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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 18 Dec 2010 20:27:56 +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/t1292703969xe1jonrl7j0a3pg.htm/, Retrieved Tue, 30 Apr 2024 08:01:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112194, Retrieved Tue, 30 Apr 2024 08:01:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149
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] [74deae64b71f9d77c839af86f7c687b5]
-               [(Partial) Autocorrelation Function] [autocorrelatiefun...] [2010-12-18 20:27:56] [e665313c9926a9f4bdf6ad1ee5aefad6] [Current]
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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 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=112194&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=112194&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112194&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
1-0.244989-1.66160.051697
20.1087880.73780.232181
3-0.002915-0.01980.492155
40.2991922.02920.024123
5-0.130581-0.88560.190208
6-0.174063-1.18050.121925
70.2441831.65610.052251
8-0.289147-1.96110.027969
90.278791.89080.032476
10-0.249154-1.68980.048912
110.2909181.97310.027255
12-0.325782-2.20960.016076
130.1555271.05480.148505
14-0.054854-0.3720.355787
15-0.09653-0.65470.257962
16-0.068915-0.46740.321208
17-0.174103-1.18080.12187
180.2666381.80840.03854
19-0.202434-1.3730.088208
200.0900260.61060.272239
21-0.130109-0.88240.191063
220.3219912.18390.017055
23-0.133933-0.90840.184206
24-0.12955-0.87860.192079
250.0490120.33240.370542
260.0622460.42220.337432
27-0.045886-0.31120.378523
28-0.141418-0.95910.17125
290.1756511.19130.119819
30-0.125456-0.85090.199621
310.0253630.1720.432089
320.0033120.02250.491088
33-0.01504-0.1020.459596
34-0.128445-0.87120.194097
350.007370.050.480176
360.0031410.02130.491548
37-0.08717-0.59120.278636
38-0.038103-0.25840.398614
390.0178840.12130.451993
400.0776610.52670.30046
41-0.049247-0.3340.369945
420.00150.01020.495964
430.0653120.4430.329933
440.0136570.09260.463302
45-0.020336-0.13790.44545
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.244989 & -1.6616 & 0.051697 \tabularnewline
2 & 0.108788 & 0.7378 & 0.232181 \tabularnewline
3 & -0.002915 & -0.0198 & 0.492155 \tabularnewline
4 & 0.299192 & 2.0292 & 0.024123 \tabularnewline
5 & -0.130581 & -0.8856 & 0.190208 \tabularnewline
6 & -0.174063 & -1.1805 & 0.121925 \tabularnewline
7 & 0.244183 & 1.6561 & 0.052251 \tabularnewline
8 & -0.289147 & -1.9611 & 0.027969 \tabularnewline
9 & 0.27879 & 1.8908 & 0.032476 \tabularnewline
10 & -0.249154 & -1.6898 & 0.048912 \tabularnewline
11 & 0.290918 & 1.9731 & 0.027255 \tabularnewline
12 & -0.325782 & -2.2096 & 0.016076 \tabularnewline
13 & 0.155527 & 1.0548 & 0.148505 \tabularnewline
14 & -0.054854 & -0.372 & 0.355787 \tabularnewline
15 & -0.09653 & -0.6547 & 0.257962 \tabularnewline
16 & -0.068915 & -0.4674 & 0.321208 \tabularnewline
17 & -0.174103 & -1.1808 & 0.12187 \tabularnewline
18 & 0.266638 & 1.8084 & 0.03854 \tabularnewline
19 & -0.202434 & -1.373 & 0.088208 \tabularnewline
20 & 0.090026 & 0.6106 & 0.272239 \tabularnewline
21 & -0.130109 & -0.8824 & 0.191063 \tabularnewline
22 & 0.321991 & 2.1839 & 0.017055 \tabularnewline
23 & -0.133933 & -0.9084 & 0.184206 \tabularnewline
24 & -0.12955 & -0.8786 & 0.192079 \tabularnewline
25 & 0.049012 & 0.3324 & 0.370542 \tabularnewline
26 & 0.062246 & 0.4222 & 0.337432 \tabularnewline
27 & -0.045886 & -0.3112 & 0.378523 \tabularnewline
28 & -0.141418 & -0.9591 & 0.17125 \tabularnewline
29 & 0.175651 & 1.1913 & 0.119819 \tabularnewline
30 & -0.125456 & -0.8509 & 0.199621 \tabularnewline
31 & 0.025363 & 0.172 & 0.432089 \tabularnewline
32 & 0.003312 & 0.0225 & 0.491088 \tabularnewline
33 & -0.01504 & -0.102 & 0.459596 \tabularnewline
34 & -0.128445 & -0.8712 & 0.194097 \tabularnewline
35 & 0.00737 & 0.05 & 0.480176 \tabularnewline
36 & 0.003141 & 0.0213 & 0.491548 \tabularnewline
37 & -0.08717 & -0.5912 & 0.278636 \tabularnewline
38 & -0.038103 & -0.2584 & 0.398614 \tabularnewline
39 & 0.017884 & 0.1213 & 0.451993 \tabularnewline
40 & 0.077661 & 0.5267 & 0.30046 \tabularnewline
41 & -0.049247 & -0.334 & 0.369945 \tabularnewline
42 & 0.0015 & 0.0102 & 0.495964 \tabularnewline
43 & 0.065312 & 0.443 & 0.329933 \tabularnewline
44 & 0.013657 & 0.0926 & 0.463302 \tabularnewline
45 & -0.020336 & -0.1379 & 0.44545 \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112194&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]-0.244989[/C][C]-1.6616[/C][C]0.051697[/C][/ROW]
[ROW][C]2[/C][C]0.108788[/C][C]0.7378[/C][C]0.232181[/C][/ROW]
[ROW][C]3[/C][C]-0.002915[/C][C]-0.0198[/C][C]0.492155[/C][/ROW]
[ROW][C]4[/C][C]0.299192[/C][C]2.0292[/C][C]0.024123[/C][/ROW]
[ROW][C]5[/C][C]-0.130581[/C][C]-0.8856[/C][C]0.190208[/C][/ROW]
[ROW][C]6[/C][C]-0.174063[/C][C]-1.1805[/C][C]0.121925[/C][/ROW]
[ROW][C]7[/C][C]0.244183[/C][C]1.6561[/C][C]0.052251[/C][/ROW]
[ROW][C]8[/C][C]-0.289147[/C][C]-1.9611[/C][C]0.027969[/C][/ROW]
[ROW][C]9[/C][C]0.27879[/C][C]1.8908[/C][C]0.032476[/C][/ROW]
[ROW][C]10[/C][C]-0.249154[/C][C]-1.6898[/C][C]0.048912[/C][/ROW]
[ROW][C]11[/C][C]0.290918[/C][C]1.9731[/C][C]0.027255[/C][/ROW]
[ROW][C]12[/C][C]-0.325782[/C][C]-2.2096[/C][C]0.016076[/C][/ROW]
[ROW][C]13[/C][C]0.155527[/C][C]1.0548[/C][C]0.148505[/C][/ROW]
[ROW][C]14[/C][C]-0.054854[/C][C]-0.372[/C][C]0.355787[/C][/ROW]
[ROW][C]15[/C][C]-0.09653[/C][C]-0.6547[/C][C]0.257962[/C][/ROW]
[ROW][C]16[/C][C]-0.068915[/C][C]-0.4674[/C][C]0.321208[/C][/ROW]
[ROW][C]17[/C][C]-0.174103[/C][C]-1.1808[/C][C]0.12187[/C][/ROW]
[ROW][C]18[/C][C]0.266638[/C][C]1.8084[/C][C]0.03854[/C][/ROW]
[ROW][C]19[/C][C]-0.202434[/C][C]-1.373[/C][C]0.088208[/C][/ROW]
[ROW][C]20[/C][C]0.090026[/C][C]0.6106[/C][C]0.272239[/C][/ROW]
[ROW][C]21[/C][C]-0.130109[/C][C]-0.8824[/C][C]0.191063[/C][/ROW]
[ROW][C]22[/C][C]0.321991[/C][C]2.1839[/C][C]0.017055[/C][/ROW]
[ROW][C]23[/C][C]-0.133933[/C][C]-0.9084[/C][C]0.184206[/C][/ROW]
[ROW][C]24[/C][C]-0.12955[/C][C]-0.8786[/C][C]0.192079[/C][/ROW]
[ROW][C]25[/C][C]0.049012[/C][C]0.3324[/C][C]0.370542[/C][/ROW]
[ROW][C]26[/C][C]0.062246[/C][C]0.4222[/C][C]0.337432[/C][/ROW]
[ROW][C]27[/C][C]-0.045886[/C][C]-0.3112[/C][C]0.378523[/C][/ROW]
[ROW][C]28[/C][C]-0.141418[/C][C]-0.9591[/C][C]0.17125[/C][/ROW]
[ROW][C]29[/C][C]0.175651[/C][C]1.1913[/C][C]0.119819[/C][/ROW]
[ROW][C]30[/C][C]-0.125456[/C][C]-0.8509[/C][C]0.199621[/C][/ROW]
[ROW][C]31[/C][C]0.025363[/C][C]0.172[/C][C]0.432089[/C][/ROW]
[ROW][C]32[/C][C]0.003312[/C][C]0.0225[/C][C]0.491088[/C][/ROW]
[ROW][C]33[/C][C]-0.01504[/C][C]-0.102[/C][C]0.459596[/C][/ROW]
[ROW][C]34[/C][C]-0.128445[/C][C]-0.8712[/C][C]0.194097[/C][/ROW]
[ROW][C]35[/C][C]0.00737[/C][C]0.05[/C][C]0.480176[/C][/ROW]
[ROW][C]36[/C][C]0.003141[/C][C]0.0213[/C][C]0.491548[/C][/ROW]
[ROW][C]37[/C][C]-0.08717[/C][C]-0.5912[/C][C]0.278636[/C][/ROW]
[ROW][C]38[/C][C]-0.038103[/C][C]-0.2584[/C][C]0.398614[/C][/ROW]
[ROW][C]39[/C][C]0.017884[/C][C]0.1213[/C][C]0.451993[/C][/ROW]
[ROW][C]40[/C][C]0.077661[/C][C]0.5267[/C][C]0.30046[/C][/ROW]
[ROW][C]41[/C][C]-0.049247[/C][C]-0.334[/C][C]0.369945[/C][/ROW]
[ROW][C]42[/C][C]0.0015[/C][C]0.0102[/C][C]0.495964[/C][/ROW]
[ROW][C]43[/C][C]0.065312[/C][C]0.443[/C][C]0.329933[/C][/ROW]
[ROW][C]44[/C][C]0.013657[/C][C]0.0926[/C][C]0.463302[/C][/ROW]
[ROW][C]45[/C][C]-0.020336[/C][C]-0.1379[/C][C]0.44545[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112194&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112194&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
1-0.244989-1.66160.051697
20.1087880.73780.232181
3-0.002915-0.01980.492155
40.2991922.02920.024123
5-0.130581-0.88560.190208
6-0.174063-1.18050.121925
70.2441831.65610.052251
8-0.289147-1.96110.027969
90.278791.89080.032476
10-0.249154-1.68980.048912
110.2909181.97310.027255
12-0.325782-2.20960.016076
130.1555271.05480.148505
14-0.054854-0.3720.355787
15-0.09653-0.65470.257962
16-0.068915-0.46740.321208
17-0.174103-1.18080.12187
180.2666381.80840.03854
19-0.202434-1.3730.088208
200.0900260.61060.272239
21-0.130109-0.88240.191063
220.3219912.18390.017055
23-0.133933-0.90840.184206
24-0.12955-0.87860.192079
250.0490120.33240.370542
260.0622460.42220.337432
27-0.045886-0.31120.378523
28-0.141418-0.95910.17125
290.1756511.19130.119819
30-0.125456-0.85090.199621
310.0253630.1720.432089
320.0033120.02250.491088
33-0.01504-0.1020.459596
34-0.128445-0.87120.194097
350.007370.050.480176
360.0031410.02130.491548
37-0.08717-0.59120.278636
38-0.038103-0.25840.398614
390.0178840.12130.451993
400.0776610.52670.30046
41-0.049247-0.3340.369945
420.00150.01020.495964
430.0653120.4430.329933
440.0136570.09260.463302
45-0.020336-0.13790.44545
46NANANA
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.244989-1.66160.051697
20.0518820.35190.363268
30.0374040.25370.400434
40.3216232.18140.017153
50.0116110.07870.468788
6-0.298783-2.02640.02427
70.1441260.97750.166715
8-0.310025-2.10270.020497
90.3162892.14520.018626
10-0.043682-0.29630.384181
110.1363250.92460.18
12-0.202864-1.37590.087759
13-0.114974-0.77980.219753
14-0.030233-0.20510.419218
15-0.064824-0.43970.331122
16-0.101533-0.68860.247258
17-0.043311-0.29370.385136
180.0628370.42620.335983
190.221951.50530.069536
20-0.180073-1.22130.114094
210.0791040.53650.297096
220.0497890.33770.368568
230.0012250.00830.496702
24-0.196907-1.33550.094144
25-0.076601-0.51950.302941
260.1433940.97250.167933
27-0.042787-0.29020.386486
280.0634020.430.334596
29-0.055473-0.37620.354236
30-0.115316-0.78210.219078
31-0.055718-0.37790.353623
32-0.058126-0.39420.347616
33-0.060332-0.40920.342149
340.0496060.33640.369033
35-0.024528-0.16640.434301
36-0.092876-0.62990.265934
370.0037960.02570.489787
380.0424140.28770.387448
39-0.051957-0.35240.363077
400.0486630.330.371431
41-0.106706-0.72370.236452
420.0811960.55070.292253
430.0677090.45920.324118
44-0.125701-0.85250.199165
450.080280.54450.294368
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.244989 & -1.6616 & 0.051697 \tabularnewline
2 & 0.051882 & 0.3519 & 0.363268 \tabularnewline
3 & 0.037404 & 0.2537 & 0.400434 \tabularnewline
4 & 0.321623 & 2.1814 & 0.017153 \tabularnewline
5 & 0.011611 & 0.0787 & 0.468788 \tabularnewline
6 & -0.298783 & -2.0264 & 0.02427 \tabularnewline
7 & 0.144126 & 0.9775 & 0.166715 \tabularnewline
8 & -0.310025 & -2.1027 & 0.020497 \tabularnewline
9 & 0.316289 & 2.1452 & 0.018626 \tabularnewline
10 & -0.043682 & -0.2963 & 0.384181 \tabularnewline
11 & 0.136325 & 0.9246 & 0.18 \tabularnewline
12 & -0.202864 & -1.3759 & 0.087759 \tabularnewline
13 & -0.114974 & -0.7798 & 0.219753 \tabularnewline
14 & -0.030233 & -0.2051 & 0.419218 \tabularnewline
15 & -0.064824 & -0.4397 & 0.331122 \tabularnewline
16 & -0.101533 & -0.6886 & 0.247258 \tabularnewline
17 & -0.043311 & -0.2937 & 0.385136 \tabularnewline
18 & 0.062837 & 0.4262 & 0.335983 \tabularnewline
19 & 0.22195 & 1.5053 & 0.069536 \tabularnewline
20 & -0.180073 & -1.2213 & 0.114094 \tabularnewline
21 & 0.079104 & 0.5365 & 0.297096 \tabularnewline
22 & 0.049789 & 0.3377 & 0.368568 \tabularnewline
23 & 0.001225 & 0.0083 & 0.496702 \tabularnewline
24 & -0.196907 & -1.3355 & 0.094144 \tabularnewline
25 & -0.076601 & -0.5195 & 0.302941 \tabularnewline
26 & 0.143394 & 0.9725 & 0.167933 \tabularnewline
27 & -0.042787 & -0.2902 & 0.386486 \tabularnewline
28 & 0.063402 & 0.43 & 0.334596 \tabularnewline
29 & -0.055473 & -0.3762 & 0.354236 \tabularnewline
30 & -0.115316 & -0.7821 & 0.219078 \tabularnewline
31 & -0.055718 & -0.3779 & 0.353623 \tabularnewline
32 & -0.058126 & -0.3942 & 0.347616 \tabularnewline
33 & -0.060332 & -0.4092 & 0.342149 \tabularnewline
34 & 0.049606 & 0.3364 & 0.369033 \tabularnewline
35 & -0.024528 & -0.1664 & 0.434301 \tabularnewline
36 & -0.092876 & -0.6299 & 0.265934 \tabularnewline
37 & 0.003796 & 0.0257 & 0.489787 \tabularnewline
38 & 0.042414 & 0.2877 & 0.387448 \tabularnewline
39 & -0.051957 & -0.3524 & 0.363077 \tabularnewline
40 & 0.048663 & 0.33 & 0.371431 \tabularnewline
41 & -0.106706 & -0.7237 & 0.236452 \tabularnewline
42 & 0.081196 & 0.5507 & 0.292253 \tabularnewline
43 & 0.067709 & 0.4592 & 0.324118 \tabularnewline
44 & -0.125701 & -0.8525 & 0.199165 \tabularnewline
45 & 0.08028 & 0.5445 & 0.294368 \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112194&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]-0.244989[/C][C]-1.6616[/C][C]0.051697[/C][/ROW]
[ROW][C]2[/C][C]0.051882[/C][C]0.3519[/C][C]0.363268[/C][/ROW]
[ROW][C]3[/C][C]0.037404[/C][C]0.2537[/C][C]0.400434[/C][/ROW]
[ROW][C]4[/C][C]0.321623[/C][C]2.1814[/C][C]0.017153[/C][/ROW]
[ROW][C]5[/C][C]0.011611[/C][C]0.0787[/C][C]0.468788[/C][/ROW]
[ROW][C]6[/C][C]-0.298783[/C][C]-2.0264[/C][C]0.02427[/C][/ROW]
[ROW][C]7[/C][C]0.144126[/C][C]0.9775[/C][C]0.166715[/C][/ROW]
[ROW][C]8[/C][C]-0.310025[/C][C]-2.1027[/C][C]0.020497[/C][/ROW]
[ROW][C]9[/C][C]0.316289[/C][C]2.1452[/C][C]0.018626[/C][/ROW]
[ROW][C]10[/C][C]-0.043682[/C][C]-0.2963[/C][C]0.384181[/C][/ROW]
[ROW][C]11[/C][C]0.136325[/C][C]0.9246[/C][C]0.18[/C][/ROW]
[ROW][C]12[/C][C]-0.202864[/C][C]-1.3759[/C][C]0.087759[/C][/ROW]
[ROW][C]13[/C][C]-0.114974[/C][C]-0.7798[/C][C]0.219753[/C][/ROW]
[ROW][C]14[/C][C]-0.030233[/C][C]-0.2051[/C][C]0.419218[/C][/ROW]
[ROW][C]15[/C][C]-0.064824[/C][C]-0.4397[/C][C]0.331122[/C][/ROW]
[ROW][C]16[/C][C]-0.101533[/C][C]-0.6886[/C][C]0.247258[/C][/ROW]
[ROW][C]17[/C][C]-0.043311[/C][C]-0.2937[/C][C]0.385136[/C][/ROW]
[ROW][C]18[/C][C]0.062837[/C][C]0.4262[/C][C]0.335983[/C][/ROW]
[ROW][C]19[/C][C]0.22195[/C][C]1.5053[/C][C]0.069536[/C][/ROW]
[ROW][C]20[/C][C]-0.180073[/C][C]-1.2213[/C][C]0.114094[/C][/ROW]
[ROW][C]21[/C][C]0.079104[/C][C]0.5365[/C][C]0.297096[/C][/ROW]
[ROW][C]22[/C][C]0.049789[/C][C]0.3377[/C][C]0.368568[/C][/ROW]
[ROW][C]23[/C][C]0.001225[/C][C]0.0083[/C][C]0.496702[/C][/ROW]
[ROW][C]24[/C][C]-0.196907[/C][C]-1.3355[/C][C]0.094144[/C][/ROW]
[ROW][C]25[/C][C]-0.076601[/C][C]-0.5195[/C][C]0.302941[/C][/ROW]
[ROW][C]26[/C][C]0.143394[/C][C]0.9725[/C][C]0.167933[/C][/ROW]
[ROW][C]27[/C][C]-0.042787[/C][C]-0.2902[/C][C]0.386486[/C][/ROW]
[ROW][C]28[/C][C]0.063402[/C][C]0.43[/C][C]0.334596[/C][/ROW]
[ROW][C]29[/C][C]-0.055473[/C][C]-0.3762[/C][C]0.354236[/C][/ROW]
[ROW][C]30[/C][C]-0.115316[/C][C]-0.7821[/C][C]0.219078[/C][/ROW]
[ROW][C]31[/C][C]-0.055718[/C][C]-0.3779[/C][C]0.353623[/C][/ROW]
[ROW][C]32[/C][C]-0.058126[/C][C]-0.3942[/C][C]0.347616[/C][/ROW]
[ROW][C]33[/C][C]-0.060332[/C][C]-0.4092[/C][C]0.342149[/C][/ROW]
[ROW][C]34[/C][C]0.049606[/C][C]0.3364[/C][C]0.369033[/C][/ROW]
[ROW][C]35[/C][C]-0.024528[/C][C]-0.1664[/C][C]0.434301[/C][/ROW]
[ROW][C]36[/C][C]-0.092876[/C][C]-0.6299[/C][C]0.265934[/C][/ROW]
[ROW][C]37[/C][C]0.003796[/C][C]0.0257[/C][C]0.489787[/C][/ROW]
[ROW][C]38[/C][C]0.042414[/C][C]0.2877[/C][C]0.387448[/C][/ROW]
[ROW][C]39[/C][C]-0.051957[/C][C]-0.3524[/C][C]0.363077[/C][/ROW]
[ROW][C]40[/C][C]0.048663[/C][C]0.33[/C][C]0.371431[/C][/ROW]
[ROW][C]41[/C][C]-0.106706[/C][C]-0.7237[/C][C]0.236452[/C][/ROW]
[ROW][C]42[/C][C]0.081196[/C][C]0.5507[/C][C]0.292253[/C][/ROW]
[ROW][C]43[/C][C]0.067709[/C][C]0.4592[/C][C]0.324118[/C][/ROW]
[ROW][C]44[/C][C]-0.125701[/C][C]-0.8525[/C][C]0.199165[/C][/ROW]
[ROW][C]45[/C][C]0.08028[/C][C]0.5445[/C][C]0.294368[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112194&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112194&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
1-0.244989-1.66160.051697
20.0518820.35190.363268
30.0374040.25370.400434
40.3216232.18140.017153
50.0116110.07870.468788
6-0.298783-2.02640.02427
70.1441260.97750.166715
8-0.310025-2.10270.020497
90.3162892.14520.018626
10-0.043682-0.29630.384181
110.1363250.92460.18
12-0.202864-1.37590.087759
13-0.114974-0.77980.219753
14-0.030233-0.20510.419218
15-0.064824-0.43970.331122
16-0.101533-0.68860.247258
17-0.043311-0.29370.385136
180.0628370.42620.335983
190.221951.50530.069536
20-0.180073-1.22130.114094
210.0791040.53650.297096
220.0497890.33770.368568
230.0012250.00830.496702
24-0.196907-1.33550.094144
25-0.076601-0.51950.302941
260.1433940.97250.167933
27-0.042787-0.29020.386486
280.0634020.430.334596
29-0.055473-0.37620.354236
30-0.115316-0.78210.219078
31-0.055718-0.37790.353623
32-0.058126-0.39420.347616
33-0.060332-0.40920.342149
340.0496060.33640.369033
35-0.024528-0.16640.434301
36-0.092876-0.62990.265934
370.0037960.02570.489787
380.0424140.28770.387448
39-0.051957-0.35240.363077
400.0486630.330.371431
41-0.106706-0.72370.236452
420.0811960.55070.292253
430.0677090.45920.324118
44-0.125701-0.85250.199165
450.080280.54450.294368
46NANANA
47NANANA
48NANANA



Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')