Free Statistics

of Irreproducible Research!

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, 27 Dec 2009 13:14:54 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/27/t12619451133l8jzmqh90b4j2y.htm/, Retrieved Thu, 02 May 2024 19:50:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70921, Retrieved Thu, 02 May 2024 19:50:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD    [(Partial) Autocorrelation Function] [ws9-3] [2009-12-04 20:43:56] [74be16979710d4c4e7c6647856088456]
-   P       [(Partial) Autocorrelation Function] [acf] [2009-12-27 19:56:57] [d8fc2cb19a73ee9b4ebccccec0f2ad7f]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-27 20:14:54] [58c0e7ecdfec19fc38e879e32991032d] [Current]
-   P             [(Partial) Autocorrelation Function] [acf3] [2009-12-28 09:37:04] [d8fc2cb19a73ee9b4ebccccec0f2ad7f]
- RMP             [Variance Reduction Matrix] [VRM] [2009-12-28 09:52:00] [d8fc2cb19a73ee9b4ebccccec0f2ad7f]
- RMP             [Spectral Analysis] [spectrum] [2009-12-28 10:19:24] [d8fc2cb19a73ee9b4ebccccec0f2ad7f]
-   P               [Spectral Analysis] [spectrum (2)] [2009-12-28 11:46:14] [d8fc2cb19a73ee9b4ebccccec0f2ad7f]
-   P               [Spectral Analysis] [spectrum (2)] [2009-12-28 11:56:24] [d8fc2cb19a73ee9b4ebccccec0f2ad7f]
Feedback Forum

Post a new message
Dataseries X:
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2260
2498
2695
2799
2947
2930
2318
2540
2570
2669
2450
2842
3440
2678
2981
2260
2844
2546
2456
2295
2379
2479
2057
2280
2351
2276
2548
2311
2201
2725
2408
2139
1898
2537
2069
2063
2524
2437
2189
2793
2074
2622
2278
2144
2427
2139
1828
2072
1800
1758
2246
1987
1868
2514
2121




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=70921&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=70921&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70921&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
1-0.531855-4.32082.7e-05
2-0.005718-0.04650.481544
30.1712281.39110.084439
4-0.062148-0.50490.307659
5-0.072195-0.58650.279766
60.009010.07320.470935
7-0.048134-0.3910.348511
80.0224010.1820.428075
90.0733180.59560.276727
10-0.073604-0.5980.275957
11-0.04353-0.35360.362368
120.1851461.50410.068659
13-0.163781-1.33060.093956
140.0378010.30710.379868
150.0919420.74690.228875
16-0.15447-1.25490.106967
170.1497971.2170.113977
18-0.124189-1.00890.15835
190.077440.62910.265721
20-0.133494-1.08450.141041
210.1678751.36380.088628
22-0.102958-0.83640.202964
23-0.059743-0.48540.314515
240.1301951.05770.147023
25-0.003166-0.02570.489779
26-0.070877-0.57580.283352
270.0885540.71940.237211
28-0.018529-0.15050.440404
29-0.027343-0.22210.412447
300.030430.24720.402754
31-0.073501-0.59710.276233
320.025460.20680.418386
330.0406680.33040.371077
340.0280920.22820.410089
35-0.172692-1.4030.082658
360.1746851.41920.08028
37-0.016142-0.13110.448034
38-0.096643-0.78510.217593
390.0622670.50590.30732
400.028360.23040.409248
41-0.040631-0.33010.371188
42-0.002464-0.020.492045
430.0293930.23880.406005
44-0.020903-0.16980.432837
45-0.092733-0.75340.226955
460.1479021.20160.116914
47-0.136185-1.10640.136292
480.0609650.49530.311022
490.0512440.41630.339268
50-0.094-0.76370.223897
510.1099060.89290.187582
52-0.039125-0.31790.375799
53-0.033477-0.2720.393246
540.080380.6530.25801
55-0.069213-0.56230.287913
56-0.032611-0.26490.395943
570.0821650.66750.253388
58-0.028041-0.22780.41025
59-0.095526-0.77610.220244
600.1336241.08560.14081

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.531855 & -4.3208 & 2.7e-05 \tabularnewline
2 & -0.005718 & -0.0465 & 0.481544 \tabularnewline
3 & 0.171228 & 1.3911 & 0.084439 \tabularnewline
4 & -0.062148 & -0.5049 & 0.307659 \tabularnewline
5 & -0.072195 & -0.5865 & 0.279766 \tabularnewline
6 & 0.00901 & 0.0732 & 0.470935 \tabularnewline
7 & -0.048134 & -0.391 & 0.348511 \tabularnewline
8 & 0.022401 & 0.182 & 0.428075 \tabularnewline
9 & 0.073318 & 0.5956 & 0.276727 \tabularnewline
10 & -0.073604 & -0.598 & 0.275957 \tabularnewline
11 & -0.04353 & -0.3536 & 0.362368 \tabularnewline
12 & 0.185146 & 1.5041 & 0.068659 \tabularnewline
13 & -0.163781 & -1.3306 & 0.093956 \tabularnewline
14 & 0.037801 & 0.3071 & 0.379868 \tabularnewline
15 & 0.091942 & 0.7469 & 0.228875 \tabularnewline
16 & -0.15447 & -1.2549 & 0.106967 \tabularnewline
17 & 0.149797 & 1.217 & 0.113977 \tabularnewline
18 & -0.124189 & -1.0089 & 0.15835 \tabularnewline
19 & 0.07744 & 0.6291 & 0.265721 \tabularnewline
20 & -0.133494 & -1.0845 & 0.141041 \tabularnewline
21 & 0.167875 & 1.3638 & 0.088628 \tabularnewline
22 & -0.102958 & -0.8364 & 0.202964 \tabularnewline
23 & -0.059743 & -0.4854 & 0.314515 \tabularnewline
24 & 0.130195 & 1.0577 & 0.147023 \tabularnewline
25 & -0.003166 & -0.0257 & 0.489779 \tabularnewline
26 & -0.070877 & -0.5758 & 0.283352 \tabularnewline
27 & 0.088554 & 0.7194 & 0.237211 \tabularnewline
28 & -0.018529 & -0.1505 & 0.440404 \tabularnewline
29 & -0.027343 & -0.2221 & 0.412447 \tabularnewline
30 & 0.03043 & 0.2472 & 0.402754 \tabularnewline
31 & -0.073501 & -0.5971 & 0.276233 \tabularnewline
32 & 0.02546 & 0.2068 & 0.418386 \tabularnewline
33 & 0.040668 & 0.3304 & 0.371077 \tabularnewline
34 & 0.028092 & 0.2282 & 0.410089 \tabularnewline
35 & -0.172692 & -1.403 & 0.082658 \tabularnewline
36 & 0.174685 & 1.4192 & 0.08028 \tabularnewline
37 & -0.016142 & -0.1311 & 0.448034 \tabularnewline
38 & -0.096643 & -0.7851 & 0.217593 \tabularnewline
39 & 0.062267 & 0.5059 & 0.30732 \tabularnewline
40 & 0.02836 & 0.2304 & 0.409248 \tabularnewline
41 & -0.040631 & -0.3301 & 0.371188 \tabularnewline
42 & -0.002464 & -0.02 & 0.492045 \tabularnewline
43 & 0.029393 & 0.2388 & 0.406005 \tabularnewline
44 & -0.020903 & -0.1698 & 0.432837 \tabularnewline
45 & -0.092733 & -0.7534 & 0.226955 \tabularnewline
46 & 0.147902 & 1.2016 & 0.116914 \tabularnewline
47 & -0.136185 & -1.1064 & 0.136292 \tabularnewline
48 & 0.060965 & 0.4953 & 0.311022 \tabularnewline
49 & 0.051244 & 0.4163 & 0.339268 \tabularnewline
50 & -0.094 & -0.7637 & 0.223897 \tabularnewline
51 & 0.109906 & 0.8929 & 0.187582 \tabularnewline
52 & -0.039125 & -0.3179 & 0.375799 \tabularnewline
53 & -0.033477 & -0.272 & 0.393246 \tabularnewline
54 & 0.08038 & 0.653 & 0.25801 \tabularnewline
55 & -0.069213 & -0.5623 & 0.287913 \tabularnewline
56 & -0.032611 & -0.2649 & 0.395943 \tabularnewline
57 & 0.082165 & 0.6675 & 0.253388 \tabularnewline
58 & -0.028041 & -0.2278 & 0.41025 \tabularnewline
59 & -0.095526 & -0.7761 & 0.220244 \tabularnewline
60 & 0.133624 & 1.0856 & 0.14081 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70921&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]-0.531855[/C][C]-4.3208[/C][C]2.7e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.005718[/C][C]-0.0465[/C][C]0.481544[/C][/ROW]
[ROW][C]3[/C][C]0.171228[/C][C]1.3911[/C][C]0.084439[/C][/ROW]
[ROW][C]4[/C][C]-0.062148[/C][C]-0.5049[/C][C]0.307659[/C][/ROW]
[ROW][C]5[/C][C]-0.072195[/C][C]-0.5865[/C][C]0.279766[/C][/ROW]
[ROW][C]6[/C][C]0.00901[/C][C]0.0732[/C][C]0.470935[/C][/ROW]
[ROW][C]7[/C][C]-0.048134[/C][C]-0.391[/C][C]0.348511[/C][/ROW]
[ROW][C]8[/C][C]0.022401[/C][C]0.182[/C][C]0.428075[/C][/ROW]
[ROW][C]9[/C][C]0.073318[/C][C]0.5956[/C][C]0.276727[/C][/ROW]
[ROW][C]10[/C][C]-0.073604[/C][C]-0.598[/C][C]0.275957[/C][/ROW]
[ROW][C]11[/C][C]-0.04353[/C][C]-0.3536[/C][C]0.362368[/C][/ROW]
[ROW][C]12[/C][C]0.185146[/C][C]1.5041[/C][C]0.068659[/C][/ROW]
[ROW][C]13[/C][C]-0.163781[/C][C]-1.3306[/C][C]0.093956[/C][/ROW]
[ROW][C]14[/C][C]0.037801[/C][C]0.3071[/C][C]0.379868[/C][/ROW]
[ROW][C]15[/C][C]0.091942[/C][C]0.7469[/C][C]0.228875[/C][/ROW]
[ROW][C]16[/C][C]-0.15447[/C][C]-1.2549[/C][C]0.106967[/C][/ROW]
[ROW][C]17[/C][C]0.149797[/C][C]1.217[/C][C]0.113977[/C][/ROW]
[ROW][C]18[/C][C]-0.124189[/C][C]-1.0089[/C][C]0.15835[/C][/ROW]
[ROW][C]19[/C][C]0.07744[/C][C]0.6291[/C][C]0.265721[/C][/ROW]
[ROW][C]20[/C][C]-0.133494[/C][C]-1.0845[/C][C]0.141041[/C][/ROW]
[ROW][C]21[/C][C]0.167875[/C][C]1.3638[/C][C]0.088628[/C][/ROW]
[ROW][C]22[/C][C]-0.102958[/C][C]-0.8364[/C][C]0.202964[/C][/ROW]
[ROW][C]23[/C][C]-0.059743[/C][C]-0.4854[/C][C]0.314515[/C][/ROW]
[ROW][C]24[/C][C]0.130195[/C][C]1.0577[/C][C]0.147023[/C][/ROW]
[ROW][C]25[/C][C]-0.003166[/C][C]-0.0257[/C][C]0.489779[/C][/ROW]
[ROW][C]26[/C][C]-0.070877[/C][C]-0.5758[/C][C]0.283352[/C][/ROW]
[ROW][C]27[/C][C]0.088554[/C][C]0.7194[/C][C]0.237211[/C][/ROW]
[ROW][C]28[/C][C]-0.018529[/C][C]-0.1505[/C][C]0.440404[/C][/ROW]
[ROW][C]29[/C][C]-0.027343[/C][C]-0.2221[/C][C]0.412447[/C][/ROW]
[ROW][C]30[/C][C]0.03043[/C][C]0.2472[/C][C]0.402754[/C][/ROW]
[ROW][C]31[/C][C]-0.073501[/C][C]-0.5971[/C][C]0.276233[/C][/ROW]
[ROW][C]32[/C][C]0.02546[/C][C]0.2068[/C][C]0.418386[/C][/ROW]
[ROW][C]33[/C][C]0.040668[/C][C]0.3304[/C][C]0.371077[/C][/ROW]
[ROW][C]34[/C][C]0.028092[/C][C]0.2282[/C][C]0.410089[/C][/ROW]
[ROW][C]35[/C][C]-0.172692[/C][C]-1.403[/C][C]0.082658[/C][/ROW]
[ROW][C]36[/C][C]0.174685[/C][C]1.4192[/C][C]0.08028[/C][/ROW]
[ROW][C]37[/C][C]-0.016142[/C][C]-0.1311[/C][C]0.448034[/C][/ROW]
[ROW][C]38[/C][C]-0.096643[/C][C]-0.7851[/C][C]0.217593[/C][/ROW]
[ROW][C]39[/C][C]0.062267[/C][C]0.5059[/C][C]0.30732[/C][/ROW]
[ROW][C]40[/C][C]0.02836[/C][C]0.2304[/C][C]0.409248[/C][/ROW]
[ROW][C]41[/C][C]-0.040631[/C][C]-0.3301[/C][C]0.371188[/C][/ROW]
[ROW][C]42[/C][C]-0.002464[/C][C]-0.02[/C][C]0.492045[/C][/ROW]
[ROW][C]43[/C][C]0.029393[/C][C]0.2388[/C][C]0.406005[/C][/ROW]
[ROW][C]44[/C][C]-0.020903[/C][C]-0.1698[/C][C]0.432837[/C][/ROW]
[ROW][C]45[/C][C]-0.092733[/C][C]-0.7534[/C][C]0.226955[/C][/ROW]
[ROW][C]46[/C][C]0.147902[/C][C]1.2016[/C][C]0.116914[/C][/ROW]
[ROW][C]47[/C][C]-0.136185[/C][C]-1.1064[/C][C]0.136292[/C][/ROW]
[ROW][C]48[/C][C]0.060965[/C][C]0.4953[/C][C]0.311022[/C][/ROW]
[ROW][C]49[/C][C]0.051244[/C][C]0.4163[/C][C]0.339268[/C][/ROW]
[ROW][C]50[/C][C]-0.094[/C][C]-0.7637[/C][C]0.223897[/C][/ROW]
[ROW][C]51[/C][C]0.109906[/C][C]0.8929[/C][C]0.187582[/C][/ROW]
[ROW][C]52[/C][C]-0.039125[/C][C]-0.3179[/C][C]0.375799[/C][/ROW]
[ROW][C]53[/C][C]-0.033477[/C][C]-0.272[/C][C]0.393246[/C][/ROW]
[ROW][C]54[/C][C]0.08038[/C][C]0.653[/C][C]0.25801[/C][/ROW]
[ROW][C]55[/C][C]-0.069213[/C][C]-0.5623[/C][C]0.287913[/C][/ROW]
[ROW][C]56[/C][C]-0.032611[/C][C]-0.2649[/C][C]0.395943[/C][/ROW]
[ROW][C]57[/C][C]0.082165[/C][C]0.6675[/C][C]0.253388[/C][/ROW]
[ROW][C]58[/C][C]-0.028041[/C][C]-0.2278[/C][C]0.41025[/C][/ROW]
[ROW][C]59[/C][C]-0.095526[/C][C]-0.7761[/C][C]0.220244[/C][/ROW]
[ROW][C]60[/C][C]0.133624[/C][C]1.0856[/C][C]0.14081[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70921&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70921&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
1-0.531855-4.32082.7e-05
2-0.005718-0.04650.481544
30.1712281.39110.084439
4-0.062148-0.50490.307659
5-0.072195-0.58650.279766
60.009010.07320.470935
7-0.048134-0.3910.348511
80.0224010.1820.428075
90.0733180.59560.276727
10-0.073604-0.5980.275957
11-0.04353-0.35360.362368
120.1851461.50410.068659
13-0.163781-1.33060.093956
140.0378010.30710.379868
150.0919420.74690.228875
16-0.15447-1.25490.106967
170.1497971.2170.113977
18-0.124189-1.00890.15835
190.077440.62910.265721
20-0.133494-1.08450.141041
210.1678751.36380.088628
22-0.102958-0.83640.202964
23-0.059743-0.48540.314515
240.1301951.05770.147023
25-0.003166-0.02570.489779
26-0.070877-0.57580.283352
270.0885540.71940.237211
28-0.018529-0.15050.440404
29-0.027343-0.22210.412447
300.030430.24720.402754
31-0.073501-0.59710.276233
320.025460.20680.418386
330.0406680.33040.371077
340.0280920.22820.410089
35-0.172692-1.4030.082658
360.1746851.41920.08028
37-0.016142-0.13110.448034
38-0.096643-0.78510.217593
390.0622670.50590.30732
400.028360.23040.409248
41-0.040631-0.33010.371188
42-0.002464-0.020.492045
430.0293930.23880.406005
44-0.020903-0.16980.432837
45-0.092733-0.75340.226955
460.1479021.20160.116914
47-0.136185-1.10640.136292
480.0609650.49530.311022
490.0512440.41630.339268
50-0.094-0.76370.223897
510.1099060.89290.187582
52-0.039125-0.31790.375799
53-0.033477-0.2720.393246
540.080380.6530.25801
55-0.069213-0.56230.287913
56-0.032611-0.26490.395943
570.0821650.66750.253388
58-0.028041-0.22780.41025
59-0.095526-0.77610.220244
600.1336241.08560.14081







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.531855-4.32082.7e-05
2-0.40242-3.26930.000857
3-0.078313-0.63620.263418
40.0446650.36290.358934
5-0.035902-0.29170.385728
6-0.139466-1.1330.130651
7-0.247358-2.00950.024286
8-0.204638-1.66250.050579
90.0150380.12220.451569
100.050590.4110.341204
11-0.125825-1.02220.155207
120.0080950.06580.473881
13-0.081934-0.66560.253982
14-0.04508-0.36620.357682
150.0884490.71860.237472
16-0.059534-0.48370.315115
170.0664270.53970.295624
18-0.092654-0.75270.227145
190.0293090.23810.406269
20-0.190824-1.55030.062931
21-0.007399-0.06010.476126
22-0.005513-0.04480.482207
23-0.134692-1.09420.138913
24-0.108396-0.88060.19086
250.0272650.22150.412692
260.0076560.06220.475296
270.0455020.36970.356409
280.0792040.64350.261078
29-0.030443-0.24730.402714
300.0300120.24380.404063
31-0.070055-0.56910.285599
320.0063260.05140.479583
330.0265310.21550.415007
340.185231.50480.068571
35-0.041368-0.33610.368941
36-0.141555-1.150.127147
370.0111770.09080.463963
38-0.02716-0.22060.413025
390.0293410.23840.406166
400.0332890.27040.393832
410.0273360.22210.412469
42-0.140633-1.14250.128686
43-0.005316-0.04320.482842
440.0729150.59240.277816
45-0.158993-1.29170.100489
46-0.032251-0.2620.397067
47-0.06625-0.53820.296118
48-0.041942-0.34070.367193
49-0.019293-0.15670.437966
500.0225670.18330.42755
51-0.032252-0.2620.397062
520.0001450.00120.499532
53-0.038258-0.31080.378462
540.06190.50290.308362
55-0.042567-0.34580.365292
56-0.013595-0.11040.456194
570.0701040.56950.285467
58-0.068776-0.55870.289115
59-0.049631-0.40320.34405
600.0007090.00580.49771

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.531855 & -4.3208 & 2.7e-05 \tabularnewline
2 & -0.40242 & -3.2693 & 0.000857 \tabularnewline
3 & -0.078313 & -0.6362 & 0.263418 \tabularnewline
4 & 0.044665 & 0.3629 & 0.358934 \tabularnewline
5 & -0.035902 & -0.2917 & 0.385728 \tabularnewline
6 & -0.139466 & -1.133 & 0.130651 \tabularnewline
7 & -0.247358 & -2.0095 & 0.024286 \tabularnewline
8 & -0.204638 & -1.6625 & 0.050579 \tabularnewline
9 & 0.015038 & 0.1222 & 0.451569 \tabularnewline
10 & 0.05059 & 0.411 & 0.341204 \tabularnewline
11 & -0.125825 & -1.0222 & 0.155207 \tabularnewline
12 & 0.008095 & 0.0658 & 0.473881 \tabularnewline
13 & -0.081934 & -0.6656 & 0.253982 \tabularnewline
14 & -0.04508 & -0.3662 & 0.357682 \tabularnewline
15 & 0.088449 & 0.7186 & 0.237472 \tabularnewline
16 & -0.059534 & -0.4837 & 0.315115 \tabularnewline
17 & 0.066427 & 0.5397 & 0.295624 \tabularnewline
18 & -0.092654 & -0.7527 & 0.227145 \tabularnewline
19 & 0.029309 & 0.2381 & 0.406269 \tabularnewline
20 & -0.190824 & -1.5503 & 0.062931 \tabularnewline
21 & -0.007399 & -0.0601 & 0.476126 \tabularnewline
22 & -0.005513 & -0.0448 & 0.482207 \tabularnewline
23 & -0.134692 & -1.0942 & 0.138913 \tabularnewline
24 & -0.108396 & -0.8806 & 0.19086 \tabularnewline
25 & 0.027265 & 0.2215 & 0.412692 \tabularnewline
26 & 0.007656 & 0.0622 & 0.475296 \tabularnewline
27 & 0.045502 & 0.3697 & 0.356409 \tabularnewline
28 & 0.079204 & 0.6435 & 0.261078 \tabularnewline
29 & -0.030443 & -0.2473 & 0.402714 \tabularnewline
30 & 0.030012 & 0.2438 & 0.404063 \tabularnewline
31 & -0.070055 & -0.5691 & 0.285599 \tabularnewline
32 & 0.006326 & 0.0514 & 0.479583 \tabularnewline
33 & 0.026531 & 0.2155 & 0.415007 \tabularnewline
34 & 0.18523 & 1.5048 & 0.068571 \tabularnewline
35 & -0.041368 & -0.3361 & 0.368941 \tabularnewline
36 & -0.141555 & -1.15 & 0.127147 \tabularnewline
37 & 0.011177 & 0.0908 & 0.463963 \tabularnewline
38 & -0.02716 & -0.2206 & 0.413025 \tabularnewline
39 & 0.029341 & 0.2384 & 0.406166 \tabularnewline
40 & 0.033289 & 0.2704 & 0.393832 \tabularnewline
41 & 0.027336 & 0.2221 & 0.412469 \tabularnewline
42 & -0.140633 & -1.1425 & 0.128686 \tabularnewline
43 & -0.005316 & -0.0432 & 0.482842 \tabularnewline
44 & 0.072915 & 0.5924 & 0.277816 \tabularnewline
45 & -0.158993 & -1.2917 & 0.100489 \tabularnewline
46 & -0.032251 & -0.262 & 0.397067 \tabularnewline
47 & -0.06625 & -0.5382 & 0.296118 \tabularnewline
48 & -0.041942 & -0.3407 & 0.367193 \tabularnewline
49 & -0.019293 & -0.1567 & 0.437966 \tabularnewline
50 & 0.022567 & 0.1833 & 0.42755 \tabularnewline
51 & -0.032252 & -0.262 & 0.397062 \tabularnewline
52 & 0.000145 & 0.0012 & 0.499532 \tabularnewline
53 & -0.038258 & -0.3108 & 0.378462 \tabularnewline
54 & 0.0619 & 0.5029 & 0.308362 \tabularnewline
55 & -0.042567 & -0.3458 & 0.365292 \tabularnewline
56 & -0.013595 & -0.1104 & 0.456194 \tabularnewline
57 & 0.070104 & 0.5695 & 0.285467 \tabularnewline
58 & -0.068776 & -0.5587 & 0.289115 \tabularnewline
59 & -0.049631 & -0.4032 & 0.34405 \tabularnewline
60 & 0.000709 & 0.0058 & 0.49771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70921&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]-0.531855[/C][C]-4.3208[/C][C]2.7e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.40242[/C][C]-3.2693[/C][C]0.000857[/C][/ROW]
[ROW][C]3[/C][C]-0.078313[/C][C]-0.6362[/C][C]0.263418[/C][/ROW]
[ROW][C]4[/C][C]0.044665[/C][C]0.3629[/C][C]0.358934[/C][/ROW]
[ROW][C]5[/C][C]-0.035902[/C][C]-0.2917[/C][C]0.385728[/C][/ROW]
[ROW][C]6[/C][C]-0.139466[/C][C]-1.133[/C][C]0.130651[/C][/ROW]
[ROW][C]7[/C][C]-0.247358[/C][C]-2.0095[/C][C]0.024286[/C][/ROW]
[ROW][C]8[/C][C]-0.204638[/C][C]-1.6625[/C][C]0.050579[/C][/ROW]
[ROW][C]9[/C][C]0.015038[/C][C]0.1222[/C][C]0.451569[/C][/ROW]
[ROW][C]10[/C][C]0.05059[/C][C]0.411[/C][C]0.341204[/C][/ROW]
[ROW][C]11[/C][C]-0.125825[/C][C]-1.0222[/C][C]0.155207[/C][/ROW]
[ROW][C]12[/C][C]0.008095[/C][C]0.0658[/C][C]0.473881[/C][/ROW]
[ROW][C]13[/C][C]-0.081934[/C][C]-0.6656[/C][C]0.253982[/C][/ROW]
[ROW][C]14[/C][C]-0.04508[/C][C]-0.3662[/C][C]0.357682[/C][/ROW]
[ROW][C]15[/C][C]0.088449[/C][C]0.7186[/C][C]0.237472[/C][/ROW]
[ROW][C]16[/C][C]-0.059534[/C][C]-0.4837[/C][C]0.315115[/C][/ROW]
[ROW][C]17[/C][C]0.066427[/C][C]0.5397[/C][C]0.295624[/C][/ROW]
[ROW][C]18[/C][C]-0.092654[/C][C]-0.7527[/C][C]0.227145[/C][/ROW]
[ROW][C]19[/C][C]0.029309[/C][C]0.2381[/C][C]0.406269[/C][/ROW]
[ROW][C]20[/C][C]-0.190824[/C][C]-1.5503[/C][C]0.062931[/C][/ROW]
[ROW][C]21[/C][C]-0.007399[/C][C]-0.0601[/C][C]0.476126[/C][/ROW]
[ROW][C]22[/C][C]-0.005513[/C][C]-0.0448[/C][C]0.482207[/C][/ROW]
[ROW][C]23[/C][C]-0.134692[/C][C]-1.0942[/C][C]0.138913[/C][/ROW]
[ROW][C]24[/C][C]-0.108396[/C][C]-0.8806[/C][C]0.19086[/C][/ROW]
[ROW][C]25[/C][C]0.027265[/C][C]0.2215[/C][C]0.412692[/C][/ROW]
[ROW][C]26[/C][C]0.007656[/C][C]0.0622[/C][C]0.475296[/C][/ROW]
[ROW][C]27[/C][C]0.045502[/C][C]0.3697[/C][C]0.356409[/C][/ROW]
[ROW][C]28[/C][C]0.079204[/C][C]0.6435[/C][C]0.261078[/C][/ROW]
[ROW][C]29[/C][C]-0.030443[/C][C]-0.2473[/C][C]0.402714[/C][/ROW]
[ROW][C]30[/C][C]0.030012[/C][C]0.2438[/C][C]0.404063[/C][/ROW]
[ROW][C]31[/C][C]-0.070055[/C][C]-0.5691[/C][C]0.285599[/C][/ROW]
[ROW][C]32[/C][C]0.006326[/C][C]0.0514[/C][C]0.479583[/C][/ROW]
[ROW][C]33[/C][C]0.026531[/C][C]0.2155[/C][C]0.415007[/C][/ROW]
[ROW][C]34[/C][C]0.18523[/C][C]1.5048[/C][C]0.068571[/C][/ROW]
[ROW][C]35[/C][C]-0.041368[/C][C]-0.3361[/C][C]0.368941[/C][/ROW]
[ROW][C]36[/C][C]-0.141555[/C][C]-1.15[/C][C]0.127147[/C][/ROW]
[ROW][C]37[/C][C]0.011177[/C][C]0.0908[/C][C]0.463963[/C][/ROW]
[ROW][C]38[/C][C]-0.02716[/C][C]-0.2206[/C][C]0.413025[/C][/ROW]
[ROW][C]39[/C][C]0.029341[/C][C]0.2384[/C][C]0.406166[/C][/ROW]
[ROW][C]40[/C][C]0.033289[/C][C]0.2704[/C][C]0.393832[/C][/ROW]
[ROW][C]41[/C][C]0.027336[/C][C]0.2221[/C][C]0.412469[/C][/ROW]
[ROW][C]42[/C][C]-0.140633[/C][C]-1.1425[/C][C]0.128686[/C][/ROW]
[ROW][C]43[/C][C]-0.005316[/C][C]-0.0432[/C][C]0.482842[/C][/ROW]
[ROW][C]44[/C][C]0.072915[/C][C]0.5924[/C][C]0.277816[/C][/ROW]
[ROW][C]45[/C][C]-0.158993[/C][C]-1.2917[/C][C]0.100489[/C][/ROW]
[ROW][C]46[/C][C]-0.032251[/C][C]-0.262[/C][C]0.397067[/C][/ROW]
[ROW][C]47[/C][C]-0.06625[/C][C]-0.5382[/C][C]0.296118[/C][/ROW]
[ROW][C]48[/C][C]-0.041942[/C][C]-0.3407[/C][C]0.367193[/C][/ROW]
[ROW][C]49[/C][C]-0.019293[/C][C]-0.1567[/C][C]0.437966[/C][/ROW]
[ROW][C]50[/C][C]0.022567[/C][C]0.1833[/C][C]0.42755[/C][/ROW]
[ROW][C]51[/C][C]-0.032252[/C][C]-0.262[/C][C]0.397062[/C][/ROW]
[ROW][C]52[/C][C]0.000145[/C][C]0.0012[/C][C]0.499532[/C][/ROW]
[ROW][C]53[/C][C]-0.038258[/C][C]-0.3108[/C][C]0.378462[/C][/ROW]
[ROW][C]54[/C][C]0.0619[/C][C]0.5029[/C][C]0.308362[/C][/ROW]
[ROW][C]55[/C][C]-0.042567[/C][C]-0.3458[/C][C]0.365292[/C][/ROW]
[ROW][C]56[/C][C]-0.013595[/C][C]-0.1104[/C][C]0.456194[/C][/ROW]
[ROW][C]57[/C][C]0.070104[/C][C]0.5695[/C][C]0.285467[/C][/ROW]
[ROW][C]58[/C][C]-0.068776[/C][C]-0.5587[/C][C]0.289115[/C][/ROW]
[ROW][C]59[/C][C]-0.049631[/C][C]-0.4032[/C][C]0.34405[/C][/ROW]
[ROW][C]60[/C][C]0.000709[/C][C]0.0058[/C][C]0.49771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70921&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70921&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
1-0.531855-4.32082.7e-05
2-0.40242-3.26930.000857
3-0.078313-0.63620.263418
40.0446650.36290.358934
5-0.035902-0.29170.385728
6-0.139466-1.1330.130651
7-0.247358-2.00950.024286
8-0.204638-1.66250.050579
90.0150380.12220.451569
100.050590.4110.341204
11-0.125825-1.02220.155207
120.0080950.06580.473881
13-0.081934-0.66560.253982
14-0.04508-0.36620.357682
150.0884490.71860.237472
16-0.059534-0.48370.315115
170.0664270.53970.295624
18-0.092654-0.75270.227145
190.0293090.23810.406269
20-0.190824-1.55030.062931
21-0.007399-0.06010.476126
22-0.005513-0.04480.482207
23-0.134692-1.09420.138913
24-0.108396-0.88060.19086
250.0272650.22150.412692
260.0076560.06220.475296
270.0455020.36970.356409
280.0792040.64350.261078
29-0.030443-0.24730.402714
300.0300120.24380.404063
31-0.070055-0.56910.285599
320.0063260.05140.479583
330.0265310.21550.415007
340.185231.50480.068571
35-0.041368-0.33610.368941
36-0.141555-1.150.127147
370.0111770.09080.463963
38-0.02716-0.22060.413025
390.0293410.23840.406166
400.0332890.27040.393832
410.0273360.22210.412469
42-0.140633-1.14250.128686
43-0.005316-0.04320.482842
440.0729150.59240.277816
45-0.158993-1.29170.100489
46-0.032251-0.2620.397067
47-0.06625-0.53820.296118
48-0.041942-0.34070.367193
49-0.019293-0.15670.437966
500.0225670.18330.42755
51-0.032252-0.2620.397062
520.0001450.00120.499532
53-0.038258-0.31080.378462
540.06190.50290.308362
55-0.042567-0.34580.365292
56-0.013595-0.11040.456194
570.0701040.56950.285467
58-0.068776-0.55870.289115
59-0.049631-0.40320.34405
600.0007090.00580.49771



Parameters (Session):
par1 = 60 ; par2 = 0.5 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 0.5 ; par3 = 1 ; 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')