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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 computationMon, 20 Dec 2010 16:16:49 +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/20/t1292863391q2sau3cbtprt1ht.htm/, Retrieved Sat, 04 May 2024 02:06:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113018, Retrieved Sat, 04 May 2024 02:06:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [SMP prof bach] [2008-12-15 22:25:20] [bc937651ef42bf891200cf0e0edc7238]
- RM    [Variance Reduction Matrix] [VRM prof bach] [2008-12-15 22:31:00] [bc937651ef42bf891200cf0e0edc7238]
- RMP     [(Partial) Autocorrelation Function] [ARIMA Prof bach A...] [2008-12-15 22:38:57] [bc937651ef42bf891200cf0e0edc7238]
-  MPD        [(Partial) Autocorrelation Function] [] [2010-12-20 16:16:49] [d1991ab4912b5ede0ff54c26afa5d84c] [Current]
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Dataseries X:
2539,91
2502,66
2466,92
2513,17
2443,27
2293,41
2070,83
2029,60
2052,02
1864,44
1670,07
1810,99
1905,41
1862,83
2014,45
2197,82
2962,34
3047,03
3032,60
3504,37
3801,06
3857,62
3674,40
3720,98
3844,49
4116,68
4105,18
4435,23
4296,49
4202,52
4562,84
4621,40
4696,96
4591,27
4356,98
4502,64
4443,91
4290,89
4199,75
4138,52
3970,10
3862,27
3701,61
3570,12
3801,06
3895,51
3917,96
3813,06
3667,03




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113018&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113018&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113018&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'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2487281.72320.045641
20.0322110.22320.412178
30.2065441.4310.079458
40.2314781.60370.057667
50.2688131.86240.034338
6-0.061709-0.42750.335451
7-0.094881-0.65740.257046
80.1123760.77860.22003
9-0.022596-0.15660.438127
10-0.222217-1.53960.065117
110.0648270.44910.327678
12-0.096772-0.67050.252891
13-0.135107-0.93610.176966
14-0.001244-0.00860.49658
15-0.124025-0.85930.197232
160.0016280.01130.495524
17-0.183908-1.27410.104373
18-0.243287-1.68550.049187
190.0256430.17770.42987
20-0.109118-0.7560.226674
21-0.217163-1.50460.069496
22-0.20117-1.39370.084907
23-0.170751-1.1830.121319
24-0.084101-0.58270.281423
25-0.041057-0.28450.388644
26-0.121176-0.83950.202666
27-0.045234-0.31340.37767
280.0625190.43310.333426
290.0155930.1080.457211
300.0566940.39280.348108
31-0.011701-0.08110.467862
320.0062550.04330.482806
330.073730.51080.305911
340.0313120.21690.414588
350.0224870.15580.438424
360.0380150.26340.396694
370.0463140.32090.374849
380.0360690.24990.401868
390.0067070.04650.481564
40-0.004146-0.02870.488603
410.0334610.23180.408829
420.034340.23790.40648
430.0134220.0930.46315
440.0047340.03280.486986
450.0020810.01440.494278
460.0097520.06760.473205
470.0056290.0390.484526
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.248728 & 1.7232 & 0.045641 \tabularnewline
2 & 0.032211 & 0.2232 & 0.412178 \tabularnewline
3 & 0.206544 & 1.431 & 0.079458 \tabularnewline
4 & 0.231478 & 1.6037 & 0.057667 \tabularnewline
5 & 0.268813 & 1.8624 & 0.034338 \tabularnewline
6 & -0.061709 & -0.4275 & 0.335451 \tabularnewline
7 & -0.094881 & -0.6574 & 0.257046 \tabularnewline
8 & 0.112376 & 0.7786 & 0.22003 \tabularnewline
9 & -0.022596 & -0.1566 & 0.438127 \tabularnewline
10 & -0.222217 & -1.5396 & 0.065117 \tabularnewline
11 & 0.064827 & 0.4491 & 0.327678 \tabularnewline
12 & -0.096772 & -0.6705 & 0.252891 \tabularnewline
13 & -0.135107 & -0.9361 & 0.176966 \tabularnewline
14 & -0.001244 & -0.0086 & 0.49658 \tabularnewline
15 & -0.124025 & -0.8593 & 0.197232 \tabularnewline
16 & 0.001628 & 0.0113 & 0.495524 \tabularnewline
17 & -0.183908 & -1.2741 & 0.104373 \tabularnewline
18 & -0.243287 & -1.6855 & 0.049187 \tabularnewline
19 & 0.025643 & 0.1777 & 0.42987 \tabularnewline
20 & -0.109118 & -0.756 & 0.226674 \tabularnewline
21 & -0.217163 & -1.5046 & 0.069496 \tabularnewline
22 & -0.20117 & -1.3937 & 0.084907 \tabularnewline
23 & -0.170751 & -1.183 & 0.121319 \tabularnewline
24 & -0.084101 & -0.5827 & 0.281423 \tabularnewline
25 & -0.041057 & -0.2845 & 0.388644 \tabularnewline
26 & -0.121176 & -0.8395 & 0.202666 \tabularnewline
27 & -0.045234 & -0.3134 & 0.37767 \tabularnewline
28 & 0.062519 & 0.4331 & 0.333426 \tabularnewline
29 & 0.015593 & 0.108 & 0.457211 \tabularnewline
30 & 0.056694 & 0.3928 & 0.348108 \tabularnewline
31 & -0.011701 & -0.0811 & 0.467862 \tabularnewline
32 & 0.006255 & 0.0433 & 0.482806 \tabularnewline
33 & 0.07373 & 0.5108 & 0.305911 \tabularnewline
34 & 0.031312 & 0.2169 & 0.414588 \tabularnewline
35 & 0.022487 & 0.1558 & 0.438424 \tabularnewline
36 & 0.038015 & 0.2634 & 0.396694 \tabularnewline
37 & 0.046314 & 0.3209 & 0.374849 \tabularnewline
38 & 0.036069 & 0.2499 & 0.401868 \tabularnewline
39 & 0.006707 & 0.0465 & 0.481564 \tabularnewline
40 & -0.004146 & -0.0287 & 0.488603 \tabularnewline
41 & 0.033461 & 0.2318 & 0.408829 \tabularnewline
42 & 0.03434 & 0.2379 & 0.40648 \tabularnewline
43 & 0.013422 & 0.093 & 0.46315 \tabularnewline
44 & 0.004734 & 0.0328 & 0.486986 \tabularnewline
45 & 0.002081 & 0.0144 & 0.494278 \tabularnewline
46 & 0.009752 & 0.0676 & 0.473205 \tabularnewline
47 & 0.005629 & 0.039 & 0.484526 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113018&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]0.248728[/C][C]1.7232[/C][C]0.045641[/C][/ROW]
[ROW][C]2[/C][C]0.032211[/C][C]0.2232[/C][C]0.412178[/C][/ROW]
[ROW][C]3[/C][C]0.206544[/C][C]1.431[/C][C]0.079458[/C][/ROW]
[ROW][C]4[/C][C]0.231478[/C][C]1.6037[/C][C]0.057667[/C][/ROW]
[ROW][C]5[/C][C]0.268813[/C][C]1.8624[/C][C]0.034338[/C][/ROW]
[ROW][C]6[/C][C]-0.061709[/C][C]-0.4275[/C][C]0.335451[/C][/ROW]
[ROW][C]7[/C][C]-0.094881[/C][C]-0.6574[/C][C]0.257046[/C][/ROW]
[ROW][C]8[/C][C]0.112376[/C][C]0.7786[/C][C]0.22003[/C][/ROW]
[ROW][C]9[/C][C]-0.022596[/C][C]-0.1566[/C][C]0.438127[/C][/ROW]
[ROW][C]10[/C][C]-0.222217[/C][C]-1.5396[/C][C]0.065117[/C][/ROW]
[ROW][C]11[/C][C]0.064827[/C][C]0.4491[/C][C]0.327678[/C][/ROW]
[ROW][C]12[/C][C]-0.096772[/C][C]-0.6705[/C][C]0.252891[/C][/ROW]
[ROW][C]13[/C][C]-0.135107[/C][C]-0.9361[/C][C]0.176966[/C][/ROW]
[ROW][C]14[/C][C]-0.001244[/C][C]-0.0086[/C][C]0.49658[/C][/ROW]
[ROW][C]15[/C][C]-0.124025[/C][C]-0.8593[/C][C]0.197232[/C][/ROW]
[ROW][C]16[/C][C]0.001628[/C][C]0.0113[/C][C]0.495524[/C][/ROW]
[ROW][C]17[/C][C]-0.183908[/C][C]-1.2741[/C][C]0.104373[/C][/ROW]
[ROW][C]18[/C][C]-0.243287[/C][C]-1.6855[/C][C]0.049187[/C][/ROW]
[ROW][C]19[/C][C]0.025643[/C][C]0.1777[/C][C]0.42987[/C][/ROW]
[ROW][C]20[/C][C]-0.109118[/C][C]-0.756[/C][C]0.226674[/C][/ROW]
[ROW][C]21[/C][C]-0.217163[/C][C]-1.5046[/C][C]0.069496[/C][/ROW]
[ROW][C]22[/C][C]-0.20117[/C][C]-1.3937[/C][C]0.084907[/C][/ROW]
[ROW][C]23[/C][C]-0.170751[/C][C]-1.183[/C][C]0.121319[/C][/ROW]
[ROW][C]24[/C][C]-0.084101[/C][C]-0.5827[/C][C]0.281423[/C][/ROW]
[ROW][C]25[/C][C]-0.041057[/C][C]-0.2845[/C][C]0.388644[/C][/ROW]
[ROW][C]26[/C][C]-0.121176[/C][C]-0.8395[/C][C]0.202666[/C][/ROW]
[ROW][C]27[/C][C]-0.045234[/C][C]-0.3134[/C][C]0.37767[/C][/ROW]
[ROW][C]28[/C][C]0.062519[/C][C]0.4331[/C][C]0.333426[/C][/ROW]
[ROW][C]29[/C][C]0.015593[/C][C]0.108[/C][C]0.457211[/C][/ROW]
[ROW][C]30[/C][C]0.056694[/C][C]0.3928[/C][C]0.348108[/C][/ROW]
[ROW][C]31[/C][C]-0.011701[/C][C]-0.0811[/C][C]0.467862[/C][/ROW]
[ROW][C]32[/C][C]0.006255[/C][C]0.0433[/C][C]0.482806[/C][/ROW]
[ROW][C]33[/C][C]0.07373[/C][C]0.5108[/C][C]0.305911[/C][/ROW]
[ROW][C]34[/C][C]0.031312[/C][C]0.2169[/C][C]0.414588[/C][/ROW]
[ROW][C]35[/C][C]0.022487[/C][C]0.1558[/C][C]0.438424[/C][/ROW]
[ROW][C]36[/C][C]0.038015[/C][C]0.2634[/C][C]0.396694[/C][/ROW]
[ROW][C]37[/C][C]0.046314[/C][C]0.3209[/C][C]0.374849[/C][/ROW]
[ROW][C]38[/C][C]0.036069[/C][C]0.2499[/C][C]0.401868[/C][/ROW]
[ROW][C]39[/C][C]0.006707[/C][C]0.0465[/C][C]0.481564[/C][/ROW]
[ROW][C]40[/C][C]-0.004146[/C][C]-0.0287[/C][C]0.488603[/C][/ROW]
[ROW][C]41[/C][C]0.033461[/C][C]0.2318[/C][C]0.408829[/C][/ROW]
[ROW][C]42[/C][C]0.03434[/C][C]0.2379[/C][C]0.40648[/C][/ROW]
[ROW][C]43[/C][C]0.013422[/C][C]0.093[/C][C]0.46315[/C][/ROW]
[ROW][C]44[/C][C]0.004734[/C][C]0.0328[/C][C]0.486986[/C][/ROW]
[ROW][C]45[/C][C]0.002081[/C][C]0.0144[/C][C]0.494278[/C][/ROW]
[ROW][C]46[/C][C]0.009752[/C][C]0.0676[/C][C]0.473205[/C][/ROW]
[ROW][C]47[/C][C]0.005629[/C][C]0.039[/C][C]0.484526[/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=113018&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113018&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
10.2487281.72320.045641
20.0322110.22320.412178
30.2065441.4310.079458
40.2314781.60370.057667
50.2688131.86240.034338
6-0.061709-0.42750.335451
7-0.094881-0.65740.257046
80.1123760.77860.22003
9-0.022596-0.15660.438127
10-0.222217-1.53960.065117
110.0648270.44910.327678
12-0.096772-0.67050.252891
13-0.135107-0.93610.176966
14-0.001244-0.00860.49658
15-0.124025-0.85930.197232
160.0016280.01130.495524
17-0.183908-1.27410.104373
18-0.243287-1.68550.049187
190.0256430.17770.42987
20-0.109118-0.7560.226674
21-0.217163-1.50460.069496
22-0.20117-1.39370.084907
23-0.170751-1.1830.121319
24-0.084101-0.58270.281423
25-0.041057-0.28450.388644
26-0.121176-0.83950.202666
27-0.045234-0.31340.37767
280.0625190.43310.333426
290.0155930.1080.457211
300.0566940.39280.348108
31-0.011701-0.08110.467862
320.0062550.04330.482806
330.073730.51080.305911
340.0313120.21690.414588
350.0224870.15580.438424
360.0380150.26340.396694
370.0463140.32090.374849
380.0360690.24990.401868
390.0067070.04650.481564
40-0.004146-0.02870.488603
410.0334610.23180.408829
420.034340.23790.40648
430.0134220.0930.46315
440.0047340.03280.486986
450.0020810.01440.494278
460.0097520.06760.473205
470.0056290.0390.484526
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2487281.72320.045641
2-0.031611-0.2190.413787
30.2199551.52390.067049
40.140350.97240.167869
50.2170741.50390.069575
6-0.224971-1.55860.062825
7-0.096133-0.6660.25429
80.0259480.17980.429043
9-0.104513-0.72410.236263
10-0.209376-1.45060.076698
110.2914642.01930.024528
12-0.207956-1.44080.078072
13-0.031012-0.21490.415394
140.1328070.92010.181057
15-0.073291-0.50780.306969
16-0.091469-0.63370.264638
17-0.109743-0.76030.22539
18-0.109105-0.75590.2267
19-0.006123-0.04240.483168
20-0.093032-0.64450.261145
210.0146780.10170.459714
22-0.208694-1.44590.077355
23-0.030812-0.21350.415932
24-0.028838-0.19980.421243
250.0405030.28060.390107
260.0419730.29080.386229
27-0.034255-0.23730.406708
280.0814950.56460.287483
290.0337020.23350.408185
30-0.141468-0.98010.16597
31-0.003198-0.02220.491207
32-0.078483-0.54370.294566
33-0.076817-0.53220.29852
340.005140.03560.48587
350.0092980.06440.474451
360.0307860.21330.416001
370.0135910.09420.462687
380.0115230.07980.468351
39-0.125965-0.87270.193583
40-0.101166-0.70090.243374
410.0047250.03270.487012
42-0.060147-0.41670.339375
430.0058040.04020.484046
44-0.038604-0.26750.395131
45-0.047323-0.32790.37222
460.0210510.14580.442327
47-0.036072-0.24990.401861
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.248728 & 1.7232 & 0.045641 \tabularnewline
2 & -0.031611 & -0.219 & 0.413787 \tabularnewline
3 & 0.219955 & 1.5239 & 0.067049 \tabularnewline
4 & 0.14035 & 0.9724 & 0.167869 \tabularnewline
5 & 0.217074 & 1.5039 & 0.069575 \tabularnewline
6 & -0.224971 & -1.5586 & 0.062825 \tabularnewline
7 & -0.096133 & -0.666 & 0.25429 \tabularnewline
8 & 0.025948 & 0.1798 & 0.429043 \tabularnewline
9 & -0.104513 & -0.7241 & 0.236263 \tabularnewline
10 & -0.209376 & -1.4506 & 0.076698 \tabularnewline
11 & 0.291464 & 2.0193 & 0.024528 \tabularnewline
12 & -0.207956 & -1.4408 & 0.078072 \tabularnewline
13 & -0.031012 & -0.2149 & 0.415394 \tabularnewline
14 & 0.132807 & 0.9201 & 0.181057 \tabularnewline
15 & -0.073291 & -0.5078 & 0.306969 \tabularnewline
16 & -0.091469 & -0.6337 & 0.264638 \tabularnewline
17 & -0.109743 & -0.7603 & 0.22539 \tabularnewline
18 & -0.109105 & -0.7559 & 0.2267 \tabularnewline
19 & -0.006123 & -0.0424 & 0.483168 \tabularnewline
20 & -0.093032 & -0.6445 & 0.261145 \tabularnewline
21 & 0.014678 & 0.1017 & 0.459714 \tabularnewline
22 & -0.208694 & -1.4459 & 0.077355 \tabularnewline
23 & -0.030812 & -0.2135 & 0.415932 \tabularnewline
24 & -0.028838 & -0.1998 & 0.421243 \tabularnewline
25 & 0.040503 & 0.2806 & 0.390107 \tabularnewline
26 & 0.041973 & 0.2908 & 0.386229 \tabularnewline
27 & -0.034255 & -0.2373 & 0.406708 \tabularnewline
28 & 0.081495 & 0.5646 & 0.287483 \tabularnewline
29 & 0.033702 & 0.2335 & 0.408185 \tabularnewline
30 & -0.141468 & -0.9801 & 0.16597 \tabularnewline
31 & -0.003198 & -0.0222 & 0.491207 \tabularnewline
32 & -0.078483 & -0.5437 & 0.294566 \tabularnewline
33 & -0.076817 & -0.5322 & 0.29852 \tabularnewline
34 & 0.00514 & 0.0356 & 0.48587 \tabularnewline
35 & 0.009298 & 0.0644 & 0.474451 \tabularnewline
36 & 0.030786 & 0.2133 & 0.416001 \tabularnewline
37 & 0.013591 & 0.0942 & 0.462687 \tabularnewline
38 & 0.011523 & 0.0798 & 0.468351 \tabularnewline
39 & -0.125965 & -0.8727 & 0.193583 \tabularnewline
40 & -0.101166 & -0.7009 & 0.243374 \tabularnewline
41 & 0.004725 & 0.0327 & 0.487012 \tabularnewline
42 & -0.060147 & -0.4167 & 0.339375 \tabularnewline
43 & 0.005804 & 0.0402 & 0.484046 \tabularnewline
44 & -0.038604 & -0.2675 & 0.395131 \tabularnewline
45 & -0.047323 & -0.3279 & 0.37222 \tabularnewline
46 & 0.021051 & 0.1458 & 0.442327 \tabularnewline
47 & -0.036072 & -0.2499 & 0.401861 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113018&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]0.248728[/C][C]1.7232[/C][C]0.045641[/C][/ROW]
[ROW][C]2[/C][C]-0.031611[/C][C]-0.219[/C][C]0.413787[/C][/ROW]
[ROW][C]3[/C][C]0.219955[/C][C]1.5239[/C][C]0.067049[/C][/ROW]
[ROW][C]4[/C][C]0.14035[/C][C]0.9724[/C][C]0.167869[/C][/ROW]
[ROW][C]5[/C][C]0.217074[/C][C]1.5039[/C][C]0.069575[/C][/ROW]
[ROW][C]6[/C][C]-0.224971[/C][C]-1.5586[/C][C]0.062825[/C][/ROW]
[ROW][C]7[/C][C]-0.096133[/C][C]-0.666[/C][C]0.25429[/C][/ROW]
[ROW][C]8[/C][C]0.025948[/C][C]0.1798[/C][C]0.429043[/C][/ROW]
[ROW][C]9[/C][C]-0.104513[/C][C]-0.7241[/C][C]0.236263[/C][/ROW]
[ROW][C]10[/C][C]-0.209376[/C][C]-1.4506[/C][C]0.076698[/C][/ROW]
[ROW][C]11[/C][C]0.291464[/C][C]2.0193[/C][C]0.024528[/C][/ROW]
[ROW][C]12[/C][C]-0.207956[/C][C]-1.4408[/C][C]0.078072[/C][/ROW]
[ROW][C]13[/C][C]-0.031012[/C][C]-0.2149[/C][C]0.415394[/C][/ROW]
[ROW][C]14[/C][C]0.132807[/C][C]0.9201[/C][C]0.181057[/C][/ROW]
[ROW][C]15[/C][C]-0.073291[/C][C]-0.5078[/C][C]0.306969[/C][/ROW]
[ROW][C]16[/C][C]-0.091469[/C][C]-0.6337[/C][C]0.264638[/C][/ROW]
[ROW][C]17[/C][C]-0.109743[/C][C]-0.7603[/C][C]0.22539[/C][/ROW]
[ROW][C]18[/C][C]-0.109105[/C][C]-0.7559[/C][C]0.2267[/C][/ROW]
[ROW][C]19[/C][C]-0.006123[/C][C]-0.0424[/C][C]0.483168[/C][/ROW]
[ROW][C]20[/C][C]-0.093032[/C][C]-0.6445[/C][C]0.261145[/C][/ROW]
[ROW][C]21[/C][C]0.014678[/C][C]0.1017[/C][C]0.459714[/C][/ROW]
[ROW][C]22[/C][C]-0.208694[/C][C]-1.4459[/C][C]0.077355[/C][/ROW]
[ROW][C]23[/C][C]-0.030812[/C][C]-0.2135[/C][C]0.415932[/C][/ROW]
[ROW][C]24[/C][C]-0.028838[/C][C]-0.1998[/C][C]0.421243[/C][/ROW]
[ROW][C]25[/C][C]0.040503[/C][C]0.2806[/C][C]0.390107[/C][/ROW]
[ROW][C]26[/C][C]0.041973[/C][C]0.2908[/C][C]0.386229[/C][/ROW]
[ROW][C]27[/C][C]-0.034255[/C][C]-0.2373[/C][C]0.406708[/C][/ROW]
[ROW][C]28[/C][C]0.081495[/C][C]0.5646[/C][C]0.287483[/C][/ROW]
[ROW][C]29[/C][C]0.033702[/C][C]0.2335[/C][C]0.408185[/C][/ROW]
[ROW][C]30[/C][C]-0.141468[/C][C]-0.9801[/C][C]0.16597[/C][/ROW]
[ROW][C]31[/C][C]-0.003198[/C][C]-0.0222[/C][C]0.491207[/C][/ROW]
[ROW][C]32[/C][C]-0.078483[/C][C]-0.5437[/C][C]0.294566[/C][/ROW]
[ROW][C]33[/C][C]-0.076817[/C][C]-0.5322[/C][C]0.29852[/C][/ROW]
[ROW][C]34[/C][C]0.00514[/C][C]0.0356[/C][C]0.48587[/C][/ROW]
[ROW][C]35[/C][C]0.009298[/C][C]0.0644[/C][C]0.474451[/C][/ROW]
[ROW][C]36[/C][C]0.030786[/C][C]0.2133[/C][C]0.416001[/C][/ROW]
[ROW][C]37[/C][C]0.013591[/C][C]0.0942[/C][C]0.462687[/C][/ROW]
[ROW][C]38[/C][C]0.011523[/C][C]0.0798[/C][C]0.468351[/C][/ROW]
[ROW][C]39[/C][C]-0.125965[/C][C]-0.8727[/C][C]0.193583[/C][/ROW]
[ROW][C]40[/C][C]-0.101166[/C][C]-0.7009[/C][C]0.243374[/C][/ROW]
[ROW][C]41[/C][C]0.004725[/C][C]0.0327[/C][C]0.487012[/C][/ROW]
[ROW][C]42[/C][C]-0.060147[/C][C]-0.4167[/C][C]0.339375[/C][/ROW]
[ROW][C]43[/C][C]0.005804[/C][C]0.0402[/C][C]0.484046[/C][/ROW]
[ROW][C]44[/C][C]-0.038604[/C][C]-0.2675[/C][C]0.395131[/C][/ROW]
[ROW][C]45[/C][C]-0.047323[/C][C]-0.3279[/C][C]0.37222[/C][/ROW]
[ROW][C]46[/C][C]0.021051[/C][C]0.1458[/C][C]0.442327[/C][/ROW]
[ROW][C]47[/C][C]-0.036072[/C][C]-0.2499[/C][C]0.401861[/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=113018&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113018&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
10.2487281.72320.045641
2-0.031611-0.2190.413787
30.2199551.52390.067049
40.140350.97240.167869
50.2170741.50390.069575
6-0.224971-1.55860.062825
7-0.096133-0.6660.25429
80.0259480.17980.429043
9-0.104513-0.72410.236263
10-0.209376-1.45060.076698
110.2914642.01930.024528
12-0.207956-1.44080.078072
13-0.031012-0.21490.415394
140.1328070.92010.181057
15-0.073291-0.50780.306969
16-0.091469-0.63370.264638
17-0.109743-0.76030.22539
18-0.109105-0.75590.2267
19-0.006123-0.04240.483168
20-0.093032-0.64450.261145
210.0146780.10170.459714
22-0.208694-1.44590.077355
23-0.030812-0.21350.415932
24-0.028838-0.19980.421243
250.0405030.28060.390107
260.0419730.29080.386229
27-0.034255-0.23730.406708
280.0814950.56460.287483
290.0337020.23350.408185
30-0.141468-0.98010.16597
31-0.003198-0.02220.491207
32-0.078483-0.54370.294566
33-0.076817-0.53220.29852
340.005140.03560.48587
350.0092980.06440.474451
360.0307860.21330.416001
370.0135910.09420.462687
380.0115230.07980.468351
39-0.125965-0.87270.193583
40-0.101166-0.70090.243374
410.0047250.03270.487012
42-0.060147-0.41670.339375
430.0058040.04020.484046
44-0.038604-0.26750.395131
45-0.047323-0.32790.37222
460.0210510.14580.442327
47-0.036072-0.24990.401861
48NANANA



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