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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 computationTue, 07 Dec 2010 08:56:39 +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/Dec/07/t1291712129tal73e7e3cb7xmb.htm/, Retrieved Fri, 03 May 2024 16:58:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106031, Retrieved Fri, 03 May 2024 16:58:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139
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] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [WS9 ACF 1] [2010-12-07 08:47:05] [07a238a5afc23eb944f8545182f29d5a]
-   P       [(Partial) Autocorrelation Function] [WS9 ACF 3 d=1 D=0...] [2010-12-07 08:52:55] [07a238a5afc23eb944f8545182f29d5a]
-   P           [(Partial) Autocorrelation Function] [WS9 ACF 4 d=D=1 (...] [2010-12-07 08:56:39] [67e3c2d70de1dbb070b545ca6c893d5e] [Current]
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Dataseries X:
562.325
560.854
555.332
543.599
536.662
542.722
593.530
610.763
612.613
611.324
594.167
595.454
590.865
589.379
584.428
573.100
567.456
569.028
620.735
628.884
628.232
612.117
595.404
597.141
593.408
590.072
579.799
574.205
572.775
572.942
619.567
625.809
619.916
587.625
565.742
557.274
560.576
548.854
531.673
525.919
511.038
498.662
555.362
564.591
541.657
527.070
509.846
514.258
516.922
507.561
492.622
490.243
469.357
477.580
528.379
533.590
517.945
506.174
501.866
516.141
528.222
532.638
536.322
536.535
523.597
536.214
586.570
596.594
580.523
564.478
557.560
575.093




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106031&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106031&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106031&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1430551.09880.138154
20.2598551.9960.025279
30.3216672.47080.008195
40.2160451.65950.051164
50.0917070.70440.241972
60.1594751.2250.112731
70.0169690.13030.448369
80.1237440.95050.172869
90.0448310.34440.365903
10-0.077516-0.59540.276921
110.2969812.28120.013083
12-0.055072-0.4230.336911
13-0.012613-0.09690.461573
140.1792321.37670.086902
150.0721340.55410.290812
160.00290.02230.491152
170.058320.4480.327909
18-0.062481-0.47990.316526
190.0394440.3030.381486
20-0.039222-0.30130.382133
21-0.180633-1.38750.085259
22-0.040046-0.30760.379736
23-0.11445-0.87910.191455
24-0.213424-1.63930.053232
25-0.098435-0.75610.226302
26-0.164383-1.26270.105841
27-0.222735-1.71090.04618
28-0.171957-1.32080.095829
29-0.093886-0.72110.236833
30-0.116446-0.89440.187361
31-0.020356-0.15640.438142
32-0.141554-1.08730.140664
33-0.000933-0.00720.497153
34-0.043629-0.33510.369361
350.0144620.11110.455963
36-0.040451-0.31070.378558
37-0.043843-0.33680.368744
38-0.059831-0.45960.323756
39-0.083626-0.64230.26157
40-0.075945-0.58330.280942
41-0.131483-1.00990.158324
42-0.075191-0.57750.282883
43-0.078603-0.60380.274159
44-0.028927-0.22220.412467
45-0.042499-0.32640.372624
46-0.027454-0.21090.416856
47-0.007174-0.05510.478122
480.0038170.02930.488353

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143055 & 1.0988 & 0.138154 \tabularnewline
2 & 0.259855 & 1.996 & 0.025279 \tabularnewline
3 & 0.321667 & 2.4708 & 0.008195 \tabularnewline
4 & 0.216045 & 1.6595 & 0.051164 \tabularnewline
5 & 0.091707 & 0.7044 & 0.241972 \tabularnewline
6 & 0.159475 & 1.225 & 0.112731 \tabularnewline
7 & 0.016969 & 0.1303 & 0.448369 \tabularnewline
8 & 0.123744 & 0.9505 & 0.172869 \tabularnewline
9 & 0.044831 & 0.3444 & 0.365903 \tabularnewline
10 & -0.077516 & -0.5954 & 0.276921 \tabularnewline
11 & 0.296981 & 2.2812 & 0.013083 \tabularnewline
12 & -0.055072 & -0.423 & 0.336911 \tabularnewline
13 & -0.012613 & -0.0969 & 0.461573 \tabularnewline
14 & 0.179232 & 1.3767 & 0.086902 \tabularnewline
15 & 0.072134 & 0.5541 & 0.290812 \tabularnewline
16 & 0.0029 & 0.0223 & 0.491152 \tabularnewline
17 & 0.05832 & 0.448 & 0.327909 \tabularnewline
18 & -0.062481 & -0.4799 & 0.316526 \tabularnewline
19 & 0.039444 & 0.303 & 0.381486 \tabularnewline
20 & -0.039222 & -0.3013 & 0.382133 \tabularnewline
21 & -0.180633 & -1.3875 & 0.085259 \tabularnewline
22 & -0.040046 & -0.3076 & 0.379736 \tabularnewline
23 & -0.11445 & -0.8791 & 0.191455 \tabularnewline
24 & -0.213424 & -1.6393 & 0.053232 \tabularnewline
25 & -0.098435 & -0.7561 & 0.226302 \tabularnewline
26 & -0.164383 & -1.2627 & 0.105841 \tabularnewline
27 & -0.222735 & -1.7109 & 0.04618 \tabularnewline
28 & -0.171957 & -1.3208 & 0.095829 \tabularnewline
29 & -0.093886 & -0.7211 & 0.236833 \tabularnewline
30 & -0.116446 & -0.8944 & 0.187361 \tabularnewline
31 & -0.020356 & -0.1564 & 0.438142 \tabularnewline
32 & -0.141554 & -1.0873 & 0.140664 \tabularnewline
33 & -0.000933 & -0.0072 & 0.497153 \tabularnewline
34 & -0.043629 & -0.3351 & 0.369361 \tabularnewline
35 & 0.014462 & 0.1111 & 0.455963 \tabularnewline
36 & -0.040451 & -0.3107 & 0.378558 \tabularnewline
37 & -0.043843 & -0.3368 & 0.368744 \tabularnewline
38 & -0.059831 & -0.4596 & 0.323756 \tabularnewline
39 & -0.083626 & -0.6423 & 0.26157 \tabularnewline
40 & -0.075945 & -0.5833 & 0.280942 \tabularnewline
41 & -0.131483 & -1.0099 & 0.158324 \tabularnewline
42 & -0.075191 & -0.5775 & 0.282883 \tabularnewline
43 & -0.078603 & -0.6038 & 0.274159 \tabularnewline
44 & -0.028927 & -0.2222 & 0.412467 \tabularnewline
45 & -0.042499 & -0.3264 & 0.372624 \tabularnewline
46 & -0.027454 & -0.2109 & 0.416856 \tabularnewline
47 & -0.007174 & -0.0551 & 0.478122 \tabularnewline
48 & 0.003817 & 0.0293 & 0.488353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106031&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]0.143055[/C][C]1.0988[/C][C]0.138154[/C][/ROW]
[ROW][C]2[/C][C]0.259855[/C][C]1.996[/C][C]0.025279[/C][/ROW]
[ROW][C]3[/C][C]0.321667[/C][C]2.4708[/C][C]0.008195[/C][/ROW]
[ROW][C]4[/C][C]0.216045[/C][C]1.6595[/C][C]0.051164[/C][/ROW]
[ROW][C]5[/C][C]0.091707[/C][C]0.7044[/C][C]0.241972[/C][/ROW]
[ROW][C]6[/C][C]0.159475[/C][C]1.225[/C][C]0.112731[/C][/ROW]
[ROW][C]7[/C][C]0.016969[/C][C]0.1303[/C][C]0.448369[/C][/ROW]
[ROW][C]8[/C][C]0.123744[/C][C]0.9505[/C][C]0.172869[/C][/ROW]
[ROW][C]9[/C][C]0.044831[/C][C]0.3444[/C][C]0.365903[/C][/ROW]
[ROW][C]10[/C][C]-0.077516[/C][C]-0.5954[/C][C]0.276921[/C][/ROW]
[ROW][C]11[/C][C]0.296981[/C][C]2.2812[/C][C]0.013083[/C][/ROW]
[ROW][C]12[/C][C]-0.055072[/C][C]-0.423[/C][C]0.336911[/C][/ROW]
[ROW][C]13[/C][C]-0.012613[/C][C]-0.0969[/C][C]0.461573[/C][/ROW]
[ROW][C]14[/C][C]0.179232[/C][C]1.3767[/C][C]0.086902[/C][/ROW]
[ROW][C]15[/C][C]0.072134[/C][C]0.5541[/C][C]0.290812[/C][/ROW]
[ROW][C]16[/C][C]0.0029[/C][C]0.0223[/C][C]0.491152[/C][/ROW]
[ROW][C]17[/C][C]0.05832[/C][C]0.448[/C][C]0.327909[/C][/ROW]
[ROW][C]18[/C][C]-0.062481[/C][C]-0.4799[/C][C]0.316526[/C][/ROW]
[ROW][C]19[/C][C]0.039444[/C][C]0.303[/C][C]0.381486[/C][/ROW]
[ROW][C]20[/C][C]-0.039222[/C][C]-0.3013[/C][C]0.382133[/C][/ROW]
[ROW][C]21[/C][C]-0.180633[/C][C]-1.3875[/C][C]0.085259[/C][/ROW]
[ROW][C]22[/C][C]-0.040046[/C][C]-0.3076[/C][C]0.379736[/C][/ROW]
[ROW][C]23[/C][C]-0.11445[/C][C]-0.8791[/C][C]0.191455[/C][/ROW]
[ROW][C]24[/C][C]-0.213424[/C][C]-1.6393[/C][C]0.053232[/C][/ROW]
[ROW][C]25[/C][C]-0.098435[/C][C]-0.7561[/C][C]0.226302[/C][/ROW]
[ROW][C]26[/C][C]-0.164383[/C][C]-1.2627[/C][C]0.105841[/C][/ROW]
[ROW][C]27[/C][C]-0.222735[/C][C]-1.7109[/C][C]0.04618[/C][/ROW]
[ROW][C]28[/C][C]-0.171957[/C][C]-1.3208[/C][C]0.095829[/C][/ROW]
[ROW][C]29[/C][C]-0.093886[/C][C]-0.7211[/C][C]0.236833[/C][/ROW]
[ROW][C]30[/C][C]-0.116446[/C][C]-0.8944[/C][C]0.187361[/C][/ROW]
[ROW][C]31[/C][C]-0.020356[/C][C]-0.1564[/C][C]0.438142[/C][/ROW]
[ROW][C]32[/C][C]-0.141554[/C][C]-1.0873[/C][C]0.140664[/C][/ROW]
[ROW][C]33[/C][C]-0.000933[/C][C]-0.0072[/C][C]0.497153[/C][/ROW]
[ROW][C]34[/C][C]-0.043629[/C][C]-0.3351[/C][C]0.369361[/C][/ROW]
[ROW][C]35[/C][C]0.014462[/C][C]0.1111[/C][C]0.455963[/C][/ROW]
[ROW][C]36[/C][C]-0.040451[/C][C]-0.3107[/C][C]0.378558[/C][/ROW]
[ROW][C]37[/C][C]-0.043843[/C][C]-0.3368[/C][C]0.368744[/C][/ROW]
[ROW][C]38[/C][C]-0.059831[/C][C]-0.4596[/C][C]0.323756[/C][/ROW]
[ROW][C]39[/C][C]-0.083626[/C][C]-0.6423[/C][C]0.26157[/C][/ROW]
[ROW][C]40[/C][C]-0.075945[/C][C]-0.5833[/C][C]0.280942[/C][/ROW]
[ROW][C]41[/C][C]-0.131483[/C][C]-1.0099[/C][C]0.158324[/C][/ROW]
[ROW][C]42[/C][C]-0.075191[/C][C]-0.5775[/C][C]0.282883[/C][/ROW]
[ROW][C]43[/C][C]-0.078603[/C][C]-0.6038[/C][C]0.274159[/C][/ROW]
[ROW][C]44[/C][C]-0.028927[/C][C]-0.2222[/C][C]0.412467[/C][/ROW]
[ROW][C]45[/C][C]-0.042499[/C][C]-0.3264[/C][C]0.372624[/C][/ROW]
[ROW][C]46[/C][C]-0.027454[/C][C]-0.2109[/C][C]0.416856[/C][/ROW]
[ROW][C]47[/C][C]-0.007174[/C][C]-0.0551[/C][C]0.478122[/C][/ROW]
[ROW][C]48[/C][C]0.003817[/C][C]0.0293[/C][C]0.488353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106031&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106031&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
10.1430551.09880.138154
20.2598551.9960.025279
30.3216672.47080.008195
40.2160451.65950.051164
50.0917070.70440.241972
60.1594751.2250.112731
70.0169690.13030.448369
80.1237440.95050.172869
90.0448310.34440.365903
10-0.077516-0.59540.276921
110.2969812.28120.013083
12-0.055072-0.4230.336911
13-0.012613-0.09690.461573
140.1792321.37670.086902
150.0721340.55410.290812
160.00290.02230.491152
170.058320.4480.327909
18-0.062481-0.47990.316526
190.0394440.3030.381486
20-0.039222-0.30130.382133
21-0.180633-1.38750.085259
22-0.040046-0.30760.379736
23-0.11445-0.87910.191455
24-0.213424-1.63930.053232
25-0.098435-0.75610.226302
26-0.164383-1.26270.105841
27-0.222735-1.71090.04618
28-0.171957-1.32080.095829
29-0.093886-0.72110.236833
30-0.116446-0.89440.187361
31-0.020356-0.15640.438142
32-0.141554-1.08730.140664
33-0.000933-0.00720.497153
34-0.043629-0.33510.369361
350.0144620.11110.455963
36-0.040451-0.31070.378558
37-0.043843-0.33680.368744
38-0.059831-0.45960.323756
39-0.083626-0.64230.26157
40-0.075945-0.58330.280942
41-0.131483-1.00990.158324
42-0.075191-0.57750.282883
43-0.078603-0.60380.274159
44-0.028927-0.22220.412467
45-0.042499-0.32640.372624
46-0.027454-0.21090.416856
47-0.007174-0.05510.478122
480.0038170.02930.488353







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1430551.09880.138154
20.2443921.87720.032718
30.2807912.15680.017554
40.1267790.97380.167064
5-0.070739-0.54340.294465
6-0.002597-0.020.492075
7-0.10704-0.82220.20714
80.0742190.57010.285391
90.0177050.1360.446143
10-0.130546-1.00270.160041
110.32482.49480.00771
12-0.109614-0.8420.201604
13-0.071688-0.55060.291977
140.1143340.87820.191694
150.0121130.0930.463093
160.0181750.13960.444725
17-0.103452-0.79460.215007
18-0.098969-0.76020.225083
190.0203390.15620.438192
20-0.04909-0.37710.353737
21-0.080847-0.6210.268496
22-0.137079-1.05290.148335
230.0080320.06170.475507
24-0.043137-0.33130.370782
25-0.103071-0.79170.215853
26-0.056214-0.43180.333734
27-0.102326-0.7860.217512
28-0.080583-0.6190.269159
290.1276380.98040.165444
30-0.017471-0.13420.446853
310.1201830.92310.179845
32-0.012886-0.0990.460746
330.0127260.09770.461232
34-0.033439-0.25680.399095
350.1287920.98930.163286
360.0342250.26290.396778
37-0.091207-0.70060.243161
380.0137340.10550.458171
39-0.069925-0.53710.296607
40-0.060914-0.46790.320794
41-0.019908-0.15290.439492
42-0.059372-0.4560.325016
430.0763340.58630.279944
440.0067270.05170.479483
45-0.016662-0.1280.449299
46-0.126088-0.96850.168374
470.0036260.02790.488936
480.0089010.06840.472862

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143055 & 1.0988 & 0.138154 \tabularnewline
2 & 0.244392 & 1.8772 & 0.032718 \tabularnewline
3 & 0.280791 & 2.1568 & 0.017554 \tabularnewline
4 & 0.126779 & 0.9738 & 0.167064 \tabularnewline
5 & -0.070739 & -0.5434 & 0.294465 \tabularnewline
6 & -0.002597 & -0.02 & 0.492075 \tabularnewline
7 & -0.10704 & -0.8222 & 0.20714 \tabularnewline
8 & 0.074219 & 0.5701 & 0.285391 \tabularnewline
9 & 0.017705 & 0.136 & 0.446143 \tabularnewline
10 & -0.130546 & -1.0027 & 0.160041 \tabularnewline
11 & 0.3248 & 2.4948 & 0.00771 \tabularnewline
12 & -0.109614 & -0.842 & 0.201604 \tabularnewline
13 & -0.071688 & -0.5506 & 0.291977 \tabularnewline
14 & 0.114334 & 0.8782 & 0.191694 \tabularnewline
15 & 0.012113 & 0.093 & 0.463093 \tabularnewline
16 & 0.018175 & 0.1396 & 0.444725 \tabularnewline
17 & -0.103452 & -0.7946 & 0.215007 \tabularnewline
18 & -0.098969 & -0.7602 & 0.225083 \tabularnewline
19 & 0.020339 & 0.1562 & 0.438192 \tabularnewline
20 & -0.04909 & -0.3771 & 0.353737 \tabularnewline
21 & -0.080847 & -0.621 & 0.268496 \tabularnewline
22 & -0.137079 & -1.0529 & 0.148335 \tabularnewline
23 & 0.008032 & 0.0617 & 0.475507 \tabularnewline
24 & -0.043137 & -0.3313 & 0.370782 \tabularnewline
25 & -0.103071 & -0.7917 & 0.215853 \tabularnewline
26 & -0.056214 & -0.4318 & 0.333734 \tabularnewline
27 & -0.102326 & -0.786 & 0.217512 \tabularnewline
28 & -0.080583 & -0.619 & 0.269159 \tabularnewline
29 & 0.127638 & 0.9804 & 0.165444 \tabularnewline
30 & -0.017471 & -0.1342 & 0.446853 \tabularnewline
31 & 0.120183 & 0.9231 & 0.179845 \tabularnewline
32 & -0.012886 & -0.099 & 0.460746 \tabularnewline
33 & 0.012726 & 0.0977 & 0.461232 \tabularnewline
34 & -0.033439 & -0.2568 & 0.399095 \tabularnewline
35 & 0.128792 & 0.9893 & 0.163286 \tabularnewline
36 & 0.034225 & 0.2629 & 0.396778 \tabularnewline
37 & -0.091207 & -0.7006 & 0.243161 \tabularnewline
38 & 0.013734 & 0.1055 & 0.458171 \tabularnewline
39 & -0.069925 & -0.5371 & 0.296607 \tabularnewline
40 & -0.060914 & -0.4679 & 0.320794 \tabularnewline
41 & -0.019908 & -0.1529 & 0.439492 \tabularnewline
42 & -0.059372 & -0.456 & 0.325016 \tabularnewline
43 & 0.076334 & 0.5863 & 0.279944 \tabularnewline
44 & 0.006727 & 0.0517 & 0.479483 \tabularnewline
45 & -0.016662 & -0.128 & 0.449299 \tabularnewline
46 & -0.126088 & -0.9685 & 0.168374 \tabularnewline
47 & 0.003626 & 0.0279 & 0.488936 \tabularnewline
48 & 0.008901 & 0.0684 & 0.472862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106031&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]0.143055[/C][C]1.0988[/C][C]0.138154[/C][/ROW]
[ROW][C]2[/C][C]0.244392[/C][C]1.8772[/C][C]0.032718[/C][/ROW]
[ROW][C]3[/C][C]0.280791[/C][C]2.1568[/C][C]0.017554[/C][/ROW]
[ROW][C]4[/C][C]0.126779[/C][C]0.9738[/C][C]0.167064[/C][/ROW]
[ROW][C]5[/C][C]-0.070739[/C][C]-0.5434[/C][C]0.294465[/C][/ROW]
[ROW][C]6[/C][C]-0.002597[/C][C]-0.02[/C][C]0.492075[/C][/ROW]
[ROW][C]7[/C][C]-0.10704[/C][C]-0.8222[/C][C]0.20714[/C][/ROW]
[ROW][C]8[/C][C]0.074219[/C][C]0.5701[/C][C]0.285391[/C][/ROW]
[ROW][C]9[/C][C]0.017705[/C][C]0.136[/C][C]0.446143[/C][/ROW]
[ROW][C]10[/C][C]-0.130546[/C][C]-1.0027[/C][C]0.160041[/C][/ROW]
[ROW][C]11[/C][C]0.3248[/C][C]2.4948[/C][C]0.00771[/C][/ROW]
[ROW][C]12[/C][C]-0.109614[/C][C]-0.842[/C][C]0.201604[/C][/ROW]
[ROW][C]13[/C][C]-0.071688[/C][C]-0.5506[/C][C]0.291977[/C][/ROW]
[ROW][C]14[/C][C]0.114334[/C][C]0.8782[/C][C]0.191694[/C][/ROW]
[ROW][C]15[/C][C]0.012113[/C][C]0.093[/C][C]0.463093[/C][/ROW]
[ROW][C]16[/C][C]0.018175[/C][C]0.1396[/C][C]0.444725[/C][/ROW]
[ROW][C]17[/C][C]-0.103452[/C][C]-0.7946[/C][C]0.215007[/C][/ROW]
[ROW][C]18[/C][C]-0.098969[/C][C]-0.7602[/C][C]0.225083[/C][/ROW]
[ROW][C]19[/C][C]0.020339[/C][C]0.1562[/C][C]0.438192[/C][/ROW]
[ROW][C]20[/C][C]-0.04909[/C][C]-0.3771[/C][C]0.353737[/C][/ROW]
[ROW][C]21[/C][C]-0.080847[/C][C]-0.621[/C][C]0.268496[/C][/ROW]
[ROW][C]22[/C][C]-0.137079[/C][C]-1.0529[/C][C]0.148335[/C][/ROW]
[ROW][C]23[/C][C]0.008032[/C][C]0.0617[/C][C]0.475507[/C][/ROW]
[ROW][C]24[/C][C]-0.043137[/C][C]-0.3313[/C][C]0.370782[/C][/ROW]
[ROW][C]25[/C][C]-0.103071[/C][C]-0.7917[/C][C]0.215853[/C][/ROW]
[ROW][C]26[/C][C]-0.056214[/C][C]-0.4318[/C][C]0.333734[/C][/ROW]
[ROW][C]27[/C][C]-0.102326[/C][C]-0.786[/C][C]0.217512[/C][/ROW]
[ROW][C]28[/C][C]-0.080583[/C][C]-0.619[/C][C]0.269159[/C][/ROW]
[ROW][C]29[/C][C]0.127638[/C][C]0.9804[/C][C]0.165444[/C][/ROW]
[ROW][C]30[/C][C]-0.017471[/C][C]-0.1342[/C][C]0.446853[/C][/ROW]
[ROW][C]31[/C][C]0.120183[/C][C]0.9231[/C][C]0.179845[/C][/ROW]
[ROW][C]32[/C][C]-0.012886[/C][C]-0.099[/C][C]0.460746[/C][/ROW]
[ROW][C]33[/C][C]0.012726[/C][C]0.0977[/C][C]0.461232[/C][/ROW]
[ROW][C]34[/C][C]-0.033439[/C][C]-0.2568[/C][C]0.399095[/C][/ROW]
[ROW][C]35[/C][C]0.128792[/C][C]0.9893[/C][C]0.163286[/C][/ROW]
[ROW][C]36[/C][C]0.034225[/C][C]0.2629[/C][C]0.396778[/C][/ROW]
[ROW][C]37[/C][C]-0.091207[/C][C]-0.7006[/C][C]0.243161[/C][/ROW]
[ROW][C]38[/C][C]0.013734[/C][C]0.1055[/C][C]0.458171[/C][/ROW]
[ROW][C]39[/C][C]-0.069925[/C][C]-0.5371[/C][C]0.296607[/C][/ROW]
[ROW][C]40[/C][C]-0.060914[/C][C]-0.4679[/C][C]0.320794[/C][/ROW]
[ROW][C]41[/C][C]-0.019908[/C][C]-0.1529[/C][C]0.439492[/C][/ROW]
[ROW][C]42[/C][C]-0.059372[/C][C]-0.456[/C][C]0.325016[/C][/ROW]
[ROW][C]43[/C][C]0.076334[/C][C]0.5863[/C][C]0.279944[/C][/ROW]
[ROW][C]44[/C][C]0.006727[/C][C]0.0517[/C][C]0.479483[/C][/ROW]
[ROW][C]45[/C][C]-0.016662[/C][C]-0.128[/C][C]0.449299[/C][/ROW]
[ROW][C]46[/C][C]-0.126088[/C][C]-0.9685[/C][C]0.168374[/C][/ROW]
[ROW][C]47[/C][C]0.003626[/C][C]0.0279[/C][C]0.488936[/C][/ROW]
[ROW][C]48[/C][C]0.008901[/C][C]0.0684[/C][C]0.472862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106031&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106031&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
10.1430551.09880.138154
20.2443921.87720.032718
30.2807912.15680.017554
40.1267790.97380.167064
5-0.070739-0.54340.294465
6-0.002597-0.020.492075
7-0.10704-0.82220.20714
80.0742190.57010.285391
90.0177050.1360.446143
10-0.130546-1.00270.160041
110.32482.49480.00771
12-0.109614-0.8420.201604
13-0.071688-0.55060.291977
140.1143340.87820.191694
150.0121130.0930.463093
160.0181750.13960.444725
17-0.103452-0.79460.215007
18-0.098969-0.76020.225083
190.0203390.15620.438192
20-0.04909-0.37710.353737
21-0.080847-0.6210.268496
22-0.137079-1.05290.148335
230.0080320.06170.475507
24-0.043137-0.33130.370782
25-0.103071-0.79170.215853
26-0.056214-0.43180.333734
27-0.102326-0.7860.217512
28-0.080583-0.6190.269159
290.1276380.98040.165444
30-0.017471-0.13420.446853
310.1201830.92310.179845
32-0.012886-0.0990.460746
330.0127260.09770.461232
34-0.033439-0.25680.399095
350.1287920.98930.163286
360.0342250.26290.396778
37-0.091207-0.70060.243161
380.0137340.10550.458171
39-0.069925-0.53710.296607
40-0.060914-0.46790.320794
41-0.019908-0.15290.439492
42-0.059372-0.4560.325016
430.0763340.58630.279944
440.0067270.05170.479483
45-0.016662-0.1280.449299
46-0.126088-0.96850.168374
470.0036260.02790.488936
480.0089010.06840.472862



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