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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 computationSun, 19 Dec 2010 14:23:35 +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/19/t1292768502hcf7i3cr69yy0hw.htm/, Retrieved Sat, 04 May 2024 21:09:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112422, Retrieved Sat, 04 May 2024 21:09:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
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] [Workshop 9, Stati...] [2010-12-03 13:18:27] [d946de7cca328fbcf207448a112523ab]
-   PD        [(Partial) Autocorrelation Function] [Autocorrelatiefun...] [2010-12-19 14:23:35] [99c051a77087383325372ff23bc64341] [Current]
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Dataseries X:
631.923
654.294
671.833
586.840
600.969
625.568
558.110
630.577
628.654
603.184
656.255
600.730
670.326
678.423
641.502
625.311
628.177
589.767
582.471
636.248
599.885
621.694
637.406
595.994
696.308
674.201
648.861
649.605
672.392
598.396
613.177
638.104
615.632
634.465
638.686
604.243
706.669
677.185
644.328
664.825
605.707
600.136
612.166
599.659
634.210
618.234
613.576
627.200
668.973
651.479
619.661
644.260
579.936
601.752
595.376
588.902
634.341
594.305
606.200
610.926
633.685
639.696
659.451
593.248
606.677
599.434
569.578
629.873
613.438
604.172
658.328
612.633
707.372
739.770
777.535
685.030
730.234
714.154
630.872
719.492
677.023
679.272
718.317
645.672




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112422&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112422&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112422&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4716324.32262.1e-05
20.4353233.98987e-05
30.4259683.90419.5e-05
40.060330.55290.290888
50.1395731.27920.102174
60.0968260.88740.188693
7-0.042997-0.39410.347263
8-0.009589-0.08790.465089
90.0373410.34220.366515
10-0.052043-0.4770.317306
110.0872650.79980.213043
120.2518642.30840.011718
13-0.023008-0.21090.416751
140.0507640.46530.321475
15-0.077946-0.71440.238485
16-0.245162-2.2470.013633
17-0.129931-1.19080.118537
18-0.222404-2.03840.02233
19-0.261056-2.39260.00948
20-0.137299-1.25840.105872
21-0.196035-1.79670.03799
22-0.163445-1.4980.068942
230.0621210.56930.28532
240.0194660.17840.429415
250.0045510.04170.483415
260.0553380.50720.306677
27-0.160614-1.4720.072372
28-0.126331-1.15780.125105
29-0.102611-0.94040.174842
30-0.21955-2.01220.023701
31-0.116719-1.06970.143898
32-0.103257-0.94640.173338
33-0.153617-1.40790.081422
340.0350180.32090.374525
350.0685590.62840.265738
360.0982230.90020.185287
370.1541161.41250.08075
380.0692940.63510.263549
39-0.034471-0.31590.376418
400.0237010.21720.41428
41-0.041355-0.3790.352814
42-0.069125-0.63350.264052
430.0506760.46440.321764
44-0.041925-0.38420.350884
450.0009450.00870.496556
460.1569011.4380.077071
470.0361270.33110.370694
480.1770561.62270.054196

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.471632 & 4.3226 & 2.1e-05 \tabularnewline
2 & 0.435323 & 3.9898 & 7e-05 \tabularnewline
3 & 0.425968 & 3.9041 & 9.5e-05 \tabularnewline
4 & 0.06033 & 0.5529 & 0.290888 \tabularnewline
5 & 0.139573 & 1.2792 & 0.102174 \tabularnewline
6 & 0.096826 & 0.8874 & 0.188693 \tabularnewline
7 & -0.042997 & -0.3941 & 0.347263 \tabularnewline
8 & -0.009589 & -0.0879 & 0.465089 \tabularnewline
9 & 0.037341 & 0.3422 & 0.366515 \tabularnewline
10 & -0.052043 & -0.477 & 0.317306 \tabularnewline
11 & 0.087265 & 0.7998 & 0.213043 \tabularnewline
12 & 0.251864 & 2.3084 & 0.011718 \tabularnewline
13 & -0.023008 & -0.2109 & 0.416751 \tabularnewline
14 & 0.050764 & 0.4653 & 0.321475 \tabularnewline
15 & -0.077946 & -0.7144 & 0.238485 \tabularnewline
16 & -0.245162 & -2.247 & 0.013633 \tabularnewline
17 & -0.129931 & -1.1908 & 0.118537 \tabularnewline
18 & -0.222404 & -2.0384 & 0.02233 \tabularnewline
19 & -0.261056 & -2.3926 & 0.00948 \tabularnewline
20 & -0.137299 & -1.2584 & 0.105872 \tabularnewline
21 & -0.196035 & -1.7967 & 0.03799 \tabularnewline
22 & -0.163445 & -1.498 & 0.068942 \tabularnewline
23 & 0.062121 & 0.5693 & 0.28532 \tabularnewline
24 & 0.019466 & 0.1784 & 0.429415 \tabularnewline
25 & 0.004551 & 0.0417 & 0.483415 \tabularnewline
26 & 0.055338 & 0.5072 & 0.306677 \tabularnewline
27 & -0.160614 & -1.472 & 0.072372 \tabularnewline
28 & -0.126331 & -1.1578 & 0.125105 \tabularnewline
29 & -0.102611 & -0.9404 & 0.174842 \tabularnewline
30 & -0.21955 & -2.0122 & 0.023701 \tabularnewline
31 & -0.116719 & -1.0697 & 0.143898 \tabularnewline
32 & -0.103257 & -0.9464 & 0.173338 \tabularnewline
33 & -0.153617 & -1.4079 & 0.081422 \tabularnewline
34 & 0.035018 & 0.3209 & 0.374525 \tabularnewline
35 & 0.068559 & 0.6284 & 0.265738 \tabularnewline
36 & 0.098223 & 0.9002 & 0.185287 \tabularnewline
37 & 0.154116 & 1.4125 & 0.08075 \tabularnewline
38 & 0.069294 & 0.6351 & 0.263549 \tabularnewline
39 & -0.034471 & -0.3159 & 0.376418 \tabularnewline
40 & 0.023701 & 0.2172 & 0.41428 \tabularnewline
41 & -0.041355 & -0.379 & 0.352814 \tabularnewline
42 & -0.069125 & -0.6335 & 0.264052 \tabularnewline
43 & 0.050676 & 0.4644 & 0.321764 \tabularnewline
44 & -0.041925 & -0.3842 & 0.350884 \tabularnewline
45 & 0.000945 & 0.0087 & 0.496556 \tabularnewline
46 & 0.156901 & 1.438 & 0.077071 \tabularnewline
47 & 0.036127 & 0.3311 & 0.370694 \tabularnewline
48 & 0.177056 & 1.6227 & 0.054196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112422&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]0.471632[/C][C]4.3226[/C][C]2.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.435323[/C][C]3.9898[/C][C]7e-05[/C][/ROW]
[ROW][C]3[/C][C]0.425968[/C][C]3.9041[/C][C]9.5e-05[/C][/ROW]
[ROW][C]4[/C][C]0.06033[/C][C]0.5529[/C][C]0.290888[/C][/ROW]
[ROW][C]5[/C][C]0.139573[/C][C]1.2792[/C][C]0.102174[/C][/ROW]
[ROW][C]6[/C][C]0.096826[/C][C]0.8874[/C][C]0.188693[/C][/ROW]
[ROW][C]7[/C][C]-0.042997[/C][C]-0.3941[/C][C]0.347263[/C][/ROW]
[ROW][C]8[/C][C]-0.009589[/C][C]-0.0879[/C][C]0.465089[/C][/ROW]
[ROW][C]9[/C][C]0.037341[/C][C]0.3422[/C][C]0.366515[/C][/ROW]
[ROW][C]10[/C][C]-0.052043[/C][C]-0.477[/C][C]0.317306[/C][/ROW]
[ROW][C]11[/C][C]0.087265[/C][C]0.7998[/C][C]0.213043[/C][/ROW]
[ROW][C]12[/C][C]0.251864[/C][C]2.3084[/C][C]0.011718[/C][/ROW]
[ROW][C]13[/C][C]-0.023008[/C][C]-0.2109[/C][C]0.416751[/C][/ROW]
[ROW][C]14[/C][C]0.050764[/C][C]0.4653[/C][C]0.321475[/C][/ROW]
[ROW][C]15[/C][C]-0.077946[/C][C]-0.7144[/C][C]0.238485[/C][/ROW]
[ROW][C]16[/C][C]-0.245162[/C][C]-2.247[/C][C]0.013633[/C][/ROW]
[ROW][C]17[/C][C]-0.129931[/C][C]-1.1908[/C][C]0.118537[/C][/ROW]
[ROW][C]18[/C][C]-0.222404[/C][C]-2.0384[/C][C]0.02233[/C][/ROW]
[ROW][C]19[/C][C]-0.261056[/C][C]-2.3926[/C][C]0.00948[/C][/ROW]
[ROW][C]20[/C][C]-0.137299[/C][C]-1.2584[/C][C]0.105872[/C][/ROW]
[ROW][C]21[/C][C]-0.196035[/C][C]-1.7967[/C][C]0.03799[/C][/ROW]
[ROW][C]22[/C][C]-0.163445[/C][C]-1.498[/C][C]0.068942[/C][/ROW]
[ROW][C]23[/C][C]0.062121[/C][C]0.5693[/C][C]0.28532[/C][/ROW]
[ROW][C]24[/C][C]0.019466[/C][C]0.1784[/C][C]0.429415[/C][/ROW]
[ROW][C]25[/C][C]0.004551[/C][C]0.0417[/C][C]0.483415[/C][/ROW]
[ROW][C]26[/C][C]0.055338[/C][C]0.5072[/C][C]0.306677[/C][/ROW]
[ROW][C]27[/C][C]-0.160614[/C][C]-1.472[/C][C]0.072372[/C][/ROW]
[ROW][C]28[/C][C]-0.126331[/C][C]-1.1578[/C][C]0.125105[/C][/ROW]
[ROW][C]29[/C][C]-0.102611[/C][C]-0.9404[/C][C]0.174842[/C][/ROW]
[ROW][C]30[/C][C]-0.21955[/C][C]-2.0122[/C][C]0.023701[/C][/ROW]
[ROW][C]31[/C][C]-0.116719[/C][C]-1.0697[/C][C]0.143898[/C][/ROW]
[ROW][C]32[/C][C]-0.103257[/C][C]-0.9464[/C][C]0.173338[/C][/ROW]
[ROW][C]33[/C][C]-0.153617[/C][C]-1.4079[/C][C]0.081422[/C][/ROW]
[ROW][C]34[/C][C]0.035018[/C][C]0.3209[/C][C]0.374525[/C][/ROW]
[ROW][C]35[/C][C]0.068559[/C][C]0.6284[/C][C]0.265738[/C][/ROW]
[ROW][C]36[/C][C]0.098223[/C][C]0.9002[/C][C]0.185287[/C][/ROW]
[ROW][C]37[/C][C]0.154116[/C][C]1.4125[/C][C]0.08075[/C][/ROW]
[ROW][C]38[/C][C]0.069294[/C][C]0.6351[/C][C]0.263549[/C][/ROW]
[ROW][C]39[/C][C]-0.034471[/C][C]-0.3159[/C][C]0.376418[/C][/ROW]
[ROW][C]40[/C][C]0.023701[/C][C]0.2172[/C][C]0.41428[/C][/ROW]
[ROW][C]41[/C][C]-0.041355[/C][C]-0.379[/C][C]0.352814[/C][/ROW]
[ROW][C]42[/C][C]-0.069125[/C][C]-0.6335[/C][C]0.264052[/C][/ROW]
[ROW][C]43[/C][C]0.050676[/C][C]0.4644[/C][C]0.321764[/C][/ROW]
[ROW][C]44[/C][C]-0.041925[/C][C]-0.3842[/C][C]0.350884[/C][/ROW]
[ROW][C]45[/C][C]0.000945[/C][C]0.0087[/C][C]0.496556[/C][/ROW]
[ROW][C]46[/C][C]0.156901[/C][C]1.438[/C][C]0.077071[/C][/ROW]
[ROW][C]47[/C][C]0.036127[/C][C]0.3311[/C][C]0.370694[/C][/ROW]
[ROW][C]48[/C][C]0.177056[/C][C]1.6227[/C][C]0.054196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112422&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112422&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
10.4716324.32262.1e-05
20.4353233.98987e-05
30.4259683.90419.5e-05
40.060330.55290.290888
50.1395731.27920.102174
60.0968260.88740.188693
7-0.042997-0.39410.347263
8-0.009589-0.08790.465089
90.0373410.34220.366515
10-0.052043-0.4770.317306
110.0872650.79980.213043
120.2518642.30840.011718
13-0.023008-0.21090.416751
140.0507640.46530.321475
15-0.077946-0.71440.238485
16-0.245162-2.2470.013633
17-0.129931-1.19080.118537
18-0.222404-2.03840.02233
19-0.261056-2.39260.00948
20-0.137299-1.25840.105872
21-0.196035-1.79670.03799
22-0.163445-1.4980.068942
230.0621210.56930.28532
240.0194660.17840.429415
250.0045510.04170.483415
260.0553380.50720.306677
27-0.160614-1.4720.072372
28-0.126331-1.15780.125105
29-0.102611-0.94040.174842
30-0.21955-2.01220.023701
31-0.116719-1.06970.143898
32-0.103257-0.94640.173338
33-0.153617-1.40790.081422
340.0350180.32090.374525
350.0685590.62840.265738
360.0982230.90020.185287
370.1541161.41250.08075
380.0692940.63510.263549
39-0.034471-0.31590.376418
400.0237010.21720.41428
41-0.041355-0.3790.352814
42-0.069125-0.63350.264052
430.0506760.46440.321764
44-0.041925-0.38420.350884
450.0009450.00870.496556
460.1569011.4380.077071
470.0361270.33110.370694
480.1770561.62270.054196







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4716324.32262.1e-05
20.2737862.50930.007009
30.2054021.88250.031613
4-0.358592-3.28650.000741
50.0585450.53660.296491
60.0692130.63430.26379
7-0.021689-0.19880.421456
8-0.124054-1.1370.129391
90.1439131.3190.095379
10-0.02745-0.25160.400989
110.1343981.23180.110734
120.2578422.36320.010215
13-0.33072-3.03110.00162
14-0.200341-1.83620.034936
15-0.177637-1.62810.053628
160.0984560.90240.184722
17-0.013335-0.12220.451509
18-0.029734-0.27250.392946
19-0.116703-1.06960.143932
200.1048190.96070.169734
21-0.009374-0.08590.465871
220.0333060.30530.380464
230.1144111.04860.148686
24-0.116833-1.07080.143666
25-0.054405-0.49860.309672
26-0.071755-0.65760.256283
27-0.057181-0.52410.300803
28-0.012739-0.11680.453667
290.0182870.16760.433651
30-0.059719-0.54730.292799
310.0209480.1920.424107
32-0.022211-0.20360.419591
330.04290.39320.347589
340.1594591.46150.073809
35-0.132081-1.21050.114733
360.0293630.26910.394249
37-0.117952-1.0810.141385
380.0388360.35590.361391
39-0.058732-0.53830.295903
400.0998930.91550.181267
41-0.036491-0.33440.369439
420.0197420.18090.428426
430.0487440.44670.328105
440.0107170.09820.460996
450.0507470.46510.321532
46-0.036376-0.33340.369835
47-0.096948-0.88850.188392
48-0.036444-0.3340.369601

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.471632 & 4.3226 & 2.1e-05 \tabularnewline
2 & 0.273786 & 2.5093 & 0.007009 \tabularnewline
3 & 0.205402 & 1.8825 & 0.031613 \tabularnewline
4 & -0.358592 & -3.2865 & 0.000741 \tabularnewline
5 & 0.058545 & 0.5366 & 0.296491 \tabularnewline
6 & 0.069213 & 0.6343 & 0.26379 \tabularnewline
7 & -0.021689 & -0.1988 & 0.421456 \tabularnewline
8 & -0.124054 & -1.137 & 0.129391 \tabularnewline
9 & 0.143913 & 1.319 & 0.095379 \tabularnewline
10 & -0.02745 & -0.2516 & 0.400989 \tabularnewline
11 & 0.134398 & 1.2318 & 0.110734 \tabularnewline
12 & 0.257842 & 2.3632 & 0.010215 \tabularnewline
13 & -0.33072 & -3.0311 & 0.00162 \tabularnewline
14 & -0.200341 & -1.8362 & 0.034936 \tabularnewline
15 & -0.177637 & -1.6281 & 0.053628 \tabularnewline
16 & 0.098456 & 0.9024 & 0.184722 \tabularnewline
17 & -0.013335 & -0.1222 & 0.451509 \tabularnewline
18 & -0.029734 & -0.2725 & 0.392946 \tabularnewline
19 & -0.116703 & -1.0696 & 0.143932 \tabularnewline
20 & 0.104819 & 0.9607 & 0.169734 \tabularnewline
21 & -0.009374 & -0.0859 & 0.465871 \tabularnewline
22 & 0.033306 & 0.3053 & 0.380464 \tabularnewline
23 & 0.114411 & 1.0486 & 0.148686 \tabularnewline
24 & -0.116833 & -1.0708 & 0.143666 \tabularnewline
25 & -0.054405 & -0.4986 & 0.309672 \tabularnewline
26 & -0.071755 & -0.6576 & 0.256283 \tabularnewline
27 & -0.057181 & -0.5241 & 0.300803 \tabularnewline
28 & -0.012739 & -0.1168 & 0.453667 \tabularnewline
29 & 0.018287 & 0.1676 & 0.433651 \tabularnewline
30 & -0.059719 & -0.5473 & 0.292799 \tabularnewline
31 & 0.020948 & 0.192 & 0.424107 \tabularnewline
32 & -0.022211 & -0.2036 & 0.419591 \tabularnewline
33 & 0.0429 & 0.3932 & 0.347589 \tabularnewline
34 & 0.159459 & 1.4615 & 0.073809 \tabularnewline
35 & -0.132081 & -1.2105 & 0.114733 \tabularnewline
36 & 0.029363 & 0.2691 & 0.394249 \tabularnewline
37 & -0.117952 & -1.081 & 0.141385 \tabularnewline
38 & 0.038836 & 0.3559 & 0.361391 \tabularnewline
39 & -0.058732 & -0.5383 & 0.295903 \tabularnewline
40 & 0.099893 & 0.9155 & 0.181267 \tabularnewline
41 & -0.036491 & -0.3344 & 0.369439 \tabularnewline
42 & 0.019742 & 0.1809 & 0.428426 \tabularnewline
43 & 0.048744 & 0.4467 & 0.328105 \tabularnewline
44 & 0.010717 & 0.0982 & 0.460996 \tabularnewline
45 & 0.050747 & 0.4651 & 0.321532 \tabularnewline
46 & -0.036376 & -0.3334 & 0.369835 \tabularnewline
47 & -0.096948 & -0.8885 & 0.188392 \tabularnewline
48 & -0.036444 & -0.334 & 0.369601 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112422&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]0.471632[/C][C]4.3226[/C][C]2.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.273786[/C][C]2.5093[/C][C]0.007009[/C][/ROW]
[ROW][C]3[/C][C]0.205402[/C][C]1.8825[/C][C]0.031613[/C][/ROW]
[ROW][C]4[/C][C]-0.358592[/C][C]-3.2865[/C][C]0.000741[/C][/ROW]
[ROW][C]5[/C][C]0.058545[/C][C]0.5366[/C][C]0.296491[/C][/ROW]
[ROW][C]6[/C][C]0.069213[/C][C]0.6343[/C][C]0.26379[/C][/ROW]
[ROW][C]7[/C][C]-0.021689[/C][C]-0.1988[/C][C]0.421456[/C][/ROW]
[ROW][C]8[/C][C]-0.124054[/C][C]-1.137[/C][C]0.129391[/C][/ROW]
[ROW][C]9[/C][C]0.143913[/C][C]1.319[/C][C]0.095379[/C][/ROW]
[ROW][C]10[/C][C]-0.02745[/C][C]-0.2516[/C][C]0.400989[/C][/ROW]
[ROW][C]11[/C][C]0.134398[/C][C]1.2318[/C][C]0.110734[/C][/ROW]
[ROW][C]12[/C][C]0.257842[/C][C]2.3632[/C][C]0.010215[/C][/ROW]
[ROW][C]13[/C][C]-0.33072[/C][C]-3.0311[/C][C]0.00162[/C][/ROW]
[ROW][C]14[/C][C]-0.200341[/C][C]-1.8362[/C][C]0.034936[/C][/ROW]
[ROW][C]15[/C][C]-0.177637[/C][C]-1.6281[/C][C]0.053628[/C][/ROW]
[ROW][C]16[/C][C]0.098456[/C][C]0.9024[/C][C]0.184722[/C][/ROW]
[ROW][C]17[/C][C]-0.013335[/C][C]-0.1222[/C][C]0.451509[/C][/ROW]
[ROW][C]18[/C][C]-0.029734[/C][C]-0.2725[/C][C]0.392946[/C][/ROW]
[ROW][C]19[/C][C]-0.116703[/C][C]-1.0696[/C][C]0.143932[/C][/ROW]
[ROW][C]20[/C][C]0.104819[/C][C]0.9607[/C][C]0.169734[/C][/ROW]
[ROW][C]21[/C][C]-0.009374[/C][C]-0.0859[/C][C]0.465871[/C][/ROW]
[ROW][C]22[/C][C]0.033306[/C][C]0.3053[/C][C]0.380464[/C][/ROW]
[ROW][C]23[/C][C]0.114411[/C][C]1.0486[/C][C]0.148686[/C][/ROW]
[ROW][C]24[/C][C]-0.116833[/C][C]-1.0708[/C][C]0.143666[/C][/ROW]
[ROW][C]25[/C][C]-0.054405[/C][C]-0.4986[/C][C]0.309672[/C][/ROW]
[ROW][C]26[/C][C]-0.071755[/C][C]-0.6576[/C][C]0.256283[/C][/ROW]
[ROW][C]27[/C][C]-0.057181[/C][C]-0.5241[/C][C]0.300803[/C][/ROW]
[ROW][C]28[/C][C]-0.012739[/C][C]-0.1168[/C][C]0.453667[/C][/ROW]
[ROW][C]29[/C][C]0.018287[/C][C]0.1676[/C][C]0.433651[/C][/ROW]
[ROW][C]30[/C][C]-0.059719[/C][C]-0.5473[/C][C]0.292799[/C][/ROW]
[ROW][C]31[/C][C]0.020948[/C][C]0.192[/C][C]0.424107[/C][/ROW]
[ROW][C]32[/C][C]-0.022211[/C][C]-0.2036[/C][C]0.419591[/C][/ROW]
[ROW][C]33[/C][C]0.0429[/C][C]0.3932[/C][C]0.347589[/C][/ROW]
[ROW][C]34[/C][C]0.159459[/C][C]1.4615[/C][C]0.073809[/C][/ROW]
[ROW][C]35[/C][C]-0.132081[/C][C]-1.2105[/C][C]0.114733[/C][/ROW]
[ROW][C]36[/C][C]0.029363[/C][C]0.2691[/C][C]0.394249[/C][/ROW]
[ROW][C]37[/C][C]-0.117952[/C][C]-1.081[/C][C]0.141385[/C][/ROW]
[ROW][C]38[/C][C]0.038836[/C][C]0.3559[/C][C]0.361391[/C][/ROW]
[ROW][C]39[/C][C]-0.058732[/C][C]-0.5383[/C][C]0.295903[/C][/ROW]
[ROW][C]40[/C][C]0.099893[/C][C]0.9155[/C][C]0.181267[/C][/ROW]
[ROW][C]41[/C][C]-0.036491[/C][C]-0.3344[/C][C]0.369439[/C][/ROW]
[ROW][C]42[/C][C]0.019742[/C][C]0.1809[/C][C]0.428426[/C][/ROW]
[ROW][C]43[/C][C]0.048744[/C][C]0.4467[/C][C]0.328105[/C][/ROW]
[ROW][C]44[/C][C]0.010717[/C][C]0.0982[/C][C]0.460996[/C][/ROW]
[ROW][C]45[/C][C]0.050747[/C][C]0.4651[/C][C]0.321532[/C][/ROW]
[ROW][C]46[/C][C]-0.036376[/C][C]-0.3334[/C][C]0.369835[/C][/ROW]
[ROW][C]47[/C][C]-0.096948[/C][C]-0.8885[/C][C]0.188392[/C][/ROW]
[ROW][C]48[/C][C]-0.036444[/C][C]-0.334[/C][C]0.369601[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112422&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112422&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
10.4716324.32262.1e-05
20.2737862.50930.007009
30.2054021.88250.031613
4-0.358592-3.28650.000741
50.0585450.53660.296491
60.0692130.63430.26379
7-0.021689-0.19880.421456
8-0.124054-1.1370.129391
90.1439131.3190.095379
10-0.02745-0.25160.400989
110.1343981.23180.110734
120.2578422.36320.010215
13-0.33072-3.03110.00162
14-0.200341-1.83620.034936
15-0.177637-1.62810.053628
160.0984560.90240.184722
17-0.013335-0.12220.451509
18-0.029734-0.27250.392946
19-0.116703-1.06960.143932
200.1048190.96070.169734
21-0.009374-0.08590.465871
220.0333060.30530.380464
230.1144111.04860.148686
24-0.116833-1.07080.143666
25-0.054405-0.49860.309672
26-0.071755-0.65760.256283
27-0.057181-0.52410.300803
28-0.012739-0.11680.453667
290.0182870.16760.433651
30-0.059719-0.54730.292799
310.0209480.1920.424107
32-0.022211-0.20360.419591
330.04290.39320.347589
340.1594591.46150.073809
35-0.132081-1.21050.114733
360.0293630.26910.394249
37-0.117952-1.0810.141385
380.0388360.35590.361391
39-0.058732-0.53830.295903
400.0998930.91550.181267
41-0.036491-0.33440.369439
420.0197420.18090.428426
430.0487440.44670.328105
440.0107170.09820.460996
450.0507470.46510.321532
46-0.036376-0.33340.369835
47-0.096948-0.88850.188392
48-0.036444-0.3340.369601



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 ; par8 = ;
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')