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 computationSat, 18 Dec 2010 19:36:44 +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/18/t1292700907g4b2len1ygfbqp3.htm/, Retrieved Tue, 30 Apr 2024 03:09:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112173, Retrieved Tue, 30 Apr 2024 03:09:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174
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 09:09:37] [b98453cac15ba1066b407e146608df68]
F   PD    [(Partial) Autocorrelation Function] [Autocorrelation F...] [2010-12-03 09:44:21] [74deae64b71f9d77c839af86f7c687b5]
-   PD        [(Partial) Autocorrelation Function] [autocorrelatie fu...] [2010-12-18 19:36:44] [e665313c9926a9f4bdf6ad1ee5aefad6] [Current]
-               [(Partial) Autocorrelation Function] [autocorrelatiefun...] [2010-12-18 20:27:56] [74deae64b71f9d77c839af86f7c687b5]
Feedback Forum

Post a new message
Dataseries X:
101.76
102.37
102.38
102.86
102.87
102.92
102.95
103.02
104.08
104.16
104.24
104.33
104.73
104.86
105.03
105.62
105.63
105.63
105.94
106.61
107.69
107.78
107.93
108.48
108.14
108.48
108.48
108.89
108.93
109.21
109.47
109.80
111.73
111.85
112.12
112.15
112.17
112.67
112.80
113.44
113.53
114.53
114.51
115.05
116.67
117.07
116.92
117.00
117.02
117.35
117.36
117.82
117.88
118.24
118.50
118.80
119.76
120.09
120.16




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=112173&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=112173&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112173&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
1-0.085445-0.65070.258896
2-0.055124-0.41980.338088
3-0.067202-0.51180.305369
4-0.143598-1.09360.139323
50.0731970.55750.289681
6-0.223987-1.70580.046695
70.1568831.19480.118517
8-0.226304-1.72350.045064
90.0105390.08030.468153
10-0.087472-0.66620.253972
110.0060370.0460.481743
120.6199864.72178e-06
13-0.017474-0.13310.447295
14-0.094923-0.72290.236318
15-0.113106-0.86140.196285
16-0.199135-1.51660.067404
170.0650140.49510.311189
18-0.0974-0.74180.230607
190.080190.61070.27189
20-0.112186-0.85440.198204
210.0077580.05910.476544
220.0349640.26630.395485
23-0.100045-0.76190.224597
240.4205143.20250.001106
25-0.012932-0.09850.460944
26-0.043874-0.33410.369742
27-0.179168-1.36450.08884
28-0.138859-1.05750.14733
290.1194160.90940.183439
30-0.109672-0.83520.203507
310.0779230.59340.277595
32-0.07245-0.55180.291614
330.0483610.36830.356993
34-0.062528-0.47620.317861
35-0.067196-0.51170.305385
360.1964511.49610.070021
37-0.014363-0.10940.456636
38-0.049516-0.37710.353737
39-0.10005-0.7620.224587
40-0.031669-0.24120.405132
410.069990.5330.298027
42-0.027577-0.210.417193
430.0512970.39070.348739
440.0184160.14030.444473
45-0.00645-0.04910.480496
46-0.00751-0.05720.477295
47-0.024018-0.18290.42775
480.0788190.60030.275333

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.085445 & -0.6507 & 0.258896 \tabularnewline
2 & -0.055124 & -0.4198 & 0.338088 \tabularnewline
3 & -0.067202 & -0.5118 & 0.305369 \tabularnewline
4 & -0.143598 & -1.0936 & 0.139323 \tabularnewline
5 & 0.073197 & 0.5575 & 0.289681 \tabularnewline
6 & -0.223987 & -1.7058 & 0.046695 \tabularnewline
7 & 0.156883 & 1.1948 & 0.118517 \tabularnewline
8 & -0.226304 & -1.7235 & 0.045064 \tabularnewline
9 & 0.010539 & 0.0803 & 0.468153 \tabularnewline
10 & -0.087472 & -0.6662 & 0.253972 \tabularnewline
11 & 0.006037 & 0.046 & 0.481743 \tabularnewline
12 & 0.619986 & 4.7217 & 8e-06 \tabularnewline
13 & -0.017474 & -0.1331 & 0.447295 \tabularnewline
14 & -0.094923 & -0.7229 & 0.236318 \tabularnewline
15 & -0.113106 & -0.8614 & 0.196285 \tabularnewline
16 & -0.199135 & -1.5166 & 0.067404 \tabularnewline
17 & 0.065014 & 0.4951 & 0.311189 \tabularnewline
18 & -0.0974 & -0.7418 & 0.230607 \tabularnewline
19 & 0.08019 & 0.6107 & 0.27189 \tabularnewline
20 & -0.112186 & -0.8544 & 0.198204 \tabularnewline
21 & 0.007758 & 0.0591 & 0.476544 \tabularnewline
22 & 0.034964 & 0.2663 & 0.395485 \tabularnewline
23 & -0.100045 & -0.7619 & 0.224597 \tabularnewline
24 & 0.420514 & 3.2025 & 0.001106 \tabularnewline
25 & -0.012932 & -0.0985 & 0.460944 \tabularnewline
26 & -0.043874 & -0.3341 & 0.369742 \tabularnewline
27 & -0.179168 & -1.3645 & 0.08884 \tabularnewline
28 & -0.138859 & -1.0575 & 0.14733 \tabularnewline
29 & 0.119416 & 0.9094 & 0.183439 \tabularnewline
30 & -0.109672 & -0.8352 & 0.203507 \tabularnewline
31 & 0.077923 & 0.5934 & 0.277595 \tabularnewline
32 & -0.07245 & -0.5518 & 0.291614 \tabularnewline
33 & 0.048361 & 0.3683 & 0.356993 \tabularnewline
34 & -0.062528 & -0.4762 & 0.317861 \tabularnewline
35 & -0.067196 & -0.5117 & 0.305385 \tabularnewline
36 & 0.196451 & 1.4961 & 0.070021 \tabularnewline
37 & -0.014363 & -0.1094 & 0.456636 \tabularnewline
38 & -0.049516 & -0.3771 & 0.353737 \tabularnewline
39 & -0.10005 & -0.762 & 0.224587 \tabularnewline
40 & -0.031669 & -0.2412 & 0.405132 \tabularnewline
41 & 0.06999 & 0.533 & 0.298027 \tabularnewline
42 & -0.027577 & -0.21 & 0.417193 \tabularnewline
43 & 0.051297 & 0.3907 & 0.348739 \tabularnewline
44 & 0.018416 & 0.1403 & 0.444473 \tabularnewline
45 & -0.00645 & -0.0491 & 0.480496 \tabularnewline
46 & -0.00751 & -0.0572 & 0.477295 \tabularnewline
47 & -0.024018 & -0.1829 & 0.42775 \tabularnewline
48 & 0.078819 & 0.6003 & 0.275333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112173&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]-0.085445[/C][C]-0.6507[/C][C]0.258896[/C][/ROW]
[ROW][C]2[/C][C]-0.055124[/C][C]-0.4198[/C][C]0.338088[/C][/ROW]
[ROW][C]3[/C][C]-0.067202[/C][C]-0.5118[/C][C]0.305369[/C][/ROW]
[ROW][C]4[/C][C]-0.143598[/C][C]-1.0936[/C][C]0.139323[/C][/ROW]
[ROW][C]5[/C][C]0.073197[/C][C]0.5575[/C][C]0.289681[/C][/ROW]
[ROW][C]6[/C][C]-0.223987[/C][C]-1.7058[/C][C]0.046695[/C][/ROW]
[ROW][C]7[/C][C]0.156883[/C][C]1.1948[/C][C]0.118517[/C][/ROW]
[ROW][C]8[/C][C]-0.226304[/C][C]-1.7235[/C][C]0.045064[/C][/ROW]
[ROW][C]9[/C][C]0.010539[/C][C]0.0803[/C][C]0.468153[/C][/ROW]
[ROW][C]10[/C][C]-0.087472[/C][C]-0.6662[/C][C]0.253972[/C][/ROW]
[ROW][C]11[/C][C]0.006037[/C][C]0.046[/C][C]0.481743[/C][/ROW]
[ROW][C]12[/C][C]0.619986[/C][C]4.7217[/C][C]8e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.017474[/C][C]-0.1331[/C][C]0.447295[/C][/ROW]
[ROW][C]14[/C][C]-0.094923[/C][C]-0.7229[/C][C]0.236318[/C][/ROW]
[ROW][C]15[/C][C]-0.113106[/C][C]-0.8614[/C][C]0.196285[/C][/ROW]
[ROW][C]16[/C][C]-0.199135[/C][C]-1.5166[/C][C]0.067404[/C][/ROW]
[ROW][C]17[/C][C]0.065014[/C][C]0.4951[/C][C]0.311189[/C][/ROW]
[ROW][C]18[/C][C]-0.0974[/C][C]-0.7418[/C][C]0.230607[/C][/ROW]
[ROW][C]19[/C][C]0.08019[/C][C]0.6107[/C][C]0.27189[/C][/ROW]
[ROW][C]20[/C][C]-0.112186[/C][C]-0.8544[/C][C]0.198204[/C][/ROW]
[ROW][C]21[/C][C]0.007758[/C][C]0.0591[/C][C]0.476544[/C][/ROW]
[ROW][C]22[/C][C]0.034964[/C][C]0.2663[/C][C]0.395485[/C][/ROW]
[ROW][C]23[/C][C]-0.100045[/C][C]-0.7619[/C][C]0.224597[/C][/ROW]
[ROW][C]24[/C][C]0.420514[/C][C]3.2025[/C][C]0.001106[/C][/ROW]
[ROW][C]25[/C][C]-0.012932[/C][C]-0.0985[/C][C]0.460944[/C][/ROW]
[ROW][C]26[/C][C]-0.043874[/C][C]-0.3341[/C][C]0.369742[/C][/ROW]
[ROW][C]27[/C][C]-0.179168[/C][C]-1.3645[/C][C]0.08884[/C][/ROW]
[ROW][C]28[/C][C]-0.138859[/C][C]-1.0575[/C][C]0.14733[/C][/ROW]
[ROW][C]29[/C][C]0.119416[/C][C]0.9094[/C][C]0.183439[/C][/ROW]
[ROW][C]30[/C][C]-0.109672[/C][C]-0.8352[/C][C]0.203507[/C][/ROW]
[ROW][C]31[/C][C]0.077923[/C][C]0.5934[/C][C]0.277595[/C][/ROW]
[ROW][C]32[/C][C]-0.07245[/C][C]-0.5518[/C][C]0.291614[/C][/ROW]
[ROW][C]33[/C][C]0.048361[/C][C]0.3683[/C][C]0.356993[/C][/ROW]
[ROW][C]34[/C][C]-0.062528[/C][C]-0.4762[/C][C]0.317861[/C][/ROW]
[ROW][C]35[/C][C]-0.067196[/C][C]-0.5117[/C][C]0.305385[/C][/ROW]
[ROW][C]36[/C][C]0.196451[/C][C]1.4961[/C][C]0.070021[/C][/ROW]
[ROW][C]37[/C][C]-0.014363[/C][C]-0.1094[/C][C]0.456636[/C][/ROW]
[ROW][C]38[/C][C]-0.049516[/C][C]-0.3771[/C][C]0.353737[/C][/ROW]
[ROW][C]39[/C][C]-0.10005[/C][C]-0.762[/C][C]0.224587[/C][/ROW]
[ROW][C]40[/C][C]-0.031669[/C][C]-0.2412[/C][C]0.405132[/C][/ROW]
[ROW][C]41[/C][C]0.06999[/C][C]0.533[/C][C]0.298027[/C][/ROW]
[ROW][C]42[/C][C]-0.027577[/C][C]-0.21[/C][C]0.417193[/C][/ROW]
[ROW][C]43[/C][C]0.051297[/C][C]0.3907[/C][C]0.348739[/C][/ROW]
[ROW][C]44[/C][C]0.018416[/C][C]0.1403[/C][C]0.444473[/C][/ROW]
[ROW][C]45[/C][C]-0.00645[/C][C]-0.0491[/C][C]0.480496[/C][/ROW]
[ROW][C]46[/C][C]-0.00751[/C][C]-0.0572[/C][C]0.477295[/C][/ROW]
[ROW][C]47[/C][C]-0.024018[/C][C]-0.1829[/C][C]0.42775[/C][/ROW]
[ROW][C]48[/C][C]0.078819[/C][C]0.6003[/C][C]0.275333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112173&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112173&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
1-0.085445-0.65070.258896
2-0.055124-0.41980.338088
3-0.067202-0.51180.305369
4-0.143598-1.09360.139323
50.0731970.55750.289681
6-0.223987-1.70580.046695
70.1568831.19480.118517
8-0.226304-1.72350.045064
90.0105390.08030.468153
10-0.087472-0.66620.253972
110.0060370.0460.481743
120.6199864.72178e-06
13-0.017474-0.13310.447295
14-0.094923-0.72290.236318
15-0.113106-0.86140.196285
16-0.199135-1.51660.067404
170.0650140.49510.311189
18-0.0974-0.74180.230607
190.080190.61070.27189
20-0.112186-0.85440.198204
210.0077580.05910.476544
220.0349640.26630.395485
23-0.100045-0.76190.224597
240.4205143.20250.001106
25-0.012932-0.09850.460944
26-0.043874-0.33410.369742
27-0.179168-1.36450.08884
28-0.138859-1.05750.14733
290.1194160.90940.183439
30-0.109672-0.83520.203507
310.0779230.59340.277595
32-0.07245-0.55180.291614
330.0483610.36830.356993
34-0.062528-0.47620.317861
35-0.067196-0.51170.305385
360.1964511.49610.070021
37-0.014363-0.10940.456636
38-0.049516-0.37710.353737
39-0.10005-0.7620.224587
40-0.031669-0.24120.405132
410.069990.5330.298027
42-0.027577-0.210.417193
430.0512970.39070.348739
440.0184160.14030.444473
45-0.00645-0.04910.480496
46-0.00751-0.05720.477295
47-0.024018-0.18290.42775
480.0788190.60030.275333







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.085445-0.65070.258896
2-0.062884-0.47890.316903
3-0.078462-0.59750.276234
4-0.163426-1.24460.10914
50.0344830.26260.396889
6-0.250888-1.91070.030495
70.1061370.80830.211105
8-0.296253-2.25620.013922
9-0.014792-0.11270.455347
10-0.266325-2.02830.023567
110.0228090.17370.431351
120.5186743.95010.000107
130.1770191.34810.091428
14-0.167202-1.27340.103983
150.0073620.05610.477741
16-0.324624-2.47230.00819
170.0951340.72450.23583
180.0370110.28190.389525
19-0.038914-0.29640.384006
200.0537780.40960.341818
210.0499330.38030.352565
220.0476530.36290.358993
23-0.10757-0.81920.208004
24-0.154429-1.17610.122181
25-0.02795-0.21290.416092
260.0859870.65490.257575
27-0.068872-0.52450.300961
280.1651961.25810.1067
290.0218250.16620.434284
30-0.089615-0.68250.248825
31-0.087152-0.66370.254748
32-0.047083-0.35860.360609
33-0.083029-0.63230.264828
34-0.090875-0.69210.245822
35-0.024117-0.18370.427456
36-0.079114-0.60250.27459
37-0.057368-0.43690.331903
38-0.085144-0.64840.25963
390.0482530.36750.357299
400.0501860.38220.351854
41-0.048366-0.36830.356978
42-0.012383-0.09430.462595
43-0.014059-0.10710.457551
44-0.019085-0.14540.442469
450.0392530.29890.383027
460.0229910.17510.430807
470.1212830.92370.179743
480.0481150.36640.357688

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.085445 & -0.6507 & 0.258896 \tabularnewline
2 & -0.062884 & -0.4789 & 0.316903 \tabularnewline
3 & -0.078462 & -0.5975 & 0.276234 \tabularnewline
4 & -0.163426 & -1.2446 & 0.10914 \tabularnewline
5 & 0.034483 & 0.2626 & 0.396889 \tabularnewline
6 & -0.250888 & -1.9107 & 0.030495 \tabularnewline
7 & 0.106137 & 0.8083 & 0.211105 \tabularnewline
8 & -0.296253 & -2.2562 & 0.013922 \tabularnewline
9 & -0.014792 & -0.1127 & 0.455347 \tabularnewline
10 & -0.266325 & -2.0283 & 0.023567 \tabularnewline
11 & 0.022809 & 0.1737 & 0.431351 \tabularnewline
12 & 0.518674 & 3.9501 & 0.000107 \tabularnewline
13 & 0.177019 & 1.3481 & 0.091428 \tabularnewline
14 & -0.167202 & -1.2734 & 0.103983 \tabularnewline
15 & 0.007362 & 0.0561 & 0.477741 \tabularnewline
16 & -0.324624 & -2.4723 & 0.00819 \tabularnewline
17 & 0.095134 & 0.7245 & 0.23583 \tabularnewline
18 & 0.037011 & 0.2819 & 0.389525 \tabularnewline
19 & -0.038914 & -0.2964 & 0.384006 \tabularnewline
20 & 0.053778 & 0.4096 & 0.341818 \tabularnewline
21 & 0.049933 & 0.3803 & 0.352565 \tabularnewline
22 & 0.047653 & 0.3629 & 0.358993 \tabularnewline
23 & -0.10757 & -0.8192 & 0.208004 \tabularnewline
24 & -0.154429 & -1.1761 & 0.122181 \tabularnewline
25 & -0.02795 & -0.2129 & 0.416092 \tabularnewline
26 & 0.085987 & 0.6549 & 0.257575 \tabularnewline
27 & -0.068872 & -0.5245 & 0.300961 \tabularnewline
28 & 0.165196 & 1.2581 & 0.1067 \tabularnewline
29 & 0.021825 & 0.1662 & 0.434284 \tabularnewline
30 & -0.089615 & -0.6825 & 0.248825 \tabularnewline
31 & -0.087152 & -0.6637 & 0.254748 \tabularnewline
32 & -0.047083 & -0.3586 & 0.360609 \tabularnewline
33 & -0.083029 & -0.6323 & 0.264828 \tabularnewline
34 & -0.090875 & -0.6921 & 0.245822 \tabularnewline
35 & -0.024117 & -0.1837 & 0.427456 \tabularnewline
36 & -0.079114 & -0.6025 & 0.27459 \tabularnewline
37 & -0.057368 & -0.4369 & 0.331903 \tabularnewline
38 & -0.085144 & -0.6484 & 0.25963 \tabularnewline
39 & 0.048253 & 0.3675 & 0.357299 \tabularnewline
40 & 0.050186 & 0.3822 & 0.351854 \tabularnewline
41 & -0.048366 & -0.3683 & 0.356978 \tabularnewline
42 & -0.012383 & -0.0943 & 0.462595 \tabularnewline
43 & -0.014059 & -0.1071 & 0.457551 \tabularnewline
44 & -0.019085 & -0.1454 & 0.442469 \tabularnewline
45 & 0.039253 & 0.2989 & 0.383027 \tabularnewline
46 & 0.022991 & 0.1751 & 0.430807 \tabularnewline
47 & 0.121283 & 0.9237 & 0.179743 \tabularnewline
48 & 0.048115 & 0.3664 & 0.357688 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112173&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]-0.085445[/C][C]-0.6507[/C][C]0.258896[/C][/ROW]
[ROW][C]2[/C][C]-0.062884[/C][C]-0.4789[/C][C]0.316903[/C][/ROW]
[ROW][C]3[/C][C]-0.078462[/C][C]-0.5975[/C][C]0.276234[/C][/ROW]
[ROW][C]4[/C][C]-0.163426[/C][C]-1.2446[/C][C]0.10914[/C][/ROW]
[ROW][C]5[/C][C]0.034483[/C][C]0.2626[/C][C]0.396889[/C][/ROW]
[ROW][C]6[/C][C]-0.250888[/C][C]-1.9107[/C][C]0.030495[/C][/ROW]
[ROW][C]7[/C][C]0.106137[/C][C]0.8083[/C][C]0.211105[/C][/ROW]
[ROW][C]8[/C][C]-0.296253[/C][C]-2.2562[/C][C]0.013922[/C][/ROW]
[ROW][C]9[/C][C]-0.014792[/C][C]-0.1127[/C][C]0.455347[/C][/ROW]
[ROW][C]10[/C][C]-0.266325[/C][C]-2.0283[/C][C]0.023567[/C][/ROW]
[ROW][C]11[/C][C]0.022809[/C][C]0.1737[/C][C]0.431351[/C][/ROW]
[ROW][C]12[/C][C]0.518674[/C][C]3.9501[/C][C]0.000107[/C][/ROW]
[ROW][C]13[/C][C]0.177019[/C][C]1.3481[/C][C]0.091428[/C][/ROW]
[ROW][C]14[/C][C]-0.167202[/C][C]-1.2734[/C][C]0.103983[/C][/ROW]
[ROW][C]15[/C][C]0.007362[/C][C]0.0561[/C][C]0.477741[/C][/ROW]
[ROW][C]16[/C][C]-0.324624[/C][C]-2.4723[/C][C]0.00819[/C][/ROW]
[ROW][C]17[/C][C]0.095134[/C][C]0.7245[/C][C]0.23583[/C][/ROW]
[ROW][C]18[/C][C]0.037011[/C][C]0.2819[/C][C]0.389525[/C][/ROW]
[ROW][C]19[/C][C]-0.038914[/C][C]-0.2964[/C][C]0.384006[/C][/ROW]
[ROW][C]20[/C][C]0.053778[/C][C]0.4096[/C][C]0.341818[/C][/ROW]
[ROW][C]21[/C][C]0.049933[/C][C]0.3803[/C][C]0.352565[/C][/ROW]
[ROW][C]22[/C][C]0.047653[/C][C]0.3629[/C][C]0.358993[/C][/ROW]
[ROW][C]23[/C][C]-0.10757[/C][C]-0.8192[/C][C]0.208004[/C][/ROW]
[ROW][C]24[/C][C]-0.154429[/C][C]-1.1761[/C][C]0.122181[/C][/ROW]
[ROW][C]25[/C][C]-0.02795[/C][C]-0.2129[/C][C]0.416092[/C][/ROW]
[ROW][C]26[/C][C]0.085987[/C][C]0.6549[/C][C]0.257575[/C][/ROW]
[ROW][C]27[/C][C]-0.068872[/C][C]-0.5245[/C][C]0.300961[/C][/ROW]
[ROW][C]28[/C][C]0.165196[/C][C]1.2581[/C][C]0.1067[/C][/ROW]
[ROW][C]29[/C][C]0.021825[/C][C]0.1662[/C][C]0.434284[/C][/ROW]
[ROW][C]30[/C][C]-0.089615[/C][C]-0.6825[/C][C]0.248825[/C][/ROW]
[ROW][C]31[/C][C]-0.087152[/C][C]-0.6637[/C][C]0.254748[/C][/ROW]
[ROW][C]32[/C][C]-0.047083[/C][C]-0.3586[/C][C]0.360609[/C][/ROW]
[ROW][C]33[/C][C]-0.083029[/C][C]-0.6323[/C][C]0.264828[/C][/ROW]
[ROW][C]34[/C][C]-0.090875[/C][C]-0.6921[/C][C]0.245822[/C][/ROW]
[ROW][C]35[/C][C]-0.024117[/C][C]-0.1837[/C][C]0.427456[/C][/ROW]
[ROW][C]36[/C][C]-0.079114[/C][C]-0.6025[/C][C]0.27459[/C][/ROW]
[ROW][C]37[/C][C]-0.057368[/C][C]-0.4369[/C][C]0.331903[/C][/ROW]
[ROW][C]38[/C][C]-0.085144[/C][C]-0.6484[/C][C]0.25963[/C][/ROW]
[ROW][C]39[/C][C]0.048253[/C][C]0.3675[/C][C]0.357299[/C][/ROW]
[ROW][C]40[/C][C]0.050186[/C][C]0.3822[/C][C]0.351854[/C][/ROW]
[ROW][C]41[/C][C]-0.048366[/C][C]-0.3683[/C][C]0.356978[/C][/ROW]
[ROW][C]42[/C][C]-0.012383[/C][C]-0.0943[/C][C]0.462595[/C][/ROW]
[ROW][C]43[/C][C]-0.014059[/C][C]-0.1071[/C][C]0.457551[/C][/ROW]
[ROW][C]44[/C][C]-0.019085[/C][C]-0.1454[/C][C]0.442469[/C][/ROW]
[ROW][C]45[/C][C]0.039253[/C][C]0.2989[/C][C]0.383027[/C][/ROW]
[ROW][C]46[/C][C]0.022991[/C][C]0.1751[/C][C]0.430807[/C][/ROW]
[ROW][C]47[/C][C]0.121283[/C][C]0.9237[/C][C]0.179743[/C][/ROW]
[ROW][C]48[/C][C]0.048115[/C][C]0.3664[/C][C]0.357688[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112173&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112173&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
1-0.085445-0.65070.258896
2-0.062884-0.47890.316903
3-0.078462-0.59750.276234
4-0.163426-1.24460.10914
50.0344830.26260.396889
6-0.250888-1.91070.030495
70.1061370.80830.211105
8-0.296253-2.25620.013922
9-0.014792-0.11270.455347
10-0.266325-2.02830.023567
110.0228090.17370.431351
120.5186743.95010.000107
130.1770191.34810.091428
14-0.167202-1.27340.103983
150.0073620.05610.477741
16-0.324624-2.47230.00819
170.0951340.72450.23583
180.0370110.28190.389525
19-0.038914-0.29640.384006
200.0537780.40960.341818
210.0499330.38030.352565
220.0476530.36290.358993
23-0.10757-0.81920.208004
24-0.154429-1.17610.122181
25-0.02795-0.21290.416092
260.0859870.65490.257575
27-0.068872-0.52450.300961
280.1651961.25810.1067
290.0218250.16620.434284
30-0.089615-0.68250.248825
31-0.087152-0.66370.254748
32-0.047083-0.35860.360609
33-0.083029-0.63230.264828
34-0.090875-0.69210.245822
35-0.024117-0.18370.427456
36-0.079114-0.60250.27459
37-0.057368-0.43690.331903
38-0.085144-0.64840.25963
390.0482530.36750.357299
400.0501860.38220.351854
41-0.048366-0.36830.356978
42-0.012383-0.09430.462595
43-0.014059-0.10710.457551
44-0.019085-0.14540.442469
450.0392530.29890.383027
460.0229910.17510.430807
470.1212830.92370.179743
480.0481150.36640.357688



Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; 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')