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, 19 Dec 2010 10:56:45 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t129275628816p3zjru5slpj3d.htm/, Retrieved Sat, 04 May 2024 23:15:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112276, Retrieved Sat, 04 May 2024 23:15:38 +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] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [Ws 9 - ACF] [2010-12-05 13:32:17] [603e2f5305d3a2a4e062624458fa1155]
-   PD        [(Partial) Autocorrelation Function] [PAPER - ACF] [2010-12-19 10:56:45] [0829c729852d8a4b1b0c41cf0848af95] [Current]
-   P           [(Partial) Autocorrelation Function] [PAPER - ACF (2)] [2010-12-21 13:48:18] [603e2f5305d3a2a4e062624458fa1155]
Feedback Forum

Post a new message
Dataseries X:
104.37
104.89
105.15
105.72
106.38
106.40
106.47
106.59
106.76
107.35
107.81
108.03
109.08
109.86
110.29
110.34
110.59
110.64
110.83
111.51
113.32
115.89
116.51
117.44
118.25
118.65
118.52
119.07
119.12
119.28
119.30
119.44
119.57
119.93
120.03
119.66
119.46
119.48
119.56
119.43
119.57
119.59
119.50
119.54
119.56
119.61
119.64
119.60
119.71
119.72
119.66
119.76
119.80
119.88
119.78
120.08
120.22




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 1 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112276&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112276&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112276&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 time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5974944.47121.9e-05
20.3529022.64090.005348
30.2541291.90170.031178
40.1521341.13850.129887
5-0.006529-0.04890.480603
60.0568770.42560.336005
70.1364991.02150.155713
80.2207571.6520.052066
90.2169621.62360.05504
100.1150.86060.196569
110.156481.1710.123281
120.0899870.67340.25173
13-0.031191-0.23340.408147
14-0.174251-1.3040.098788
15-0.179408-1.34260.092414
16-0.142602-1.06710.145246
17-0.00121-0.00910.496402
18-0.049392-0.36960.356531
19-0.038249-0.28620.387879
20-0.003886-0.02910.488453
21-0.079548-0.59530.277027
22-0.138692-1.03790.151894
23-0.142718-1.0680.145051
24-0.103287-0.77290.221406
25-0.141142-1.05620.147704
26-0.156302-1.16970.123546
27-0.152329-1.13990.129584
28-0.11051-0.8270.20588
29-0.147369-1.10280.137414
30-0.124588-0.93230.177584
31-0.131234-0.98210.165146
32-0.124086-0.92860.178548
33-0.141977-1.06250.146294
34-0.086783-0.64940.25936
35-0.072442-0.54210.294947
36-0.040101-0.30010.382609
37-0.031464-0.23550.407357
38-0.044252-0.33120.370883
39-0.022134-0.16560.43452
40-0.040587-0.30370.381231
41-0.038466-0.28790.387262
42-0.031884-0.23860.406145
43-0.017117-0.12810.449267
44-0.019538-0.14620.442141
45-0.009441-0.07060.471965
46-0.00985-0.07370.470753
47-0.006223-0.04660.481512
48-0.004172-0.03120.487602

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.597494 & 4.4712 & 1.9e-05 \tabularnewline
2 & 0.352902 & 2.6409 & 0.005348 \tabularnewline
3 & 0.254129 & 1.9017 & 0.031178 \tabularnewline
4 & 0.152134 & 1.1385 & 0.129887 \tabularnewline
5 & -0.006529 & -0.0489 & 0.480603 \tabularnewline
6 & 0.056877 & 0.4256 & 0.336005 \tabularnewline
7 & 0.136499 & 1.0215 & 0.155713 \tabularnewline
8 & 0.220757 & 1.652 & 0.052066 \tabularnewline
9 & 0.216962 & 1.6236 & 0.05504 \tabularnewline
10 & 0.115 & 0.8606 & 0.196569 \tabularnewline
11 & 0.15648 & 1.171 & 0.123281 \tabularnewline
12 & 0.089987 & 0.6734 & 0.25173 \tabularnewline
13 & -0.031191 & -0.2334 & 0.408147 \tabularnewline
14 & -0.174251 & -1.304 & 0.098788 \tabularnewline
15 & -0.179408 & -1.3426 & 0.092414 \tabularnewline
16 & -0.142602 & -1.0671 & 0.145246 \tabularnewline
17 & -0.00121 & -0.0091 & 0.496402 \tabularnewline
18 & -0.049392 & -0.3696 & 0.356531 \tabularnewline
19 & -0.038249 & -0.2862 & 0.387879 \tabularnewline
20 & -0.003886 & -0.0291 & 0.488453 \tabularnewline
21 & -0.079548 & -0.5953 & 0.277027 \tabularnewline
22 & -0.138692 & -1.0379 & 0.151894 \tabularnewline
23 & -0.142718 & -1.068 & 0.145051 \tabularnewline
24 & -0.103287 & -0.7729 & 0.221406 \tabularnewline
25 & -0.141142 & -1.0562 & 0.147704 \tabularnewline
26 & -0.156302 & -1.1697 & 0.123546 \tabularnewline
27 & -0.152329 & -1.1399 & 0.129584 \tabularnewline
28 & -0.11051 & -0.827 & 0.20588 \tabularnewline
29 & -0.147369 & -1.1028 & 0.137414 \tabularnewline
30 & -0.124588 & -0.9323 & 0.177584 \tabularnewline
31 & -0.131234 & -0.9821 & 0.165146 \tabularnewline
32 & -0.124086 & -0.9286 & 0.178548 \tabularnewline
33 & -0.141977 & -1.0625 & 0.146294 \tabularnewline
34 & -0.086783 & -0.6494 & 0.25936 \tabularnewline
35 & -0.072442 & -0.5421 & 0.294947 \tabularnewline
36 & -0.040101 & -0.3001 & 0.382609 \tabularnewline
37 & -0.031464 & -0.2355 & 0.407357 \tabularnewline
38 & -0.044252 & -0.3312 & 0.370883 \tabularnewline
39 & -0.022134 & -0.1656 & 0.43452 \tabularnewline
40 & -0.040587 & -0.3037 & 0.381231 \tabularnewline
41 & -0.038466 & -0.2879 & 0.387262 \tabularnewline
42 & -0.031884 & -0.2386 & 0.406145 \tabularnewline
43 & -0.017117 & -0.1281 & 0.449267 \tabularnewline
44 & -0.019538 & -0.1462 & 0.442141 \tabularnewline
45 & -0.009441 & -0.0706 & 0.471965 \tabularnewline
46 & -0.00985 & -0.0737 & 0.470753 \tabularnewline
47 & -0.006223 & -0.0466 & 0.481512 \tabularnewline
48 & -0.004172 & -0.0312 & 0.487602 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112276&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]0.597494[/C][C]4.4712[/C][C]1.9e-05[/C][/ROW]
[ROW][C]2[/C][C]0.352902[/C][C]2.6409[/C][C]0.005348[/C][/ROW]
[ROW][C]3[/C][C]0.254129[/C][C]1.9017[/C][C]0.031178[/C][/ROW]
[ROW][C]4[/C][C]0.152134[/C][C]1.1385[/C][C]0.129887[/C][/ROW]
[ROW][C]5[/C][C]-0.006529[/C][C]-0.0489[/C][C]0.480603[/C][/ROW]
[ROW][C]6[/C][C]0.056877[/C][C]0.4256[/C][C]0.336005[/C][/ROW]
[ROW][C]7[/C][C]0.136499[/C][C]1.0215[/C][C]0.155713[/C][/ROW]
[ROW][C]8[/C][C]0.220757[/C][C]1.652[/C][C]0.052066[/C][/ROW]
[ROW][C]9[/C][C]0.216962[/C][C]1.6236[/C][C]0.05504[/C][/ROW]
[ROW][C]10[/C][C]0.115[/C][C]0.8606[/C][C]0.196569[/C][/ROW]
[ROW][C]11[/C][C]0.15648[/C][C]1.171[/C][C]0.123281[/C][/ROW]
[ROW][C]12[/C][C]0.089987[/C][C]0.6734[/C][C]0.25173[/C][/ROW]
[ROW][C]13[/C][C]-0.031191[/C][C]-0.2334[/C][C]0.408147[/C][/ROW]
[ROW][C]14[/C][C]-0.174251[/C][C]-1.304[/C][C]0.098788[/C][/ROW]
[ROW][C]15[/C][C]-0.179408[/C][C]-1.3426[/C][C]0.092414[/C][/ROW]
[ROW][C]16[/C][C]-0.142602[/C][C]-1.0671[/C][C]0.145246[/C][/ROW]
[ROW][C]17[/C][C]-0.00121[/C][C]-0.0091[/C][C]0.496402[/C][/ROW]
[ROW][C]18[/C][C]-0.049392[/C][C]-0.3696[/C][C]0.356531[/C][/ROW]
[ROW][C]19[/C][C]-0.038249[/C][C]-0.2862[/C][C]0.387879[/C][/ROW]
[ROW][C]20[/C][C]-0.003886[/C][C]-0.0291[/C][C]0.488453[/C][/ROW]
[ROW][C]21[/C][C]-0.079548[/C][C]-0.5953[/C][C]0.277027[/C][/ROW]
[ROW][C]22[/C][C]-0.138692[/C][C]-1.0379[/C][C]0.151894[/C][/ROW]
[ROW][C]23[/C][C]-0.142718[/C][C]-1.068[/C][C]0.145051[/C][/ROW]
[ROW][C]24[/C][C]-0.103287[/C][C]-0.7729[/C][C]0.221406[/C][/ROW]
[ROW][C]25[/C][C]-0.141142[/C][C]-1.0562[/C][C]0.147704[/C][/ROW]
[ROW][C]26[/C][C]-0.156302[/C][C]-1.1697[/C][C]0.123546[/C][/ROW]
[ROW][C]27[/C][C]-0.152329[/C][C]-1.1399[/C][C]0.129584[/C][/ROW]
[ROW][C]28[/C][C]-0.11051[/C][C]-0.827[/C][C]0.20588[/C][/ROW]
[ROW][C]29[/C][C]-0.147369[/C][C]-1.1028[/C][C]0.137414[/C][/ROW]
[ROW][C]30[/C][C]-0.124588[/C][C]-0.9323[/C][C]0.177584[/C][/ROW]
[ROW][C]31[/C][C]-0.131234[/C][C]-0.9821[/C][C]0.165146[/C][/ROW]
[ROW][C]32[/C][C]-0.124086[/C][C]-0.9286[/C][C]0.178548[/C][/ROW]
[ROW][C]33[/C][C]-0.141977[/C][C]-1.0625[/C][C]0.146294[/C][/ROW]
[ROW][C]34[/C][C]-0.086783[/C][C]-0.6494[/C][C]0.25936[/C][/ROW]
[ROW][C]35[/C][C]-0.072442[/C][C]-0.5421[/C][C]0.294947[/C][/ROW]
[ROW][C]36[/C][C]-0.040101[/C][C]-0.3001[/C][C]0.382609[/C][/ROW]
[ROW][C]37[/C][C]-0.031464[/C][C]-0.2355[/C][C]0.407357[/C][/ROW]
[ROW][C]38[/C][C]-0.044252[/C][C]-0.3312[/C][C]0.370883[/C][/ROW]
[ROW][C]39[/C][C]-0.022134[/C][C]-0.1656[/C][C]0.43452[/C][/ROW]
[ROW][C]40[/C][C]-0.040587[/C][C]-0.3037[/C][C]0.381231[/C][/ROW]
[ROW][C]41[/C][C]-0.038466[/C][C]-0.2879[/C][C]0.387262[/C][/ROW]
[ROW][C]42[/C][C]-0.031884[/C][C]-0.2386[/C][C]0.406145[/C][/ROW]
[ROW][C]43[/C][C]-0.017117[/C][C]-0.1281[/C][C]0.449267[/C][/ROW]
[ROW][C]44[/C][C]-0.019538[/C][C]-0.1462[/C][C]0.442141[/C][/ROW]
[ROW][C]45[/C][C]-0.009441[/C][C]-0.0706[/C][C]0.471965[/C][/ROW]
[ROW][C]46[/C][C]-0.00985[/C][C]-0.0737[/C][C]0.470753[/C][/ROW]
[ROW][C]47[/C][C]-0.006223[/C][C]-0.0466[/C][C]0.481512[/C][/ROW]
[ROW][C]48[/C][C]-0.004172[/C][C]-0.0312[/C][C]0.487602[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112276&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112276&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
10.5974944.47121.9e-05
20.3529022.64090.005348
30.2541291.90170.031178
40.1521341.13850.129887
5-0.006529-0.04890.480603
60.0568770.42560.336005
70.1364991.02150.155713
80.2207571.6520.052066
90.2169621.62360.05504
100.1150.86060.196569
110.156481.1710.123281
120.0899870.67340.25173
13-0.031191-0.23340.408147
14-0.174251-1.3040.098788
15-0.179408-1.34260.092414
16-0.142602-1.06710.145246
17-0.00121-0.00910.496402
18-0.049392-0.36960.356531
19-0.038249-0.28620.387879
20-0.003886-0.02910.488453
21-0.079548-0.59530.277027
22-0.138692-1.03790.151894
23-0.142718-1.0680.145051
24-0.103287-0.77290.221406
25-0.141142-1.05620.147704
26-0.156302-1.16970.123546
27-0.152329-1.13990.129584
28-0.11051-0.8270.20588
29-0.147369-1.10280.137414
30-0.124588-0.93230.177584
31-0.131234-0.98210.165146
32-0.124086-0.92860.178548
33-0.141977-1.06250.146294
34-0.086783-0.64940.25936
35-0.072442-0.54210.294947
36-0.040101-0.30010.382609
37-0.031464-0.23550.407357
38-0.044252-0.33120.370883
39-0.022134-0.16560.43452
40-0.040587-0.30370.381231
41-0.038466-0.28790.387262
42-0.031884-0.23860.406145
43-0.017117-0.12810.449267
44-0.019538-0.14620.442141
45-0.009441-0.07060.471965
46-0.00985-0.07370.470753
47-0.006223-0.04660.481512
48-0.004172-0.03120.487602







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5974944.47121.9e-05
2-0.006372-0.04770.481069
30.0711320.53230.29831
4-0.040561-0.30350.381305
5-0.148748-1.11310.135204
60.1849481.3840.085921
70.0936010.70040.243275
80.1607741.20310.116996
9-0.00226-0.01690.493284
10-0.168115-1.25810.106796
110.1807241.35240.090839
12-0.103251-0.77270.221487
13-0.053107-0.39740.346284
14-0.210498-1.57520.060419
15-0.091268-0.6830.248716
160.1053640.78850.216873
170.1777421.33010.094438
18-0.174766-1.30780.098138
19-0.083246-0.6230.267922
20-0.035392-0.26490.396049
21-0.003739-0.0280.488888
220.1357441.01580.157042
23-0.099732-0.74630.229296
24-0.018359-0.13740.44561
25-0.110463-0.82660.205978
26-0.028968-0.21680.414586
270.113850.8520.198928
28-0.157927-1.18180.121136
29-0.116636-0.87280.193243
300.0292530.21890.413757
31-0.011189-0.08370.466784
320.1178240.88170.19085
33-0.129343-0.96790.168624
34-0.019135-0.14320.443326
350.0191060.1430.443411
360.0618740.4630.322572
370.0554490.41490.339886
38-0.064143-0.480.316547
39-0.048681-0.36430.358504
40-0.010739-0.08040.468119
410.0216830.16230.435843
420.0281740.21080.41689
43-0.079025-0.59140.278327
44-0.075405-0.56430.287408
45-0.006714-0.05020.480055
460.0732110.54790.292983
47-0.062889-0.47060.31987
48-0.02005-0.150.440635

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.597494 & 4.4712 & 1.9e-05 \tabularnewline
2 & -0.006372 & -0.0477 & 0.481069 \tabularnewline
3 & 0.071132 & 0.5323 & 0.29831 \tabularnewline
4 & -0.040561 & -0.3035 & 0.381305 \tabularnewline
5 & -0.148748 & -1.1131 & 0.135204 \tabularnewline
6 & 0.184948 & 1.384 & 0.085921 \tabularnewline
7 & 0.093601 & 0.7004 & 0.243275 \tabularnewline
8 & 0.160774 & 1.2031 & 0.116996 \tabularnewline
9 & -0.00226 & -0.0169 & 0.493284 \tabularnewline
10 & -0.168115 & -1.2581 & 0.106796 \tabularnewline
11 & 0.180724 & 1.3524 & 0.090839 \tabularnewline
12 & -0.103251 & -0.7727 & 0.221487 \tabularnewline
13 & -0.053107 & -0.3974 & 0.346284 \tabularnewline
14 & -0.210498 & -1.5752 & 0.060419 \tabularnewline
15 & -0.091268 & -0.683 & 0.248716 \tabularnewline
16 & 0.105364 & 0.7885 & 0.216873 \tabularnewline
17 & 0.177742 & 1.3301 & 0.094438 \tabularnewline
18 & -0.174766 & -1.3078 & 0.098138 \tabularnewline
19 & -0.083246 & -0.623 & 0.267922 \tabularnewline
20 & -0.035392 & -0.2649 & 0.396049 \tabularnewline
21 & -0.003739 & -0.028 & 0.488888 \tabularnewline
22 & 0.135744 & 1.0158 & 0.157042 \tabularnewline
23 & -0.099732 & -0.7463 & 0.229296 \tabularnewline
24 & -0.018359 & -0.1374 & 0.44561 \tabularnewline
25 & -0.110463 & -0.8266 & 0.205978 \tabularnewline
26 & -0.028968 & -0.2168 & 0.414586 \tabularnewline
27 & 0.11385 & 0.852 & 0.198928 \tabularnewline
28 & -0.157927 & -1.1818 & 0.121136 \tabularnewline
29 & -0.116636 & -0.8728 & 0.193243 \tabularnewline
30 & 0.029253 & 0.2189 & 0.413757 \tabularnewline
31 & -0.011189 & -0.0837 & 0.466784 \tabularnewline
32 & 0.117824 & 0.8817 & 0.19085 \tabularnewline
33 & -0.129343 & -0.9679 & 0.168624 \tabularnewline
34 & -0.019135 & -0.1432 & 0.443326 \tabularnewline
35 & 0.019106 & 0.143 & 0.443411 \tabularnewline
36 & 0.061874 & 0.463 & 0.322572 \tabularnewline
37 & 0.055449 & 0.4149 & 0.339886 \tabularnewline
38 & -0.064143 & -0.48 & 0.316547 \tabularnewline
39 & -0.048681 & -0.3643 & 0.358504 \tabularnewline
40 & -0.010739 & -0.0804 & 0.468119 \tabularnewline
41 & 0.021683 & 0.1623 & 0.435843 \tabularnewline
42 & 0.028174 & 0.2108 & 0.41689 \tabularnewline
43 & -0.079025 & -0.5914 & 0.278327 \tabularnewline
44 & -0.075405 & -0.5643 & 0.287408 \tabularnewline
45 & -0.006714 & -0.0502 & 0.480055 \tabularnewline
46 & 0.073211 & 0.5479 & 0.292983 \tabularnewline
47 & -0.062889 & -0.4706 & 0.31987 \tabularnewline
48 & -0.02005 & -0.15 & 0.440635 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112276&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]0.597494[/C][C]4.4712[/C][C]1.9e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.006372[/C][C]-0.0477[/C][C]0.481069[/C][/ROW]
[ROW][C]3[/C][C]0.071132[/C][C]0.5323[/C][C]0.29831[/C][/ROW]
[ROW][C]4[/C][C]-0.040561[/C][C]-0.3035[/C][C]0.381305[/C][/ROW]
[ROW][C]5[/C][C]-0.148748[/C][C]-1.1131[/C][C]0.135204[/C][/ROW]
[ROW][C]6[/C][C]0.184948[/C][C]1.384[/C][C]0.085921[/C][/ROW]
[ROW][C]7[/C][C]0.093601[/C][C]0.7004[/C][C]0.243275[/C][/ROW]
[ROW][C]8[/C][C]0.160774[/C][C]1.2031[/C][C]0.116996[/C][/ROW]
[ROW][C]9[/C][C]-0.00226[/C][C]-0.0169[/C][C]0.493284[/C][/ROW]
[ROW][C]10[/C][C]-0.168115[/C][C]-1.2581[/C][C]0.106796[/C][/ROW]
[ROW][C]11[/C][C]0.180724[/C][C]1.3524[/C][C]0.090839[/C][/ROW]
[ROW][C]12[/C][C]-0.103251[/C][C]-0.7727[/C][C]0.221487[/C][/ROW]
[ROW][C]13[/C][C]-0.053107[/C][C]-0.3974[/C][C]0.346284[/C][/ROW]
[ROW][C]14[/C][C]-0.210498[/C][C]-1.5752[/C][C]0.060419[/C][/ROW]
[ROW][C]15[/C][C]-0.091268[/C][C]-0.683[/C][C]0.248716[/C][/ROW]
[ROW][C]16[/C][C]0.105364[/C][C]0.7885[/C][C]0.216873[/C][/ROW]
[ROW][C]17[/C][C]0.177742[/C][C]1.3301[/C][C]0.094438[/C][/ROW]
[ROW][C]18[/C][C]-0.174766[/C][C]-1.3078[/C][C]0.098138[/C][/ROW]
[ROW][C]19[/C][C]-0.083246[/C][C]-0.623[/C][C]0.267922[/C][/ROW]
[ROW][C]20[/C][C]-0.035392[/C][C]-0.2649[/C][C]0.396049[/C][/ROW]
[ROW][C]21[/C][C]-0.003739[/C][C]-0.028[/C][C]0.488888[/C][/ROW]
[ROW][C]22[/C][C]0.135744[/C][C]1.0158[/C][C]0.157042[/C][/ROW]
[ROW][C]23[/C][C]-0.099732[/C][C]-0.7463[/C][C]0.229296[/C][/ROW]
[ROW][C]24[/C][C]-0.018359[/C][C]-0.1374[/C][C]0.44561[/C][/ROW]
[ROW][C]25[/C][C]-0.110463[/C][C]-0.8266[/C][C]0.205978[/C][/ROW]
[ROW][C]26[/C][C]-0.028968[/C][C]-0.2168[/C][C]0.414586[/C][/ROW]
[ROW][C]27[/C][C]0.11385[/C][C]0.852[/C][C]0.198928[/C][/ROW]
[ROW][C]28[/C][C]-0.157927[/C][C]-1.1818[/C][C]0.121136[/C][/ROW]
[ROW][C]29[/C][C]-0.116636[/C][C]-0.8728[/C][C]0.193243[/C][/ROW]
[ROW][C]30[/C][C]0.029253[/C][C]0.2189[/C][C]0.413757[/C][/ROW]
[ROW][C]31[/C][C]-0.011189[/C][C]-0.0837[/C][C]0.466784[/C][/ROW]
[ROW][C]32[/C][C]0.117824[/C][C]0.8817[/C][C]0.19085[/C][/ROW]
[ROW][C]33[/C][C]-0.129343[/C][C]-0.9679[/C][C]0.168624[/C][/ROW]
[ROW][C]34[/C][C]-0.019135[/C][C]-0.1432[/C][C]0.443326[/C][/ROW]
[ROW][C]35[/C][C]0.019106[/C][C]0.143[/C][C]0.443411[/C][/ROW]
[ROW][C]36[/C][C]0.061874[/C][C]0.463[/C][C]0.322572[/C][/ROW]
[ROW][C]37[/C][C]0.055449[/C][C]0.4149[/C][C]0.339886[/C][/ROW]
[ROW][C]38[/C][C]-0.064143[/C][C]-0.48[/C][C]0.316547[/C][/ROW]
[ROW][C]39[/C][C]-0.048681[/C][C]-0.3643[/C][C]0.358504[/C][/ROW]
[ROW][C]40[/C][C]-0.010739[/C][C]-0.0804[/C][C]0.468119[/C][/ROW]
[ROW][C]41[/C][C]0.021683[/C][C]0.1623[/C][C]0.435843[/C][/ROW]
[ROW][C]42[/C][C]0.028174[/C][C]0.2108[/C][C]0.41689[/C][/ROW]
[ROW][C]43[/C][C]-0.079025[/C][C]-0.5914[/C][C]0.278327[/C][/ROW]
[ROW][C]44[/C][C]-0.075405[/C][C]-0.5643[/C][C]0.287408[/C][/ROW]
[ROW][C]45[/C][C]-0.006714[/C][C]-0.0502[/C][C]0.480055[/C][/ROW]
[ROW][C]46[/C][C]0.073211[/C][C]0.5479[/C][C]0.292983[/C][/ROW]
[ROW][C]47[/C][C]-0.062889[/C][C]-0.4706[/C][C]0.31987[/C][/ROW]
[ROW][C]48[/C][C]-0.02005[/C][C]-0.15[/C][C]0.440635[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112276&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112276&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
10.5974944.47121.9e-05
2-0.006372-0.04770.481069
30.0711320.53230.29831
4-0.040561-0.30350.381305
5-0.148748-1.11310.135204
60.1849481.3840.085921
70.0936010.70040.243275
80.1607741.20310.116996
9-0.00226-0.01690.493284
10-0.168115-1.25810.106796
110.1807241.35240.090839
12-0.103251-0.77270.221487
13-0.053107-0.39740.346284
14-0.210498-1.57520.060419
15-0.091268-0.6830.248716
160.1053640.78850.216873
170.1777421.33010.094438
18-0.174766-1.30780.098138
19-0.083246-0.6230.267922
20-0.035392-0.26490.396049
21-0.003739-0.0280.488888
220.1357441.01580.157042
23-0.099732-0.74630.229296
24-0.018359-0.13740.44561
25-0.110463-0.82660.205978
26-0.028968-0.21680.414586
270.113850.8520.198928
28-0.157927-1.18180.121136
29-0.116636-0.87280.193243
300.0292530.21890.413757
31-0.011189-0.08370.466784
320.1178240.88170.19085
33-0.129343-0.96790.168624
34-0.019135-0.14320.443326
350.0191060.1430.443411
360.0618740.4630.322572
370.0554490.41490.339886
38-0.064143-0.480.316547
39-0.048681-0.36430.358504
40-0.010739-0.08040.468119
410.0216830.16230.435843
420.0281740.21080.41689
43-0.079025-0.59140.278327
44-0.075405-0.56430.287408
45-0.006714-0.05020.480055
460.0732110.54790.292983
47-0.062889-0.47060.31987
48-0.02005-0.150.440635



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')