032081 & 0.2223 & 0.412526 \tabularnewline
26 & 0.012639 & 0.0876 & 0.465293 \tabularnewline
27 & 0.018635 & 0.1291 & 0.448906 \tabularnewline
28 & 0.00196 & 0.0136 & 0.49461 \tabularnewline
29 & -0.016247 & -0.1126 & 0.455423 \tabularnewline
30 & -0.046542 & -0.3225 & 0.374254 \tabularnewline
31 & -0.072781 & -0.5042 & 0.3082 \tabularnewline
32 & -0.104059 & -0.7209 & 0.237221 \tabularnewline
33 & -0.145125 & -1.0055 & 0.159859 \tabularnewline
34 & -0.175674 & -1.2171 & 0.114757 \tabularnewline
35 & -0.200659 & -1.3902 & 0.085439 \tabularnewline
36 & -0.219314 & -1.5195 & 0.067605 \tabularnewline
37 & -0.210395 & -1.4577 & 0.075723 \tabularnewline
38 & -0.227727 & -1.5777 & 0.060597 \tabularnewline
39 & -0.254729 & -1.7648 & 0.041978 \tabularnewline
40 & -0.255171 & -1.7679 & 0.041719 \tabularnewline
41 & -0.263525 & -1.8258 & 0.037056 \tabularnewline
42 & -0.276355 & -1.9146 & 0.030754 \tabularnewline
43 & -0.287496 & -1.9918 & 0.026048 \tabularnewline
44 & -0.187296 & -1.2976 & 0.100309 \tabularnewline
45 & -0.120567 & -0.8353 & 0.203839 \tabularnewline
46 & -0.102649 & -0.7112 & 0.24021 \tabularnewline
47 & -0.049515 & -0.3431 & 0.366528 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63419&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]0.814022[/C][C]5.6397[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.65478[/C][C]4.5364[/C][C]1.9e-05[/C][/ROW]
[ROW][C]3[/C][C]0.534607[/C][C]3.7039[/C][C]0.000274[/C][/ROW]
[ROW][C]4[/C][C]0.407382[/C][C]2.8224[/C][C]0.003458[/C][/ROW]
[ROW][C]5[/C][C]0.275463[/C][C]1.9085[/C][C]0.031161[/C][/ROW]
[ROW][C]6[/C][C]0.203255[/C][C]1.4082[/C][C]0.082759[/C][/ROW]
[ROW][C]7[/C][C]0.171035[/C][C]1.185[/C][C]0.120932[/C][/ROW]
[ROW][C]8[/C][C]0.115991[/C][C]0.8036[/C][C]0.212793[/C][/ROW]
[ROW][C]9[/C][C]0.049394[/C][C]0.3422[/C][C]0.366842[/C][/ROW]
[ROW][C]10[/C][C]-0.010368[/C][C]-0.0718[/C][C]0.471517[/C][/ROW]
[ROW][C]11[/C][C]-0.061151[/C][C]-0.4237[/C][C]0.336851[/C][/ROW]
[ROW][C]12[/C][C]-0.100135[/C][C]-0.6938[/C][C]0.24559[/C][/ROW]
[ROW][C]13[/C][C]-0.101334[/C][C]-0.7021[/C][C]0.243015[/C][/ROW]
[ROW][C]14[/C][C]-0.111871[/C][C]-0.7751[/C][C]0.221051[/C][/ROW]
[ROW][C]15[/C][C]-0.075623[/C][C]-0.5239[/C][C]0.301369[/C][/ROW]
[ROW][C]16[/C][C]-0.040468[/C][C]-0.2804[/C][C]0.390198[/C][/ROW]
[ROW][C]17[/C][C]-0.005974[/C][C]-0.0414[/C][C]0.48358[/C][/ROW]
[ROW][C]18[/C][C]-0.02957[/C][C]-0.2049[/C][C]0.419272[/C][/ROW]
[ROW][C]19[/C][C]-0.049853[/C][C]-0.3454[/C][C]0.365656[/C][/ROW]
[ROW][C]20[/C][C]-0.025586[/C][C]-0.1773[/C][C]0.430024[/C][/ROW]
[ROW][C]21[/C][C]-0.015048[/C][C]-0.1043[/C][C]0.4587[/C][/ROW]
[ROW][C]22[/C][C]-0.008008[/C][C]-0.0555[/C][C]0.477992[/C][/ROW]
[ROW][C]23[/C][C]0.013342[/C][C]0.0924[/C][C]0.463369[/C][/ROW]
[ROW][C]24[/C][C]0.04623[/C][C]0.3203[/C][C]0.37507[/C][/ROW]
[ROW][C]25[/C][C]0.032081[/C][C]0.2223[/C][C]0.412526[/C][/ROW]
[ROW][C]26[/C][C]0.012639[/C][C]0.0876[/C][C]0.465293[/C][/ROW]
[ROW][C]27[/C][C]0.018635[/C][C]0.1291[/C][C]0.448906[/C][/ROW]
[ROW][C]28[/C][C]0.00196[/C][C]0.0136[/C][C]0.49461[/C][/ROW]
[ROW][C]29[/C][C]-0.016247[/C][C]-0.1126[/C][C]0.455423[/C][/ROW]
[ROW][C]30[/C][C]-0.046542[/C][C]-0.3225[/C][C]0.374254[/C][/ROW]
[ROW][C]31[/C][C]-0.072781[/C][C]-0.5042[/C][C]0.3082[/C][/ROW]
[ROW][C]32[/C][C]-0.104059[/C][C]-0.7209[/C][C]0.237221[/C][/ROW]
[ROW][C]33[/C][C]-0.145125[/C][C]-1.0055[/C][C]0.159859[/C][/ROW]
[ROW][C]34[/C][C]-0.175674[/C][C]-1.2171[/C][C]0.114757[/C][/ROW]
[ROW][C]35[/C][C]-0.200659[/C][C]-1.3902[/C][C]0.085439[/C][/ROW]
[ROW][C]36[/C][C]-0.219314[/C][C]-1.5195[/C][C]0.067605[/C][/ROW]
[ROW][C]37[/C][C]-0.210395[/C][C]-1.4577[/C][C]0.075723[/C][/ROW]
[ROW][C]38[/C][C]-0.227727[/C][C]-1.5777[/C][C]0.060597[/C][/ROW]
[ROW][C]39[/C][C]-0.254729[/C][C]-1.7648[/C][C]0.041978[/C][/ROW]
[ROW][C]40[/C][C]-0.255171[/C][C]-1.7679[/C][C]0.041719[/C][/ROW]
[ROW][C]41[/C][C]-0.263525[/C][C]-1.8258[/C][C]0.037056[/C][/ROW]
[ROW][C]42[/C][C]-0.276355[/C][C]-1.9146[/C][C]0.030754[/C][/ROW]
[ROW][C]43[/C][C]-0.287496[/C][C]-1.9918[/C][C]0.026048[/C][/ROW]
[ROW][C]44[/C][C]-0.187296[/C][C]-1.2976[/C][C]0.100309[/C][/ROW]
[ROW][C]45[/C][C]-0.120567[/C][C]-0.8353[/C][C]0.203839[/C][/ROW]
[ROW][C]46[/C][C]-0.102649[/C][C]-0.7112[/C][C]0.24021[/C][/ROW]
[ROW][C]47[/C][C]-0.049515[/C][C]-0.3431[/C][C]0.366528[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63419&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63419&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
10.8140225.63970
20.654784.53641.9e-05
30.5346073.70390.000274
40.4073822.82240.003458
50.2754631.90850.031161
60.2032551.40820.082759
70.1710351.1850.120932
80.1159910.80360.212793
90.0493940.34220.366842
10-0.010368-0.07180.471517
11-0.061151-0.42370.336851
12-0.100135-0.69380.24559
13-0.101334-0.70210.243015
14-0.111871-0.77510.221051
15-0.075623-0.52390.301369
16-0.040468-0.28040.390198
17-0.005974-0.04140.48358
18-0.02957-0.20490.419272
19-0.049853-0.34540.365656
20-0.025586-0.17730.430024
21-0.015048-0.10430.4587
22-0.008008-0.05550.477992
230.0133420.09240.463369
240.046230.32030.37507
250.0320810.22230.412526
260.0126390.08760.465293
270.0186350.12910.448906
280.001960.01360.49461
29-0.016247-0.11260.455423
30-0.046542-0.32250.374254
31-0.072781-0.50420.3082
32-0.104059-0.72090.237221
33-0.145125-1.00550.159859
34-0.175674-1.21710.114757
35-0.200659-1.39020.085439
36-0.219314-1.51950.067605
37-0.210395-1.45770.075723
38-0.227727-1.57770.060597
39-0.254729-1.76480.041978
40-0.255171-1.76790.041719
41-0.263525-1.82580.037056
42-0.276355-1.91460.030754
43-0.287496-1.99180.026048
44-0.187296-1.29760.100309
45-0.120567-0.83530.203839
46-0.102649-0.71120.24021
47-0.049515-0.34310.366528
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8140225.63970
2-0.023274-0.16130.436286
30.0241460.16730.433923
4-0.087466-0.6060.273691
5-0.09595-0.66480.254693
60.0730940.50640.307444
70.0672050.46560.3218
8-0.07163-0.49630.310986
9-0.08481-0.58760.279785
10-0.069483-0.48140.316214
11-0.026447-0.18320.427695
120.0112590.0780.469073
130.0687550.47630.317995
14-0.064867-0.44940.327579
150.1074220.74420.230178
160.0057330.03970.484241
170.0377240.26140.397466
18-0.14322-0.99230.163024
19-0.031386-0.21750.414389
200.1066140.73860.23186
210.0125270.08680.465599
220.008030.05560.477932
23-0.013598-0.09420.462667
240.013540.09380.462827
25-0.065075-0.45090.327063
260.005310.03680.485403
270.0655580.45420.325867
28-0.074548-0.51650.303943
290.0158960.11010.456382
30-0.111719-0.7740.221359
31-0.019372-0.13420.446898
32-0.048872-0.33860.368197
33-0.068621-0.47540.318322
340.0013820.00960.4962
35-0.025997-0.18010.428912
36-0.013527-0.09370.462862
370.0015060.01040.495859
38-0.102099-0.70740.24138
39-0.084539-0.58570.28041
400.0003250.00230.499107
41-0.041199-0.28540.388269
42-0.041308-0.28620.387981
43-0.050042-0.34670.365166
440.2228221.54380.064607
45-0.026877-0.18620.426532
46-0.089405-0.61940.269287
470.0560980.38870.349624
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.814022 & 5.6397 & 0 \tabularnewline
2 & -0.023274 & -0.1613 & 0.436286 \tabularnewline
3 & 0.024146 & 0.1673 & 0.433923 \tabularnewline
4 & -0.087466 & -0.606 & 0.273691 \tabularnewline
5 & -0.09595 & -0.6648 & 0.254693 \tabularnewline
6 & 0.073094 & 0.5064 & 0.307444 \tabularnewline
7 & 0.067205 & 0.4656 & 0.3218 \tabularnewline
8 & -0.07163 & -0.4963 & 0.310986 \tabularnewline
9 & -0.08481 & -0.5876 & 0.279785 \tabularnewline
10 & -0.069483 & -0.4814 & 0.316214 \tabularnewline
11 & -0.026447 & -0.1832 & 0.427695 \tabularnewline
12 & 0.011259 & 0.078 & 0.469073 \tabularnewline
13 & 0.068755 & 0.4763 & 0.317995 \tabularnewline
14 & -0.064867 & -0.4494 & 0.327579 \tabularnewline
15 & 0.107422 & 0.7442 & 0.230178 \tabularnewline
16 & 0.005733 & 0.0397 & 0.484241 \tabularnewline
17 & 0.037724 & 0.2614 & 0.397466 \tabularnewline
18 & -0.14322 & -0.9923 & 0.163024 \tabularnewline
19 & -0.031386 & -0.2175 & 0.414389 \tabularnewline
20 & 0.106614 & 0.7386 & 0.23186 \tabularnewline
21 & 0.012527 & 0.0868 & 0.465599 \tabularnewline
22 & 0.00803 & 0.0556 & 0.477932 \tabularnewline
23 & -0.013598 & -0.0942 & 0.462667 \tabularnewline
24 & 0.01354 & 0.0938 & 0.462827 \tabularnewline
25 & -0.065075 & -0.4509 & 0.327063 \tabularnewline
26 & 0.00531 & 0.0368 & 0.485403 \tabularnewline
27 & 0.065558 & 0.4542 & 0.325867 \tabularnewline
28 & -0.074548 & -0.5165 & 0.303943 \tabularnewline
29 & 0.015896 & 0.1101 & 0.456382 \tabularnewline
30 & -0.111719 & -0.774 & 0.221359 \tabularnewline
31 & -0.019372 & -0.1342 & 0.446898 \tabularnewline
32 & -0.048872 & -0.3386 & 0.368197 \tabularnewline
33 & -0.068621 & -0.4754 & 0.318322 \tabularnewline
34 & 0.001382 & 0.0096 & 0.4962 \tabularnewline
35 & -0.025997 & -0.1801 & 0.428912 \tabularnewline
36 & -0.013527 & -0.0937 & 0.462862 \tabularnewline
37 & 0.001506 & 0.0104 & 0.495859 \tabularnewline
38 & -0.102099 & -0.7074 & 0.24138 \tabularnewline
39 & -0.084539 & -0.5857 & 0.28041 \tabularnewline
40 & 0.000325 & 0.0023 & 0.499107 \tabularnewline
41 & -0.041199 & -0.2854 & 0.388269 \tabularnewline
42 & -0.041308 & -0.2862 & 0.387981 \tabularnewline
43 & -0.050042 & -0.3467 & 0.365166 \tabularnewline
44 & 0.222822 & 1.5438 & 0.064607 \tabularnewline
45 & -0.026877 & -0.1862 & 0.426532 \tabularnewline
46 & -0.089405 & -0.6194 & 0.269287 \tabularnewline
47 & 0.056098 & 0.3887 & 0.349624 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63419&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]0.814022[/C][C]5.6397[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.023274[/C][C]-0.1613[/C][C]0.436286[/C][/ROW]
[ROW][C]3[/C][C]0.024146[/C][C]0.1673[/C][C]0.433923[/C][/ROW]
[ROW][C]4[/C][C]-0.087466[/C][C]-0.606[/C][C]0.273691[/C][/ROW]
[ROW][C]5[/C][C]-0.09595[/C][C]-0.6648[/C][C]0.254693[/C][/ROW]
[ROW][C]6[/C][C]0.073094[/C][C]0.5064[/C][C]0.307444[/C][/ROW]
[ROW][C]7[/C][C]0.067205[/C][C]0.4656[/C][C]0.3218[/C][/ROW]
[ROW][C]8[/C][C]-0.07163[/C][C]-0.4963[/C][C]0.310986[/C][/ROW]
[ROW][C]9[/C][C]-0.08481[/C][C]-0.5876[/C][C]0.279785[/C][/ROW]
[ROW][C]10[/C][C]-0.069483[/C][C]-0.4814[/C][C]0.316214[/C][/ROW]
[ROW][C]11[/C][C]-0.026447[/C][C]-0.1832[/C][C]0.427695[/C][/ROW]
[ROW][C]12[/C][C]0.011259[/C][C]0.078[/C][C]0.469073[/C][/ROW]
[ROW][C]13[/C][C]0.068755[/C][C]0.4763[/C][C]0.317995[/C][/ROW]
[ROW][C]14[/C][C]-0.064867[/C][C]-0.4494[/C][C]0.327579[/C][/ROW]
[ROW][C]15[/C][C]0.107422[/C][C]0.7442[/C][C]0.230178[/C][/ROW]
[ROW][C]16[/C][C]0.005733[/C][C]0.0397[/C][C]0.484241[/C][/ROW]
[ROW][C]17[/C][C]0.037724[/C][C]0.2614[/C][C]0.397466[/C][/ROW]
[ROW][C]18[/C][C]-0.14322[/C][C]-0.9923[/C][C]0.163024[/C][/ROW]
[ROW][C]19[/C][C]-0.031386[/C][C]-0.2175[/C][C]0.414389[/C][/ROW]
[ROW][C]20[/C][C]0.106614[/C][C]0.7386[/C][C]0.23186[/C][/ROW]
[ROW][C]21[/C][C]0.012527[/C][C]0.0868[/C][C]0.465599[/C][/ROW]
[ROW][C]22[/C][C]0.00803[/C][C]0.0556[/C][C]0.477932[/C][/ROW]
[ROW][C]23[/C][C]-0.013598[/C][C]-0.0942[/C][C]0.462667[/C][/ROW]
[ROW][C]24[/C][C]0.01354[/C][C]0.0938[/C][C]0.462827[/C][/ROW]
[ROW][C]25[/C][C]-0.065075[/C][C]-0.4509[/C][C]0.327063[/C][/ROW]
[ROW][C]26[/C][C]0.00531[/C][C]0.0368[/C][C]0.485403[/C][/ROW]
[ROW][C]27[/C][C]0.065558[/C][C]0.4542[/C][C]0.325867[/C][/ROW]
[ROW][C]28[/C][C]-0.074548[/C][C]-0.5165[/C][C]0.303943[/C][/ROW]
[ROW][C]29[/C][C]0.015896[/C][C]0.1101[/C][C]0.456382[/C][/ROW]
[ROW][C]30[/C][C]-0.111719[/C][C]-0.774[/C][C]0.221359[/C][/ROW]
[ROW][C]31[/C][C]-0.019372[/C][C]-0.1342[/C][C]0.446898[/C][/ROW]
[ROW][C]32[/C][C]-0.048872[/C][C]-0.3386[/C][C]0.368197[/C][/ROW]
[ROW][C]33[/C][C]-0.068621[/C][C]-0.4754[/C][C]0.318322[/C][/ROW]
[ROW][C]34[/C][C]0.001382[/C][C]0.0096[/C][C]0.4962[/C][/ROW]
[ROW][C]35[/C][C]-0.025997[/C][C]-0.1801[/C][C]0.428912[/C][/ROW]
[ROW][C]36[/C][C]-0.013527[/C][C]-0.0937[/C][C]0.462862[/C][/ROW]
[ROW][C]37[/C][C]0.001506[/C][C]0.0104[/C][C]0.495859[/C][/ROW]
[ROW][C]38[/C][C]-0.102099[/C][C]-0.7074[/C][C]0.24138[/C][/ROW]
[ROW][C]39[/C][C]-0.084539[/C][C]-0.5857[/C][C]0.28041[/C][/ROW]
[ROW][C]40[/C][C]0.000325[/C][C]0.0023[/C][C]0.499107[/C][/ROW]
[ROW][C]41[/C][C]-0.041199[/C][C]-0.2854[/C][C]0.388269[/C][/ROW]
[ROW][C]42[/C][C]-0.041308[/C][C]-0.2862[/C][C]0.387981[/C][/ROW]
[ROW][C]43[/C][C]-0.050042[/C][C]-0.3467[/C][C]0.365166[/C][/ROW]
[ROW][C]44[/C][C]0.222822[/C][C]1.5438[/C][C]0.064607[/C][/ROW]
[ROW][C]45[/C][C]-0.026877[/C][C]-0.1862[/C][C]0.426532[/C][/ROW]
[ROW][C]46[/C][C]-0.089405[/C][C]-0.6194[/C][C]0.269287[/C][/ROW]
[ROW][C]47[/C][C]0.056098[/C][C]0.3887[/C][C]0.349624[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63419&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63419&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
10.8140225.63970
2-0.023274-0.16130.436286
30.0241460.16730.433923
4-0.087466-0.6060.273691
5-0.09595-0.66480.254693
60.0730940.50640.307444
70.0672050.46560.3218
8-0.07163-0.49630.310986
9-0.08481-0.58760.279785
10-0.069483-0.48140.316214
11-0.026447-0.18320.427695
120.0112590.0780.469073
130.0687550.47630.317995
14-0.064867-0.44940.327579
150.1074220.74420.230178
160.0057330.03970.484241
170.0377240.26140.397466
18-0.14322-0.99230.163024
19-0.031386-0.21750.414389
200.1066140.73860.23186
210.0125270.08680.465599
220.008030.05560.477932
23-0.013598-0.09420.462667
240.013540.09380.462827
25-0.065075-0.45090.327063
260.005310.03680.485403
270.0655580.45420.325867
28-0.074548-0.51650.303943
290.0158960.11010.456382
30-0.111719-0.7740.221359
31-0.019372-0.13420.446898
32-0.048872-0.33860.368197
33-0.068621-0.47540.318322
340.0013820.00960.4962
35-0.025997-0.18010.428912
36-0.013527-0.09370.462862
370.0015060.01040.495859
38-0.102099-0.70740.24138
39-0.084539-0.58570.28041
400.0003250.00230.499107
41-0.041199-0.28540.388269
42-0.041308-0.28620.387981
43-0.050042-0.34670.365166
440.2228221.54380.064607
45-0.026877-0.18620.426532
46-0.089405-0.61940.269287
470.0560980.38870.349624
48NANANA



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