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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 15 Nov 2010 18:44:29 +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/Nov/15/t12898467068nqiy5xjwatismq.htm/, Retrieved Sun, 28 Apr 2024 17:55:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=95001, Retrieved Sun, 28 Apr 2024 17:55:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [] [Opgave 6bis; Opdr...] [1970-01-01 00:00:00] [07e3bd7de496d4bb901bc9a984612f8a]
- RMPD    [(Partial) Autocorrelation Function] [Opgave 6bis; Opdr...] [2010-11-15 18:44:29] [516d1a4ad1f0b8513272cbee80fe4619] [Current]
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Dataseries X:
13.81
13.9
13.91
13.94
13.96
14.01
14.01
14.06
14.09
14.13
14.12
14.13
14.14
14.16
14.21
14.26
14.29
14.32
14.33
14.39
14.48
14.44
14.46
14.48
14.53
14.58
14.62
14.62
14.61
14.65
14.68
14.7
14.78
14.84
14.89
14.89
15.13
15.25
15.33
15.36
15.4
15.4
15.41
15.47
15.54
15.55
15.59
15.65
15.75
15.86
15.89
15.94
15.93
15.95
15.99
15.99
16.06
16.08
16.07
16.11
16.15
16.18
16.3
16.42
16.49
16.5
16.58
16.64
16.66
16.81
16.91
16.92
16.95
17.11
17.16
17.16
17.27
17.34
17.39
17.43
17.45
17.5
17.56
17.65





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=95001&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=95001&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95001&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'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1503071.36940.08729
2-0.06626-0.60370.273859
30.0899970.81990.207308
40.1162521.05910.146311
5-0.105264-0.9590.170173
60.056180.51180.305065
70.1904021.73460.043258
8-0.108963-0.99270.16187
9-0.201525-1.8360.03497
100.0821690.74860.228109
110.042720.38920.349063
120.0708920.64590.260075
130.1797931.6380.052605
140.0622480.56710.286086
15-0.107594-0.98020.164911
16-0.057941-0.52790.2995
170.0220590.2010.420607
18-0.055087-0.50190.308546
19-0.01166-0.10620.457829
200.0277030.25240.400684
21-0.123945-1.12920.131035
22-0.096242-0.87680.191561
23-0.029341-0.26730.394946
240.0104140.09490.46232
250.0252560.23010.409292
260.0166160.15140.440021
270.0197140.17960.428952
28-0.084824-0.77280.220923
290.0685540.62460.266987
300.058960.53710.296301
31-0.002939-0.02680.48935
32-0.045752-0.41680.338944
330.1366191.24470.10838
34-0.013751-0.12530.450304
35-0.044103-0.40180.344435
360.0414310.37750.353398
370.1882751.71530.045014
38-0.088894-0.80990.210168
39-0.042835-0.39020.348677
400.1120671.0210.155116
41-0.055074-0.50170.308588
42-0.075612-0.68890.246416
43-0.01406-0.12810.449191
440.0194690.17740.429826
45-0.045625-0.41570.339365
46-0.024472-0.22290.412062
470.0814890.74240.229971
48-0.039312-0.35810.360572

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.150307 & 1.3694 & 0.08729 \tabularnewline
2 & -0.06626 & -0.6037 & 0.273859 \tabularnewline
3 & 0.089997 & 0.8199 & 0.207308 \tabularnewline
4 & 0.116252 & 1.0591 & 0.146311 \tabularnewline
5 & -0.105264 & -0.959 & 0.170173 \tabularnewline
6 & 0.05618 & 0.5118 & 0.305065 \tabularnewline
7 & 0.190402 & 1.7346 & 0.043258 \tabularnewline
8 & -0.108963 & -0.9927 & 0.16187 \tabularnewline
9 & -0.201525 & -1.836 & 0.03497 \tabularnewline
10 & 0.082169 & 0.7486 & 0.228109 \tabularnewline
11 & 0.04272 & 0.3892 & 0.349063 \tabularnewline
12 & 0.070892 & 0.6459 & 0.260075 \tabularnewline
13 & 0.179793 & 1.638 & 0.052605 \tabularnewline
14 & 0.062248 & 0.5671 & 0.286086 \tabularnewline
15 & -0.107594 & -0.9802 & 0.164911 \tabularnewline
16 & -0.057941 & -0.5279 & 0.2995 \tabularnewline
17 & 0.022059 & 0.201 & 0.420607 \tabularnewline
18 & -0.055087 & -0.5019 & 0.308546 \tabularnewline
19 & -0.01166 & -0.1062 & 0.457829 \tabularnewline
20 & 0.027703 & 0.2524 & 0.400684 \tabularnewline
21 & -0.123945 & -1.1292 & 0.131035 \tabularnewline
22 & -0.096242 & -0.8768 & 0.191561 \tabularnewline
23 & -0.029341 & -0.2673 & 0.394946 \tabularnewline
24 & 0.010414 & 0.0949 & 0.46232 \tabularnewline
25 & 0.025256 & 0.2301 & 0.409292 \tabularnewline
26 & 0.016616 & 0.1514 & 0.440021 \tabularnewline
27 & 0.019714 & 0.1796 & 0.428952 \tabularnewline
28 & -0.084824 & -0.7728 & 0.220923 \tabularnewline
29 & 0.068554 & 0.6246 & 0.266987 \tabularnewline
30 & 0.05896 & 0.5371 & 0.296301 \tabularnewline
31 & -0.002939 & -0.0268 & 0.48935 \tabularnewline
32 & -0.045752 & -0.4168 & 0.338944 \tabularnewline
33 & 0.136619 & 1.2447 & 0.10838 \tabularnewline
34 & -0.013751 & -0.1253 & 0.450304 \tabularnewline
35 & -0.044103 & -0.4018 & 0.344435 \tabularnewline
36 & 0.041431 & 0.3775 & 0.353398 \tabularnewline
37 & 0.188275 & 1.7153 & 0.045014 \tabularnewline
38 & -0.088894 & -0.8099 & 0.210168 \tabularnewline
39 & -0.042835 & -0.3902 & 0.348677 \tabularnewline
40 & 0.112067 & 1.021 & 0.155116 \tabularnewline
41 & -0.055074 & -0.5017 & 0.308588 \tabularnewline
42 & -0.075612 & -0.6889 & 0.246416 \tabularnewline
43 & -0.01406 & -0.1281 & 0.449191 \tabularnewline
44 & 0.019469 & 0.1774 & 0.429826 \tabularnewline
45 & -0.045625 & -0.4157 & 0.339365 \tabularnewline
46 & -0.024472 & -0.2229 & 0.412062 \tabularnewline
47 & 0.081489 & 0.7424 & 0.229971 \tabularnewline
48 & -0.039312 & -0.3581 & 0.360572 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95001&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]0.150307[/C][C]1.3694[/C][C]0.08729[/C][/ROW]
[ROW][C]2[/C][C]-0.06626[/C][C]-0.6037[/C][C]0.273859[/C][/ROW]
[ROW][C]3[/C][C]0.089997[/C][C]0.8199[/C][C]0.207308[/C][/ROW]
[ROW][C]4[/C][C]0.116252[/C][C]1.0591[/C][C]0.146311[/C][/ROW]
[ROW][C]5[/C][C]-0.105264[/C][C]-0.959[/C][C]0.170173[/C][/ROW]
[ROW][C]6[/C][C]0.05618[/C][C]0.5118[/C][C]0.305065[/C][/ROW]
[ROW][C]7[/C][C]0.190402[/C][C]1.7346[/C][C]0.043258[/C][/ROW]
[ROW][C]8[/C][C]-0.108963[/C][C]-0.9927[/C][C]0.16187[/C][/ROW]
[ROW][C]9[/C][C]-0.201525[/C][C]-1.836[/C][C]0.03497[/C][/ROW]
[ROW][C]10[/C][C]0.082169[/C][C]0.7486[/C][C]0.228109[/C][/ROW]
[ROW][C]11[/C][C]0.04272[/C][C]0.3892[/C][C]0.349063[/C][/ROW]
[ROW][C]12[/C][C]0.070892[/C][C]0.6459[/C][C]0.260075[/C][/ROW]
[ROW][C]13[/C][C]0.179793[/C][C]1.638[/C][C]0.052605[/C][/ROW]
[ROW][C]14[/C][C]0.062248[/C][C]0.5671[/C][C]0.286086[/C][/ROW]
[ROW][C]15[/C][C]-0.107594[/C][C]-0.9802[/C][C]0.164911[/C][/ROW]
[ROW][C]16[/C][C]-0.057941[/C][C]-0.5279[/C][C]0.2995[/C][/ROW]
[ROW][C]17[/C][C]0.022059[/C][C]0.201[/C][C]0.420607[/C][/ROW]
[ROW][C]18[/C][C]-0.055087[/C][C]-0.5019[/C][C]0.308546[/C][/ROW]
[ROW][C]19[/C][C]-0.01166[/C][C]-0.1062[/C][C]0.457829[/C][/ROW]
[ROW][C]20[/C][C]0.027703[/C][C]0.2524[/C][C]0.400684[/C][/ROW]
[ROW][C]21[/C][C]-0.123945[/C][C]-1.1292[/C][C]0.131035[/C][/ROW]
[ROW][C]22[/C][C]-0.096242[/C][C]-0.8768[/C][C]0.191561[/C][/ROW]
[ROW][C]23[/C][C]-0.029341[/C][C]-0.2673[/C][C]0.394946[/C][/ROW]
[ROW][C]24[/C][C]0.010414[/C][C]0.0949[/C][C]0.46232[/C][/ROW]
[ROW][C]25[/C][C]0.025256[/C][C]0.2301[/C][C]0.409292[/C][/ROW]
[ROW][C]26[/C][C]0.016616[/C][C]0.1514[/C][C]0.440021[/C][/ROW]
[ROW][C]27[/C][C]0.019714[/C][C]0.1796[/C][C]0.428952[/C][/ROW]
[ROW][C]28[/C][C]-0.084824[/C][C]-0.7728[/C][C]0.220923[/C][/ROW]
[ROW][C]29[/C][C]0.068554[/C][C]0.6246[/C][C]0.266987[/C][/ROW]
[ROW][C]30[/C][C]0.05896[/C][C]0.5371[/C][C]0.296301[/C][/ROW]
[ROW][C]31[/C][C]-0.002939[/C][C]-0.0268[/C][C]0.48935[/C][/ROW]
[ROW][C]32[/C][C]-0.045752[/C][C]-0.4168[/C][C]0.338944[/C][/ROW]
[ROW][C]33[/C][C]0.136619[/C][C]1.2447[/C][C]0.10838[/C][/ROW]
[ROW][C]34[/C][C]-0.013751[/C][C]-0.1253[/C][C]0.450304[/C][/ROW]
[ROW][C]35[/C][C]-0.044103[/C][C]-0.4018[/C][C]0.344435[/C][/ROW]
[ROW][C]36[/C][C]0.041431[/C][C]0.3775[/C][C]0.353398[/C][/ROW]
[ROW][C]37[/C][C]0.188275[/C][C]1.7153[/C][C]0.045014[/C][/ROW]
[ROW][C]38[/C][C]-0.088894[/C][C]-0.8099[/C][C]0.210168[/C][/ROW]
[ROW][C]39[/C][C]-0.042835[/C][C]-0.3902[/C][C]0.348677[/C][/ROW]
[ROW][C]40[/C][C]0.112067[/C][C]1.021[/C][C]0.155116[/C][/ROW]
[ROW][C]41[/C][C]-0.055074[/C][C]-0.5017[/C][C]0.308588[/C][/ROW]
[ROW][C]42[/C][C]-0.075612[/C][C]-0.6889[/C][C]0.246416[/C][/ROW]
[ROW][C]43[/C][C]-0.01406[/C][C]-0.1281[/C][C]0.449191[/C][/ROW]
[ROW][C]44[/C][C]0.019469[/C][C]0.1774[/C][C]0.429826[/C][/ROW]
[ROW][C]45[/C][C]-0.045625[/C][C]-0.4157[/C][C]0.339365[/C][/ROW]
[ROW][C]46[/C][C]-0.024472[/C][C]-0.2229[/C][C]0.412062[/C][/ROW]
[ROW][C]47[/C][C]0.081489[/C][C]0.7424[/C][C]0.229971[/C][/ROW]
[ROW][C]48[/C][C]-0.039312[/C][C]-0.3581[/C][C]0.360572[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95001&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95001&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
10.1503071.36940.08729
2-0.06626-0.60370.273859
30.0899970.81990.207308
40.1162521.05910.146311
5-0.105264-0.9590.170173
60.056180.51180.305065
70.1904021.73460.043258
8-0.108963-0.99270.16187
9-0.201525-1.8360.03497
100.0821690.74860.228109
110.042720.38920.349063
120.0708920.64590.260075
130.1797931.6380.052605
140.0622480.56710.286086
15-0.107594-0.98020.164911
16-0.057941-0.52790.2995
170.0220590.2010.420607
18-0.055087-0.50190.308546
19-0.01166-0.10620.457829
200.0277030.25240.400684
21-0.123945-1.12920.131035
22-0.096242-0.87680.191561
23-0.029341-0.26730.394946
240.0104140.09490.46232
250.0252560.23010.409292
260.0166160.15140.440021
270.0197140.17960.428952
28-0.084824-0.77280.220923
290.0685540.62460.266987
300.058960.53710.296301
31-0.002939-0.02680.48935
32-0.045752-0.41680.338944
330.1366191.24470.10838
34-0.013751-0.12530.450304
35-0.044103-0.40180.344435
360.0414310.37750.353398
370.1882751.71530.045014
38-0.088894-0.80990.210168
39-0.042835-0.39020.348677
400.1120671.0210.155116
41-0.055074-0.50170.308588
42-0.075612-0.68890.246416
43-0.01406-0.12810.449191
440.0194690.17740.429826
45-0.045625-0.41570.339365
46-0.024472-0.22290.412062
470.0814890.74240.229971
48-0.039312-0.35810.360572







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1503071.36940.08729
2-0.090906-0.82820.204968
30.1181491.07640.142437
40.0789530.71930.236989
5-0.126654-1.15390.125932
60.1094970.99760.160696
70.1341381.22210.112574
8-0.159708-1.4550.074719
9-0.1308-1.19160.118398
100.084370.76870.222141
11-0.008623-0.07860.468786
120.1737681.58310.0586
130.1413871.28810.100646
14-0.065349-0.59540.276612
15-0.043028-0.3920.34803
16-0.045475-0.41430.339861
17-0.071618-0.65250.257949
18-0.043638-0.39760.345986
190.016260.14810.441296
20-0.012534-0.11420.45468
21-0.049423-0.45030.326847
220.022540.20530.418903
23-0.079848-0.72750.234498
24-0.015458-0.14080.444172
250.0395580.36040.359736
26-0.047902-0.43640.331836
270.0409860.37340.354901
28-0.022908-0.20870.417597
290.1122061.02220.154817
300.0217820.19840.421592
31-0.004196-0.03820.484799
32-0.081678-0.74410.229453
330.1701631.55030.062442
34-0.021197-0.19310.423672
350.0116750.10640.457773
360.0203150.18510.426808
370.1337551.21860.113231
38-0.111579-1.01650.156165
39-0.008388-0.07640.469636
400.0381750.34780.364438
41-0.142331-1.29670.099164
420.0492530.44870.327403
43-0.108093-0.98480.163798
44-0.032612-0.29710.383561
450.083010.75630.225818
46-0.028515-0.25980.397838
470.0072090.06570.473895
480.0137690.12540.450239

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.150307 & 1.3694 & 0.08729 \tabularnewline
2 & -0.090906 & -0.8282 & 0.204968 \tabularnewline
3 & 0.118149 & 1.0764 & 0.142437 \tabularnewline
4 & 0.078953 & 0.7193 & 0.236989 \tabularnewline
5 & -0.126654 & -1.1539 & 0.125932 \tabularnewline
6 & 0.109497 & 0.9976 & 0.160696 \tabularnewline
7 & 0.134138 & 1.2221 & 0.112574 \tabularnewline
8 & -0.159708 & -1.455 & 0.074719 \tabularnewline
9 & -0.1308 & -1.1916 & 0.118398 \tabularnewline
10 & 0.08437 & 0.7687 & 0.222141 \tabularnewline
11 & -0.008623 & -0.0786 & 0.468786 \tabularnewline
12 & 0.173768 & 1.5831 & 0.0586 \tabularnewline
13 & 0.141387 & 1.2881 & 0.100646 \tabularnewline
14 & -0.065349 & -0.5954 & 0.276612 \tabularnewline
15 & -0.043028 & -0.392 & 0.34803 \tabularnewline
16 & -0.045475 & -0.4143 & 0.339861 \tabularnewline
17 & -0.071618 & -0.6525 & 0.257949 \tabularnewline
18 & -0.043638 & -0.3976 & 0.345986 \tabularnewline
19 & 0.01626 & 0.1481 & 0.441296 \tabularnewline
20 & -0.012534 & -0.1142 & 0.45468 \tabularnewline
21 & -0.049423 & -0.4503 & 0.326847 \tabularnewline
22 & 0.02254 & 0.2053 & 0.418903 \tabularnewline
23 & -0.079848 & -0.7275 & 0.234498 \tabularnewline
24 & -0.015458 & -0.1408 & 0.444172 \tabularnewline
25 & 0.039558 & 0.3604 & 0.359736 \tabularnewline
26 & -0.047902 & -0.4364 & 0.331836 \tabularnewline
27 & 0.040986 & 0.3734 & 0.354901 \tabularnewline
28 & -0.022908 & -0.2087 & 0.417597 \tabularnewline
29 & 0.112206 & 1.0222 & 0.154817 \tabularnewline
30 & 0.021782 & 0.1984 & 0.421592 \tabularnewline
31 & -0.004196 & -0.0382 & 0.484799 \tabularnewline
32 & -0.081678 & -0.7441 & 0.229453 \tabularnewline
33 & 0.170163 & 1.5503 & 0.062442 \tabularnewline
34 & -0.021197 & -0.1931 & 0.423672 \tabularnewline
35 & 0.011675 & 0.1064 & 0.457773 \tabularnewline
36 & 0.020315 & 0.1851 & 0.426808 \tabularnewline
37 & 0.133755 & 1.2186 & 0.113231 \tabularnewline
38 & -0.111579 & -1.0165 & 0.156165 \tabularnewline
39 & -0.008388 & -0.0764 & 0.469636 \tabularnewline
40 & 0.038175 & 0.3478 & 0.364438 \tabularnewline
41 & -0.142331 & -1.2967 & 0.099164 \tabularnewline
42 & 0.049253 & 0.4487 & 0.327403 \tabularnewline
43 & -0.108093 & -0.9848 & 0.163798 \tabularnewline
44 & -0.032612 & -0.2971 & 0.383561 \tabularnewline
45 & 0.08301 & 0.7563 & 0.225818 \tabularnewline
46 & -0.028515 & -0.2598 & 0.397838 \tabularnewline
47 & 0.007209 & 0.0657 & 0.473895 \tabularnewline
48 & 0.013769 & 0.1254 & 0.450239 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95001&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]0.150307[/C][C]1.3694[/C][C]0.08729[/C][/ROW]
[ROW][C]2[/C][C]-0.090906[/C][C]-0.8282[/C][C]0.204968[/C][/ROW]
[ROW][C]3[/C][C]0.118149[/C][C]1.0764[/C][C]0.142437[/C][/ROW]
[ROW][C]4[/C][C]0.078953[/C][C]0.7193[/C][C]0.236989[/C][/ROW]
[ROW][C]5[/C][C]-0.126654[/C][C]-1.1539[/C][C]0.125932[/C][/ROW]
[ROW][C]6[/C][C]0.109497[/C][C]0.9976[/C][C]0.160696[/C][/ROW]
[ROW][C]7[/C][C]0.134138[/C][C]1.2221[/C][C]0.112574[/C][/ROW]
[ROW][C]8[/C][C]-0.159708[/C][C]-1.455[/C][C]0.074719[/C][/ROW]
[ROW][C]9[/C][C]-0.1308[/C][C]-1.1916[/C][C]0.118398[/C][/ROW]
[ROW][C]10[/C][C]0.08437[/C][C]0.7687[/C][C]0.222141[/C][/ROW]
[ROW][C]11[/C][C]-0.008623[/C][C]-0.0786[/C][C]0.468786[/C][/ROW]
[ROW][C]12[/C][C]0.173768[/C][C]1.5831[/C][C]0.0586[/C][/ROW]
[ROW][C]13[/C][C]0.141387[/C][C]1.2881[/C][C]0.100646[/C][/ROW]
[ROW][C]14[/C][C]-0.065349[/C][C]-0.5954[/C][C]0.276612[/C][/ROW]
[ROW][C]15[/C][C]-0.043028[/C][C]-0.392[/C][C]0.34803[/C][/ROW]
[ROW][C]16[/C][C]-0.045475[/C][C]-0.4143[/C][C]0.339861[/C][/ROW]
[ROW][C]17[/C][C]-0.071618[/C][C]-0.6525[/C][C]0.257949[/C][/ROW]
[ROW][C]18[/C][C]-0.043638[/C][C]-0.3976[/C][C]0.345986[/C][/ROW]
[ROW][C]19[/C][C]0.01626[/C][C]0.1481[/C][C]0.441296[/C][/ROW]
[ROW][C]20[/C][C]-0.012534[/C][C]-0.1142[/C][C]0.45468[/C][/ROW]
[ROW][C]21[/C][C]-0.049423[/C][C]-0.4503[/C][C]0.326847[/C][/ROW]
[ROW][C]22[/C][C]0.02254[/C][C]0.2053[/C][C]0.418903[/C][/ROW]
[ROW][C]23[/C][C]-0.079848[/C][C]-0.7275[/C][C]0.234498[/C][/ROW]
[ROW][C]24[/C][C]-0.015458[/C][C]-0.1408[/C][C]0.444172[/C][/ROW]
[ROW][C]25[/C][C]0.039558[/C][C]0.3604[/C][C]0.359736[/C][/ROW]
[ROW][C]26[/C][C]-0.047902[/C][C]-0.4364[/C][C]0.331836[/C][/ROW]
[ROW][C]27[/C][C]0.040986[/C][C]0.3734[/C][C]0.354901[/C][/ROW]
[ROW][C]28[/C][C]-0.022908[/C][C]-0.2087[/C][C]0.417597[/C][/ROW]
[ROW][C]29[/C][C]0.112206[/C][C]1.0222[/C][C]0.154817[/C][/ROW]
[ROW][C]30[/C][C]0.021782[/C][C]0.1984[/C][C]0.421592[/C][/ROW]
[ROW][C]31[/C][C]-0.004196[/C][C]-0.0382[/C][C]0.484799[/C][/ROW]
[ROW][C]32[/C][C]-0.081678[/C][C]-0.7441[/C][C]0.229453[/C][/ROW]
[ROW][C]33[/C][C]0.170163[/C][C]1.5503[/C][C]0.062442[/C][/ROW]
[ROW][C]34[/C][C]-0.021197[/C][C]-0.1931[/C][C]0.423672[/C][/ROW]
[ROW][C]35[/C][C]0.011675[/C][C]0.1064[/C][C]0.457773[/C][/ROW]
[ROW][C]36[/C][C]0.020315[/C][C]0.1851[/C][C]0.426808[/C][/ROW]
[ROW][C]37[/C][C]0.133755[/C][C]1.2186[/C][C]0.113231[/C][/ROW]
[ROW][C]38[/C][C]-0.111579[/C][C]-1.0165[/C][C]0.156165[/C][/ROW]
[ROW][C]39[/C][C]-0.008388[/C][C]-0.0764[/C][C]0.469636[/C][/ROW]
[ROW][C]40[/C][C]0.038175[/C][C]0.3478[/C][C]0.364438[/C][/ROW]
[ROW][C]41[/C][C]-0.142331[/C][C]-1.2967[/C][C]0.099164[/C][/ROW]
[ROW][C]42[/C][C]0.049253[/C][C]0.4487[/C][C]0.327403[/C][/ROW]
[ROW][C]43[/C][C]-0.108093[/C][C]-0.9848[/C][C]0.163798[/C][/ROW]
[ROW][C]44[/C][C]-0.032612[/C][C]-0.2971[/C][C]0.383561[/C][/ROW]
[ROW][C]45[/C][C]0.08301[/C][C]0.7563[/C][C]0.225818[/C][/ROW]
[ROW][C]46[/C][C]-0.028515[/C][C]-0.2598[/C][C]0.397838[/C][/ROW]
[ROW][C]47[/C][C]0.007209[/C][C]0.0657[/C][C]0.473895[/C][/ROW]
[ROW][C]48[/C][C]0.013769[/C][C]0.1254[/C][C]0.450239[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95001&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95001&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
10.1503071.36940.08729
2-0.090906-0.82820.204968
30.1181491.07640.142437
40.0789530.71930.236989
5-0.126654-1.15390.125932
60.1094970.99760.160696
70.1341381.22210.112574
8-0.159708-1.4550.074719
9-0.1308-1.19160.118398
100.084370.76870.222141
11-0.008623-0.07860.468786
120.1737681.58310.0586
130.1413871.28810.100646
14-0.065349-0.59540.276612
15-0.043028-0.3920.34803
16-0.045475-0.41430.339861
17-0.071618-0.65250.257949
18-0.043638-0.39760.345986
190.016260.14810.441296
20-0.012534-0.11420.45468
21-0.049423-0.45030.326847
220.022540.20530.418903
23-0.079848-0.72750.234498
24-0.015458-0.14080.444172
250.0395580.36040.359736
26-0.047902-0.43640.331836
270.0409860.37340.354901
28-0.022908-0.20870.417597
290.1122061.02220.154817
300.0217820.19840.421592
31-0.004196-0.03820.484799
32-0.081678-0.74410.229453
330.1701631.55030.062442
34-0.021197-0.19310.423672
350.0116750.10640.457773
360.0203150.18510.426808
370.1337551.21860.113231
38-0.111579-1.01650.156165
39-0.008388-0.07640.469636
400.0381750.34780.364438
41-0.142331-1.29670.099164
420.0492530.44870.327403
43-0.108093-0.98480.163798
44-0.032612-0.29710.383561
450.083010.75630.225818
46-0.028515-0.25980.397838
470.0072090.06570.473895
480.0137690.12540.450239



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 ;
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')