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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, 03 Dec 2010 09:47:23 +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/03/t129136954010cxg1a6d3b33jo.htm/, Retrieved Tue, 07 May 2024 17:26:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104573, Retrieved Tue, 07 May 2024 17:26:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
-   PD            [(Partial) Autocorrelation Function] [Workshop 9 - Auto...] [2010-12-03 09:47:23] [708f372e2a7a3c78ea31b4de2d1213f8] [Current]
-                   [(Partial) Autocorrelation Function] [Workshop 9 - Auto...] [2010-12-03 10:22:20] [6f0e7a2d1a07390e3505a2db8288f975]
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Dataseries X:
1579
2146
2462
3695
4831
5134
6250
5760
6249
2917
1741
2359
1511
2059
2635
2867
4403
5720
4502
5749
5627
2846
1762
2429
1169
2154
2249
2687
4359
5382
4459
6398
4596
3024
1887
2070
1351
2218
2461
3028
4784
4975
4607
6249
4809
3157
1910
2228
1594
2467
2222
3607
4685
4962
5770
5480
5000
3228
1993
2288
1580
2111
2192
3601
4665
4876
5813
5589
5331
3075
2002
2306
1507
1992
2487
3490
4647
5594
5611
5788
6204
3013
1931
2549
1504
2090
2702
2939
4500
6208
6415
5657
5964
3163
1997
2422




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104573&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104573&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.73477.19860
20.3870883.79270.00013
3-0.000125-0.00120.499511
4-0.434319-4.25542.4e-05
5-0.7201-7.05550
6-0.785135-7.69270
7-0.692733-6.78740
8-0.383629-3.75880.000147
90.0349580.34250.366357
100.3562813.49080.000365
110.6524266.39240
120.8221578.05550
130.6236386.11040
140.3342693.27520.000735
15-0.013351-0.13080.448097
16-0.364028-3.56670.000283
17-0.6031-5.90910
18-0.677232-6.63550
19-0.596272-5.84220
20-0.323152-3.16620.001035
210.014120.13830.445129
220.3016552.95560.001963
230.5693635.57860
240.6768256.63150
250.5342065.23410
260.2812332.75550.003506
27-0.024434-0.23940.405652
28-0.311348-3.05060.001476
29-0.516375-5.05941e-06
30-0.57805-5.66370
31-0.493765-4.83792e-06
32-0.262282-2.56980.005857
330.0120490.11810.453134
340.2647472.5940.005486
350.4755114.6595e-06
360.5607925.49460
370.4552044.46011.1e-05
380.2186432.14230.017352
39-0.023018-0.22550.411022
40-0.25436-2.49220.007204
41-0.433697-4.24932.5e-05
42-0.48058-4.70874e-06
43-0.399627-3.91558.4e-05
44-0.228852-2.24230.013622
450.0167490.16410.434996
460.2314142.26740.012805
470.383943.76180.000145
480.4630354.53688e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.7347 & 7.1986 & 0 \tabularnewline
2 & 0.387088 & 3.7927 & 0.00013 \tabularnewline
3 & -0.000125 & -0.0012 & 0.499511 \tabularnewline
4 & -0.434319 & -4.2554 & 2.4e-05 \tabularnewline
5 & -0.7201 & -7.0555 & 0 \tabularnewline
6 & -0.785135 & -7.6927 & 0 \tabularnewline
7 & -0.692733 & -6.7874 & 0 \tabularnewline
8 & -0.383629 & -3.7588 & 0.000147 \tabularnewline
9 & 0.034958 & 0.3425 & 0.366357 \tabularnewline
10 & 0.356281 & 3.4908 & 0.000365 \tabularnewline
11 & 0.652426 & 6.3924 & 0 \tabularnewline
12 & 0.822157 & 8.0555 & 0 \tabularnewline
13 & 0.623638 & 6.1104 & 0 \tabularnewline
14 & 0.334269 & 3.2752 & 0.000735 \tabularnewline
15 & -0.013351 & -0.1308 & 0.448097 \tabularnewline
16 & -0.364028 & -3.5667 & 0.000283 \tabularnewline
17 & -0.6031 & -5.9091 & 0 \tabularnewline
18 & -0.677232 & -6.6355 & 0 \tabularnewline
19 & -0.596272 & -5.8422 & 0 \tabularnewline
20 & -0.323152 & -3.1662 & 0.001035 \tabularnewline
21 & 0.01412 & 0.1383 & 0.445129 \tabularnewline
22 & 0.301655 & 2.9556 & 0.001963 \tabularnewline
23 & 0.569363 & 5.5786 & 0 \tabularnewline
24 & 0.676825 & 6.6315 & 0 \tabularnewline
25 & 0.534206 & 5.2341 & 0 \tabularnewline
26 & 0.281233 & 2.7555 & 0.003506 \tabularnewline
27 & -0.024434 & -0.2394 & 0.405652 \tabularnewline
28 & -0.311348 & -3.0506 & 0.001476 \tabularnewline
29 & -0.516375 & -5.0594 & 1e-06 \tabularnewline
30 & -0.57805 & -5.6637 & 0 \tabularnewline
31 & -0.493765 & -4.8379 & 2e-06 \tabularnewline
32 & -0.262282 & -2.5698 & 0.005857 \tabularnewline
33 & 0.012049 & 0.1181 & 0.453134 \tabularnewline
34 & 0.264747 & 2.594 & 0.005486 \tabularnewline
35 & 0.475511 & 4.659 & 5e-06 \tabularnewline
36 & 0.560792 & 5.4946 & 0 \tabularnewline
37 & 0.455204 & 4.4601 & 1.1e-05 \tabularnewline
38 & 0.218643 & 2.1423 & 0.017352 \tabularnewline
39 & -0.023018 & -0.2255 & 0.411022 \tabularnewline
40 & -0.25436 & -2.4922 & 0.007204 \tabularnewline
41 & -0.433697 & -4.2493 & 2.5e-05 \tabularnewline
42 & -0.48058 & -4.7087 & 4e-06 \tabularnewline
43 & -0.399627 & -3.9155 & 8.4e-05 \tabularnewline
44 & -0.228852 & -2.2423 & 0.013622 \tabularnewline
45 & 0.016749 & 0.1641 & 0.434996 \tabularnewline
46 & 0.231414 & 2.2674 & 0.012805 \tabularnewline
47 & 0.38394 & 3.7618 & 0.000145 \tabularnewline
48 & 0.463035 & 4.5368 & 8e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104573&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]0.7347[/C][C]7.1986[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.387088[/C][C]3.7927[/C][C]0.00013[/C][/ROW]
[ROW][C]3[/C][C]-0.000125[/C][C]-0.0012[/C][C]0.499511[/C][/ROW]
[ROW][C]4[/C][C]-0.434319[/C][C]-4.2554[/C][C]2.4e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.7201[/C][C]-7.0555[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]-0.785135[/C][C]-7.6927[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.692733[/C][C]-6.7874[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]-0.383629[/C][C]-3.7588[/C][C]0.000147[/C][/ROW]
[ROW][C]9[/C][C]0.034958[/C][C]0.3425[/C][C]0.366357[/C][/ROW]
[ROW][C]10[/C][C]0.356281[/C][C]3.4908[/C][C]0.000365[/C][/ROW]
[ROW][C]11[/C][C]0.652426[/C][C]6.3924[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.822157[/C][C]8.0555[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.623638[/C][C]6.1104[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.334269[/C][C]3.2752[/C][C]0.000735[/C][/ROW]
[ROW][C]15[/C][C]-0.013351[/C][C]-0.1308[/C][C]0.448097[/C][/ROW]
[ROW][C]16[/C][C]-0.364028[/C][C]-3.5667[/C][C]0.000283[/C][/ROW]
[ROW][C]17[/C][C]-0.6031[/C][C]-5.9091[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]-0.677232[/C][C]-6.6355[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.596272[/C][C]-5.8422[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]-0.323152[/C][C]-3.1662[/C][C]0.001035[/C][/ROW]
[ROW][C]21[/C][C]0.01412[/C][C]0.1383[/C][C]0.445129[/C][/ROW]
[ROW][C]22[/C][C]0.301655[/C][C]2.9556[/C][C]0.001963[/C][/ROW]
[ROW][C]23[/C][C]0.569363[/C][C]5.5786[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.676825[/C][C]6.6315[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.534206[/C][C]5.2341[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.281233[/C][C]2.7555[/C][C]0.003506[/C][/ROW]
[ROW][C]27[/C][C]-0.024434[/C][C]-0.2394[/C][C]0.405652[/C][/ROW]
[ROW][C]28[/C][C]-0.311348[/C][C]-3.0506[/C][C]0.001476[/C][/ROW]
[ROW][C]29[/C][C]-0.516375[/C][C]-5.0594[/C][C]1e-06[/C][/ROW]
[ROW][C]30[/C][C]-0.57805[/C][C]-5.6637[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]-0.493765[/C][C]-4.8379[/C][C]2e-06[/C][/ROW]
[ROW][C]32[/C][C]-0.262282[/C][C]-2.5698[/C][C]0.005857[/C][/ROW]
[ROW][C]33[/C][C]0.012049[/C][C]0.1181[/C][C]0.453134[/C][/ROW]
[ROW][C]34[/C][C]0.264747[/C][C]2.594[/C][C]0.005486[/C][/ROW]
[ROW][C]35[/C][C]0.475511[/C][C]4.659[/C][C]5e-06[/C][/ROW]
[ROW][C]36[/C][C]0.560792[/C][C]5.4946[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.455204[/C][C]4.4601[/C][C]1.1e-05[/C][/ROW]
[ROW][C]38[/C][C]0.218643[/C][C]2.1423[/C][C]0.017352[/C][/ROW]
[ROW][C]39[/C][C]-0.023018[/C][C]-0.2255[/C][C]0.411022[/C][/ROW]
[ROW][C]40[/C][C]-0.25436[/C][C]-2.4922[/C][C]0.007204[/C][/ROW]
[ROW][C]41[/C][C]-0.433697[/C][C]-4.2493[/C][C]2.5e-05[/C][/ROW]
[ROW][C]42[/C][C]-0.48058[/C][C]-4.7087[/C][C]4e-06[/C][/ROW]
[ROW][C]43[/C][C]-0.399627[/C][C]-3.9155[/C][C]8.4e-05[/C][/ROW]
[ROW][C]44[/C][C]-0.228852[/C][C]-2.2423[/C][C]0.013622[/C][/ROW]
[ROW][C]45[/C][C]0.016749[/C][C]0.1641[/C][C]0.434996[/C][/ROW]
[ROW][C]46[/C][C]0.231414[/C][C]2.2674[/C][C]0.012805[/C][/ROW]
[ROW][C]47[/C][C]0.38394[/C][C]3.7618[/C][C]0.000145[/C][/ROW]
[ROW][C]48[/C][C]0.463035[/C][C]4.5368[/C][C]8e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104573&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
10.73477.19860
20.3870883.79270.00013
3-0.000125-0.00120.499511
4-0.434319-4.25542.4e-05
5-0.7201-7.05550
6-0.785135-7.69270
7-0.692733-6.78740
8-0.383629-3.75880.000147
90.0349580.34250.366357
100.3562813.49080.000365
110.6524266.39240
120.8221578.05550
130.6236386.11040
140.3342693.27520.000735
15-0.013351-0.13080.448097
16-0.364028-3.56670.000283
17-0.6031-5.90910
18-0.677232-6.63550
19-0.596272-5.84220
20-0.323152-3.16620.001035
210.014120.13830.445129
220.3016552.95560.001963
230.5693635.57860
240.6768256.63150
250.5342065.23410
260.2812332.75550.003506
27-0.024434-0.23940.405652
28-0.311348-3.05060.001476
29-0.516375-5.05941e-06
30-0.57805-5.66370
31-0.493765-4.83792e-06
32-0.262282-2.56980.005857
330.0120490.11810.453134
340.2647472.5940.005486
350.4755114.6595e-06
360.5607925.49460
370.4552044.46011.1e-05
380.2186432.14230.017352
39-0.023018-0.22550.411022
40-0.25436-2.49220.007204
41-0.433697-4.24932.5e-05
42-0.48058-4.70874e-06
43-0.399627-3.91558.4e-05
44-0.228852-2.24230.013622
450.0167490.16410.434996
460.2314142.26740.012805
470.383943.76180.000145
480.4630354.53688e-06







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.73477.19860
2-0.331793-3.25090.000794
3-0.329898-3.23230.000842
4-0.51606-5.05631e-06
5-0.311301-3.05010.001478
6-0.178836-1.75220.041464
7-0.267022-2.61630.005163
8-0.034569-0.33870.367784
90.0402710.39460.347018
10-0.193038-1.89140.030794
110.1601281.56890.059978
120.339613.32750.000622
13-0.291879-2.85980.0026
140.0002840.00280.498892
150.0225610.22110.41276
160.2100632.05820.021141
170.0053670.05260.479086
18-0.076259-0.74720.228391
190.0482580.47280.318703
200.0179850.17620.430247
21-0.083135-0.81450.208673
220.0839440.82250.206421
230.1016570.9960.16087
24-0.068741-0.67350.251117
25-0.059147-0.57950.281799
26-0.059967-0.58750.279107
270.0751570.73640.231647
28-0.002602-0.02550.489856
29-0.071783-0.70330.241777
300.0788130.77220.220944
310.006670.06540.474014
32-0.087903-0.86130.195619
33-0.006317-0.06190.475389
340.03370.33020.370986
35-0.027659-0.2710.393485
360.0296560.29060.386006
37-0.01611-0.15780.437455
38-0.078736-0.77150.221167
390.0648990.63590.263185
400.0021440.0210.491641
410.006930.06790.473002
420.0072850.07140.471622
430.0037130.03640.485529
44-0.08288-0.81210.209384
450.0979880.96010.169713
46-0.009623-0.09430.462539
47-0.031594-0.30960.378783
48-0.016758-0.16420.434962

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.7347 & 7.1986 & 0 \tabularnewline
2 & -0.331793 & -3.2509 & 0.000794 \tabularnewline
3 & -0.329898 & -3.2323 & 0.000842 \tabularnewline
4 & -0.51606 & -5.0563 & 1e-06 \tabularnewline
5 & -0.311301 & -3.0501 & 0.001478 \tabularnewline
6 & -0.178836 & -1.7522 & 0.041464 \tabularnewline
7 & -0.267022 & -2.6163 & 0.005163 \tabularnewline
8 & -0.034569 & -0.3387 & 0.367784 \tabularnewline
9 & 0.040271 & 0.3946 & 0.347018 \tabularnewline
10 & -0.193038 & -1.8914 & 0.030794 \tabularnewline
11 & 0.160128 & 1.5689 & 0.059978 \tabularnewline
12 & 0.33961 & 3.3275 & 0.000622 \tabularnewline
13 & -0.291879 & -2.8598 & 0.0026 \tabularnewline
14 & 0.000284 & 0.0028 & 0.498892 \tabularnewline
15 & 0.022561 & 0.2211 & 0.41276 \tabularnewline
16 & 0.210063 & 2.0582 & 0.021141 \tabularnewline
17 & 0.005367 & 0.0526 & 0.479086 \tabularnewline
18 & -0.076259 & -0.7472 & 0.228391 \tabularnewline
19 & 0.048258 & 0.4728 & 0.318703 \tabularnewline
20 & 0.017985 & 0.1762 & 0.430247 \tabularnewline
21 & -0.083135 & -0.8145 & 0.208673 \tabularnewline
22 & 0.083944 & 0.8225 & 0.206421 \tabularnewline
23 & 0.101657 & 0.996 & 0.16087 \tabularnewline
24 & -0.068741 & -0.6735 & 0.251117 \tabularnewline
25 & -0.059147 & -0.5795 & 0.281799 \tabularnewline
26 & -0.059967 & -0.5875 & 0.279107 \tabularnewline
27 & 0.075157 & 0.7364 & 0.231647 \tabularnewline
28 & -0.002602 & -0.0255 & 0.489856 \tabularnewline
29 & -0.071783 & -0.7033 & 0.241777 \tabularnewline
30 & 0.078813 & 0.7722 & 0.220944 \tabularnewline
31 & 0.00667 & 0.0654 & 0.474014 \tabularnewline
32 & -0.087903 & -0.8613 & 0.195619 \tabularnewline
33 & -0.006317 & -0.0619 & 0.475389 \tabularnewline
34 & 0.0337 & 0.3302 & 0.370986 \tabularnewline
35 & -0.027659 & -0.271 & 0.393485 \tabularnewline
36 & 0.029656 & 0.2906 & 0.386006 \tabularnewline
37 & -0.01611 & -0.1578 & 0.437455 \tabularnewline
38 & -0.078736 & -0.7715 & 0.221167 \tabularnewline
39 & 0.064899 & 0.6359 & 0.263185 \tabularnewline
40 & 0.002144 & 0.021 & 0.491641 \tabularnewline
41 & 0.00693 & 0.0679 & 0.473002 \tabularnewline
42 & 0.007285 & 0.0714 & 0.471622 \tabularnewline
43 & 0.003713 & 0.0364 & 0.485529 \tabularnewline
44 & -0.08288 & -0.8121 & 0.209384 \tabularnewline
45 & 0.097988 & 0.9601 & 0.169713 \tabularnewline
46 & -0.009623 & -0.0943 & 0.462539 \tabularnewline
47 & -0.031594 & -0.3096 & 0.378783 \tabularnewline
48 & -0.016758 & -0.1642 & 0.434962 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104573&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]0.7347[/C][C]7.1986[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.331793[/C][C]-3.2509[/C][C]0.000794[/C][/ROW]
[ROW][C]3[/C][C]-0.329898[/C][C]-3.2323[/C][C]0.000842[/C][/ROW]
[ROW][C]4[/C][C]-0.51606[/C][C]-5.0563[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]-0.311301[/C][C]-3.0501[/C][C]0.001478[/C][/ROW]
[ROW][C]6[/C][C]-0.178836[/C][C]-1.7522[/C][C]0.041464[/C][/ROW]
[ROW][C]7[/C][C]-0.267022[/C][C]-2.6163[/C][C]0.005163[/C][/ROW]
[ROW][C]8[/C][C]-0.034569[/C][C]-0.3387[/C][C]0.367784[/C][/ROW]
[ROW][C]9[/C][C]0.040271[/C][C]0.3946[/C][C]0.347018[/C][/ROW]
[ROW][C]10[/C][C]-0.193038[/C][C]-1.8914[/C][C]0.030794[/C][/ROW]
[ROW][C]11[/C][C]0.160128[/C][C]1.5689[/C][C]0.059978[/C][/ROW]
[ROW][C]12[/C][C]0.33961[/C][C]3.3275[/C][C]0.000622[/C][/ROW]
[ROW][C]13[/C][C]-0.291879[/C][C]-2.8598[/C][C]0.0026[/C][/ROW]
[ROW][C]14[/C][C]0.000284[/C][C]0.0028[/C][C]0.498892[/C][/ROW]
[ROW][C]15[/C][C]0.022561[/C][C]0.2211[/C][C]0.41276[/C][/ROW]
[ROW][C]16[/C][C]0.210063[/C][C]2.0582[/C][C]0.021141[/C][/ROW]
[ROW][C]17[/C][C]0.005367[/C][C]0.0526[/C][C]0.479086[/C][/ROW]
[ROW][C]18[/C][C]-0.076259[/C][C]-0.7472[/C][C]0.228391[/C][/ROW]
[ROW][C]19[/C][C]0.048258[/C][C]0.4728[/C][C]0.318703[/C][/ROW]
[ROW][C]20[/C][C]0.017985[/C][C]0.1762[/C][C]0.430247[/C][/ROW]
[ROW][C]21[/C][C]-0.083135[/C][C]-0.8145[/C][C]0.208673[/C][/ROW]
[ROW][C]22[/C][C]0.083944[/C][C]0.8225[/C][C]0.206421[/C][/ROW]
[ROW][C]23[/C][C]0.101657[/C][C]0.996[/C][C]0.16087[/C][/ROW]
[ROW][C]24[/C][C]-0.068741[/C][C]-0.6735[/C][C]0.251117[/C][/ROW]
[ROW][C]25[/C][C]-0.059147[/C][C]-0.5795[/C][C]0.281799[/C][/ROW]
[ROW][C]26[/C][C]-0.059967[/C][C]-0.5875[/C][C]0.279107[/C][/ROW]
[ROW][C]27[/C][C]0.075157[/C][C]0.7364[/C][C]0.231647[/C][/ROW]
[ROW][C]28[/C][C]-0.002602[/C][C]-0.0255[/C][C]0.489856[/C][/ROW]
[ROW][C]29[/C][C]-0.071783[/C][C]-0.7033[/C][C]0.241777[/C][/ROW]
[ROW][C]30[/C][C]0.078813[/C][C]0.7722[/C][C]0.220944[/C][/ROW]
[ROW][C]31[/C][C]0.00667[/C][C]0.0654[/C][C]0.474014[/C][/ROW]
[ROW][C]32[/C][C]-0.087903[/C][C]-0.8613[/C][C]0.195619[/C][/ROW]
[ROW][C]33[/C][C]-0.006317[/C][C]-0.0619[/C][C]0.475389[/C][/ROW]
[ROW][C]34[/C][C]0.0337[/C][C]0.3302[/C][C]0.370986[/C][/ROW]
[ROW][C]35[/C][C]-0.027659[/C][C]-0.271[/C][C]0.393485[/C][/ROW]
[ROW][C]36[/C][C]0.029656[/C][C]0.2906[/C][C]0.386006[/C][/ROW]
[ROW][C]37[/C][C]-0.01611[/C][C]-0.1578[/C][C]0.437455[/C][/ROW]
[ROW][C]38[/C][C]-0.078736[/C][C]-0.7715[/C][C]0.221167[/C][/ROW]
[ROW][C]39[/C][C]0.064899[/C][C]0.6359[/C][C]0.263185[/C][/ROW]
[ROW][C]40[/C][C]0.002144[/C][C]0.021[/C][C]0.491641[/C][/ROW]
[ROW][C]41[/C][C]0.00693[/C][C]0.0679[/C][C]0.473002[/C][/ROW]
[ROW][C]42[/C][C]0.007285[/C][C]0.0714[/C][C]0.471622[/C][/ROW]
[ROW][C]43[/C][C]0.003713[/C][C]0.0364[/C][C]0.485529[/C][/ROW]
[ROW][C]44[/C][C]-0.08288[/C][C]-0.8121[/C][C]0.209384[/C][/ROW]
[ROW][C]45[/C][C]0.097988[/C][C]0.9601[/C][C]0.169713[/C][/ROW]
[ROW][C]46[/C][C]-0.009623[/C][C]-0.0943[/C][C]0.462539[/C][/ROW]
[ROW][C]47[/C][C]-0.031594[/C][C]-0.3096[/C][C]0.378783[/C][/ROW]
[ROW][C]48[/C][C]-0.016758[/C][C]-0.1642[/C][C]0.434962[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104573&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104573&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
10.73477.19860
2-0.331793-3.25090.000794
3-0.329898-3.23230.000842
4-0.51606-5.05631e-06
5-0.311301-3.05010.001478
6-0.178836-1.75220.041464
7-0.267022-2.61630.005163
8-0.034569-0.33870.367784
90.0402710.39460.347018
10-0.193038-1.89140.030794
110.1601281.56890.059978
120.339613.32750.000622
13-0.291879-2.85980.0026
140.0002840.00280.498892
150.0225610.22110.41276
160.2100632.05820.021141
170.0053670.05260.479086
18-0.076259-0.74720.228391
190.0482580.47280.318703
200.0179850.17620.430247
21-0.083135-0.81450.208673
220.0839440.82250.206421
230.1016570.9960.16087
24-0.068741-0.67350.251117
25-0.059147-0.57950.281799
26-0.059967-0.58750.279107
270.0751570.73640.231647
28-0.002602-0.02550.489856
29-0.071783-0.70330.241777
300.0788130.77220.220944
310.006670.06540.474014
32-0.087903-0.86130.195619
33-0.006317-0.06190.475389
340.03370.33020.370986
35-0.027659-0.2710.393485
360.0296560.29060.386006
37-0.01611-0.15780.437455
38-0.078736-0.77150.221167
390.0648990.63590.263185
400.0021440.0210.491641
410.006930.06790.473002
420.0072850.07140.471622
430.0037130.03640.485529
44-0.08288-0.81210.209384
450.0979880.96010.169713
46-0.009623-0.09430.462539
47-0.031594-0.30960.378783
48-0.016758-0.16420.434962



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 ;
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')