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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 computationTue, 21 Dec 2010 11:53:47 +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/21/t1292932661365t4j3jkb7fvzd.htm/, Retrieved Thu, 16 May 2024 17:20:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113328, Retrieved Thu, 16 May 2024 17:20:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [(partial) autocor...] [2009-12-09 13:20:29] [f7fc9270f813d017f9fa5b506fdc7682]
-   P   [(Partial) Autocorrelation Function] [autocorrelation] [2009-12-09 13:36:40] [f7fc9270f813d017f9fa5b506fdc7682]
-   PD    [(Partial) Autocorrelation Function] [autocorrelation o...] [2010-12-18 13:59:09] [a8a0ff0853b70f438be515083758c362]
-   P         [(Partial) Autocorrelation Function] [differentiatie va...] [2010-12-21 11:53:47] [8f110cf3e3846d42560df9b5835185a6] [Current]
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Dataseries X:
78.33
78.21
78.94
77.94
77.31
75.75
77.73
77.90
77.45
77.46
77.97
77.23
76.56
76.70
76.51
76.03
76.69
76.38
76.80
76.63
77.17
78.63
78.89
76.94
77.50
79.27
79.77
78.62
78.60
77.88
78.71
79.27
80.12
81.12
81.48
82.81
82.39
82.41
82.20
81.99
81.61
83.51
84.05
82.99
83.54
84.44
84.24
83.88
84.17
84.59
84.76
85.14
85.22
84.77
84.50
84.56
83.79
83.96
84.80
84.89
84.78
84.80
84.44
84.65
84.22
84.08
85.29
85.00
84.63
84.92
84.61
84.50
84.29
84.50
84.41
84.71
84.21
83.86
84.40
83.71
84.42
85.26
85.08
85.65
85.74
85.89
86.08
85.49
85.97
85.84
86.72
85.42
83.87
85.45
85.35
84.27
83.13
83.79
83.70
83.76
83.47
83.78
84.83
84.43
84.90
85.36
85.49
85.29




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113328&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113328&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113328&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.078293-0.80990.209906
2-0.300045-3.10370.001223
30.0218220.22570.410923
40.191151.97730.025291
5-0.041406-0.42830.334646
6-0.109656-1.13430.129603
70.0220990.22860.40981
80.0500610.51780.302822
90.0722670.74750.22819
10-0.019711-0.20390.419414
11-0.030247-0.31290.37749
120.0493750.51070.305294
13-0.111538-1.15380.125584
140.0010970.01140.495482
150.0737930.76330.223475
160.0729870.7550.225958
17-0.037912-0.39220.34786
18-0.094937-0.9820.16415
190.0678460.70180.242161
200.0868940.89880.185379
21-0.141431-1.4630.073203
22-0.09564-0.98930.162372
23-0.035493-0.36710.357118
240.1864561.92870.028208
250.0287930.29780.383204
26-0.067359-0.69680.243731
27-0.003717-0.03840.484702
28-0.001758-0.01820.492764
29-0.063086-0.65260.257717
30-0.135407-1.40070.082104
310.0316740.32760.371914
32-0.017754-0.18360.427318
330.0387590.40090.344636
34-0.062717-0.64870.258945
350.0757490.78360.217517
360.0334850.34640.364872
37-0.161625-1.67190.048737
38-0.023452-0.24260.404394
390.1097741.13550.129348
40-0.031419-0.3250.372907
41-0.014254-0.14740.44153
420.0345110.3570.360904
43-0.047287-0.48910.312873
44-0.00186-0.01920.492341
450.0708120.73250.232737
46-0.107501-1.1120.134315
47-0.074072-0.76620.222621
480.0944910.97740.165283

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.078293 & -0.8099 & 0.209906 \tabularnewline
2 & -0.300045 & -3.1037 & 0.001223 \tabularnewline
3 & 0.021822 & 0.2257 & 0.410923 \tabularnewline
4 & 0.19115 & 1.9773 & 0.025291 \tabularnewline
5 & -0.041406 & -0.4283 & 0.334646 \tabularnewline
6 & -0.109656 & -1.1343 & 0.129603 \tabularnewline
7 & 0.022099 & 0.2286 & 0.40981 \tabularnewline
8 & 0.050061 & 0.5178 & 0.302822 \tabularnewline
9 & 0.072267 & 0.7475 & 0.22819 \tabularnewline
10 & -0.019711 & -0.2039 & 0.419414 \tabularnewline
11 & -0.030247 & -0.3129 & 0.37749 \tabularnewline
12 & 0.049375 & 0.5107 & 0.305294 \tabularnewline
13 & -0.111538 & -1.1538 & 0.125584 \tabularnewline
14 & 0.001097 & 0.0114 & 0.495482 \tabularnewline
15 & 0.073793 & 0.7633 & 0.223475 \tabularnewline
16 & 0.072987 & 0.755 & 0.225958 \tabularnewline
17 & -0.037912 & -0.3922 & 0.34786 \tabularnewline
18 & -0.094937 & -0.982 & 0.16415 \tabularnewline
19 & 0.067846 & 0.7018 & 0.242161 \tabularnewline
20 & 0.086894 & 0.8988 & 0.185379 \tabularnewline
21 & -0.141431 & -1.463 & 0.073203 \tabularnewline
22 & -0.09564 & -0.9893 & 0.162372 \tabularnewline
23 & -0.035493 & -0.3671 & 0.357118 \tabularnewline
24 & 0.186456 & 1.9287 & 0.028208 \tabularnewline
25 & 0.028793 & 0.2978 & 0.383204 \tabularnewline
26 & -0.067359 & -0.6968 & 0.243731 \tabularnewline
27 & -0.003717 & -0.0384 & 0.484702 \tabularnewline
28 & -0.001758 & -0.0182 & 0.492764 \tabularnewline
29 & -0.063086 & -0.6526 & 0.257717 \tabularnewline
30 & -0.135407 & -1.4007 & 0.082104 \tabularnewline
31 & 0.031674 & 0.3276 & 0.371914 \tabularnewline
32 & -0.017754 & -0.1836 & 0.427318 \tabularnewline
33 & 0.038759 & 0.4009 & 0.344636 \tabularnewline
34 & -0.062717 & -0.6487 & 0.258945 \tabularnewline
35 & 0.075749 & 0.7836 & 0.217517 \tabularnewline
36 & 0.033485 & 0.3464 & 0.364872 \tabularnewline
37 & -0.161625 & -1.6719 & 0.048737 \tabularnewline
38 & -0.023452 & -0.2426 & 0.404394 \tabularnewline
39 & 0.109774 & 1.1355 & 0.129348 \tabularnewline
40 & -0.031419 & -0.325 & 0.372907 \tabularnewline
41 & -0.014254 & -0.1474 & 0.44153 \tabularnewline
42 & 0.034511 & 0.357 & 0.360904 \tabularnewline
43 & -0.047287 & -0.4891 & 0.312873 \tabularnewline
44 & -0.00186 & -0.0192 & 0.492341 \tabularnewline
45 & 0.070812 & 0.7325 & 0.232737 \tabularnewline
46 & -0.107501 & -1.112 & 0.134315 \tabularnewline
47 & -0.074072 & -0.7662 & 0.222621 \tabularnewline
48 & 0.094491 & 0.9774 & 0.165283 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113328&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]-0.078293[/C][C]-0.8099[/C][C]0.209906[/C][/ROW]
[ROW][C]2[/C][C]-0.300045[/C][C]-3.1037[/C][C]0.001223[/C][/ROW]
[ROW][C]3[/C][C]0.021822[/C][C]0.2257[/C][C]0.410923[/C][/ROW]
[ROW][C]4[/C][C]0.19115[/C][C]1.9773[/C][C]0.025291[/C][/ROW]
[ROW][C]5[/C][C]-0.041406[/C][C]-0.4283[/C][C]0.334646[/C][/ROW]
[ROW][C]6[/C][C]-0.109656[/C][C]-1.1343[/C][C]0.129603[/C][/ROW]
[ROW][C]7[/C][C]0.022099[/C][C]0.2286[/C][C]0.40981[/C][/ROW]
[ROW][C]8[/C][C]0.050061[/C][C]0.5178[/C][C]0.302822[/C][/ROW]
[ROW][C]9[/C][C]0.072267[/C][C]0.7475[/C][C]0.22819[/C][/ROW]
[ROW][C]10[/C][C]-0.019711[/C][C]-0.2039[/C][C]0.419414[/C][/ROW]
[ROW][C]11[/C][C]-0.030247[/C][C]-0.3129[/C][C]0.37749[/C][/ROW]
[ROW][C]12[/C][C]0.049375[/C][C]0.5107[/C][C]0.305294[/C][/ROW]
[ROW][C]13[/C][C]-0.111538[/C][C]-1.1538[/C][C]0.125584[/C][/ROW]
[ROW][C]14[/C][C]0.001097[/C][C]0.0114[/C][C]0.495482[/C][/ROW]
[ROW][C]15[/C][C]0.073793[/C][C]0.7633[/C][C]0.223475[/C][/ROW]
[ROW][C]16[/C][C]0.072987[/C][C]0.755[/C][C]0.225958[/C][/ROW]
[ROW][C]17[/C][C]-0.037912[/C][C]-0.3922[/C][C]0.34786[/C][/ROW]
[ROW][C]18[/C][C]-0.094937[/C][C]-0.982[/C][C]0.16415[/C][/ROW]
[ROW][C]19[/C][C]0.067846[/C][C]0.7018[/C][C]0.242161[/C][/ROW]
[ROW][C]20[/C][C]0.086894[/C][C]0.8988[/C][C]0.185379[/C][/ROW]
[ROW][C]21[/C][C]-0.141431[/C][C]-1.463[/C][C]0.073203[/C][/ROW]
[ROW][C]22[/C][C]-0.09564[/C][C]-0.9893[/C][C]0.162372[/C][/ROW]
[ROW][C]23[/C][C]-0.035493[/C][C]-0.3671[/C][C]0.357118[/C][/ROW]
[ROW][C]24[/C][C]0.186456[/C][C]1.9287[/C][C]0.028208[/C][/ROW]
[ROW][C]25[/C][C]0.028793[/C][C]0.2978[/C][C]0.383204[/C][/ROW]
[ROW][C]26[/C][C]-0.067359[/C][C]-0.6968[/C][C]0.243731[/C][/ROW]
[ROW][C]27[/C][C]-0.003717[/C][C]-0.0384[/C][C]0.484702[/C][/ROW]
[ROW][C]28[/C][C]-0.001758[/C][C]-0.0182[/C][C]0.492764[/C][/ROW]
[ROW][C]29[/C][C]-0.063086[/C][C]-0.6526[/C][C]0.257717[/C][/ROW]
[ROW][C]30[/C][C]-0.135407[/C][C]-1.4007[/C][C]0.082104[/C][/ROW]
[ROW][C]31[/C][C]0.031674[/C][C]0.3276[/C][C]0.371914[/C][/ROW]
[ROW][C]32[/C][C]-0.017754[/C][C]-0.1836[/C][C]0.427318[/C][/ROW]
[ROW][C]33[/C][C]0.038759[/C][C]0.4009[/C][C]0.344636[/C][/ROW]
[ROW][C]34[/C][C]-0.062717[/C][C]-0.6487[/C][C]0.258945[/C][/ROW]
[ROW][C]35[/C][C]0.075749[/C][C]0.7836[/C][C]0.217517[/C][/ROW]
[ROW][C]36[/C][C]0.033485[/C][C]0.3464[/C][C]0.364872[/C][/ROW]
[ROW][C]37[/C][C]-0.161625[/C][C]-1.6719[/C][C]0.048737[/C][/ROW]
[ROW][C]38[/C][C]-0.023452[/C][C]-0.2426[/C][C]0.404394[/C][/ROW]
[ROW][C]39[/C][C]0.109774[/C][C]1.1355[/C][C]0.129348[/C][/ROW]
[ROW][C]40[/C][C]-0.031419[/C][C]-0.325[/C][C]0.372907[/C][/ROW]
[ROW][C]41[/C][C]-0.014254[/C][C]-0.1474[/C][C]0.44153[/C][/ROW]
[ROW][C]42[/C][C]0.034511[/C][C]0.357[/C][C]0.360904[/C][/ROW]
[ROW][C]43[/C][C]-0.047287[/C][C]-0.4891[/C][C]0.312873[/C][/ROW]
[ROW][C]44[/C][C]-0.00186[/C][C]-0.0192[/C][C]0.492341[/C][/ROW]
[ROW][C]45[/C][C]0.070812[/C][C]0.7325[/C][C]0.232737[/C][/ROW]
[ROW][C]46[/C][C]-0.107501[/C][C]-1.112[/C][C]0.134315[/C][/ROW]
[ROW][C]47[/C][C]-0.074072[/C][C]-0.7662[/C][C]0.222621[/C][/ROW]
[ROW][C]48[/C][C]0.094491[/C][C]0.9774[/C][C]0.165283[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113328&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113328&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
1-0.078293-0.80990.209906
2-0.300045-3.10370.001223
30.0218220.22570.410923
40.191151.97730.025291
5-0.041406-0.42830.334646
6-0.109656-1.13430.129603
70.0220990.22860.40981
80.0500610.51780.302822
90.0722670.74750.22819
10-0.019711-0.20390.419414
11-0.030247-0.31290.37749
120.0493750.51070.305294
13-0.111538-1.15380.125584
140.0010970.01140.495482
150.0737930.76330.223475
160.0729870.7550.225958
17-0.037912-0.39220.34786
18-0.094937-0.9820.16415
190.0678460.70180.242161
200.0868940.89880.185379
21-0.141431-1.4630.073203
22-0.09564-0.98930.162372
23-0.035493-0.36710.357118
240.1864561.92870.028208
250.0287930.29780.383204
26-0.067359-0.69680.243731
27-0.003717-0.03840.484702
28-0.001758-0.01820.492764
29-0.063086-0.65260.257717
30-0.135407-1.40070.082104
310.0316740.32760.371914
32-0.017754-0.18360.427318
330.0387590.40090.344636
34-0.062717-0.64870.258945
350.0757490.78360.217517
360.0334850.34640.364872
37-0.161625-1.67190.048737
38-0.023452-0.24260.404394
390.1097741.13550.129348
40-0.031419-0.3250.372907
41-0.014254-0.14740.44153
420.0345110.3570.360904
43-0.047287-0.48910.312873
44-0.00186-0.01920.492341
450.0708120.73250.232737
46-0.107501-1.1120.134315
47-0.074072-0.76620.222621
480.0944910.97740.165283







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.078293-0.80990.209906
2-0.308064-3.18660.000943
3-0.036714-0.37980.352433
40.1081961.11920.132784
5-0.014881-0.15390.438977
6-0.033209-0.34350.365943
7-0.006569-0.06790.472978
8-0.008687-0.08990.464282
90.0975231.00880.157676
100.0299720.310.378571
110.0117320.12140.451819
120.0466350.48240.315256
13-0.148404-1.53510.063855
140.0038620.03990.484105
150.0274380.28380.388546
160.0834950.86370.194847
170.0439280.45440.325231
18-0.08277-0.85620.196907
190.0176910.1830.427575
200.0489070.50590.306986
21-0.112577-1.16450.123404
22-0.036284-0.37530.354081
23-0.156251-1.61630.05449
240.1067231.10390.136046
250.0670630.69370.244684
260.0217460.22490.411225
270.0518110.53590.296556
28-0.079171-0.8190.207316
29-0.095557-0.98850.162581
30-0.141692-1.46570.072835
31-0.059165-0.6120.270917
32-0.069112-0.71490.238115
330.0601920.62260.267424
34-0.112616-1.16490.123323
350.1040941.07680.142004
36-0.015734-0.16280.435508
37-0.078361-0.81060.209706
380.0270710.280.390001
390.0029230.03020.487968
40-0.055182-0.57080.284662
410.0627080.64870.258977
420.0029170.03020.48799
43-0.086348-0.89320.186879
44-0.012207-0.12630.449878
450.0575370.59520.276495
46-0.032545-0.33670.36852
47-0.035787-0.37020.355988
480.0382110.39530.346719

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.078293 & -0.8099 & 0.209906 \tabularnewline
2 & -0.308064 & -3.1866 & 0.000943 \tabularnewline
3 & -0.036714 & -0.3798 & 0.352433 \tabularnewline
4 & 0.108196 & 1.1192 & 0.132784 \tabularnewline
5 & -0.014881 & -0.1539 & 0.438977 \tabularnewline
6 & -0.033209 & -0.3435 & 0.365943 \tabularnewline
7 & -0.006569 & -0.0679 & 0.472978 \tabularnewline
8 & -0.008687 & -0.0899 & 0.464282 \tabularnewline
9 & 0.097523 & 1.0088 & 0.157676 \tabularnewline
10 & 0.029972 & 0.31 & 0.378571 \tabularnewline
11 & 0.011732 & 0.1214 & 0.451819 \tabularnewline
12 & 0.046635 & 0.4824 & 0.315256 \tabularnewline
13 & -0.148404 & -1.5351 & 0.063855 \tabularnewline
14 & 0.003862 & 0.0399 & 0.484105 \tabularnewline
15 & 0.027438 & 0.2838 & 0.388546 \tabularnewline
16 & 0.083495 & 0.8637 & 0.194847 \tabularnewline
17 & 0.043928 & 0.4544 & 0.325231 \tabularnewline
18 & -0.08277 & -0.8562 & 0.196907 \tabularnewline
19 & 0.017691 & 0.183 & 0.427575 \tabularnewline
20 & 0.048907 & 0.5059 & 0.306986 \tabularnewline
21 & -0.112577 & -1.1645 & 0.123404 \tabularnewline
22 & -0.036284 & -0.3753 & 0.354081 \tabularnewline
23 & -0.156251 & -1.6163 & 0.05449 \tabularnewline
24 & 0.106723 & 1.1039 & 0.136046 \tabularnewline
25 & 0.067063 & 0.6937 & 0.244684 \tabularnewline
26 & 0.021746 & 0.2249 & 0.411225 \tabularnewline
27 & 0.051811 & 0.5359 & 0.296556 \tabularnewline
28 & -0.079171 & -0.819 & 0.207316 \tabularnewline
29 & -0.095557 & -0.9885 & 0.162581 \tabularnewline
30 & -0.141692 & -1.4657 & 0.072835 \tabularnewline
31 & -0.059165 & -0.612 & 0.270917 \tabularnewline
32 & -0.069112 & -0.7149 & 0.238115 \tabularnewline
33 & 0.060192 & 0.6226 & 0.267424 \tabularnewline
34 & -0.112616 & -1.1649 & 0.123323 \tabularnewline
35 & 0.104094 & 1.0768 & 0.142004 \tabularnewline
36 & -0.015734 & -0.1628 & 0.435508 \tabularnewline
37 & -0.078361 & -0.8106 & 0.209706 \tabularnewline
38 & 0.027071 & 0.28 & 0.390001 \tabularnewline
39 & 0.002923 & 0.0302 & 0.487968 \tabularnewline
40 & -0.055182 & -0.5708 & 0.284662 \tabularnewline
41 & 0.062708 & 0.6487 & 0.258977 \tabularnewline
42 & 0.002917 & 0.0302 & 0.48799 \tabularnewline
43 & -0.086348 & -0.8932 & 0.186879 \tabularnewline
44 & -0.012207 & -0.1263 & 0.449878 \tabularnewline
45 & 0.057537 & 0.5952 & 0.276495 \tabularnewline
46 & -0.032545 & -0.3367 & 0.36852 \tabularnewline
47 & -0.035787 & -0.3702 & 0.355988 \tabularnewline
48 & 0.038211 & 0.3953 & 0.346719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113328&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]-0.078293[/C][C]-0.8099[/C][C]0.209906[/C][/ROW]
[ROW][C]2[/C][C]-0.308064[/C][C]-3.1866[/C][C]0.000943[/C][/ROW]
[ROW][C]3[/C][C]-0.036714[/C][C]-0.3798[/C][C]0.352433[/C][/ROW]
[ROW][C]4[/C][C]0.108196[/C][C]1.1192[/C][C]0.132784[/C][/ROW]
[ROW][C]5[/C][C]-0.014881[/C][C]-0.1539[/C][C]0.438977[/C][/ROW]
[ROW][C]6[/C][C]-0.033209[/C][C]-0.3435[/C][C]0.365943[/C][/ROW]
[ROW][C]7[/C][C]-0.006569[/C][C]-0.0679[/C][C]0.472978[/C][/ROW]
[ROW][C]8[/C][C]-0.008687[/C][C]-0.0899[/C][C]0.464282[/C][/ROW]
[ROW][C]9[/C][C]0.097523[/C][C]1.0088[/C][C]0.157676[/C][/ROW]
[ROW][C]10[/C][C]0.029972[/C][C]0.31[/C][C]0.378571[/C][/ROW]
[ROW][C]11[/C][C]0.011732[/C][C]0.1214[/C][C]0.451819[/C][/ROW]
[ROW][C]12[/C][C]0.046635[/C][C]0.4824[/C][C]0.315256[/C][/ROW]
[ROW][C]13[/C][C]-0.148404[/C][C]-1.5351[/C][C]0.063855[/C][/ROW]
[ROW][C]14[/C][C]0.003862[/C][C]0.0399[/C][C]0.484105[/C][/ROW]
[ROW][C]15[/C][C]0.027438[/C][C]0.2838[/C][C]0.388546[/C][/ROW]
[ROW][C]16[/C][C]0.083495[/C][C]0.8637[/C][C]0.194847[/C][/ROW]
[ROW][C]17[/C][C]0.043928[/C][C]0.4544[/C][C]0.325231[/C][/ROW]
[ROW][C]18[/C][C]-0.08277[/C][C]-0.8562[/C][C]0.196907[/C][/ROW]
[ROW][C]19[/C][C]0.017691[/C][C]0.183[/C][C]0.427575[/C][/ROW]
[ROW][C]20[/C][C]0.048907[/C][C]0.5059[/C][C]0.306986[/C][/ROW]
[ROW][C]21[/C][C]-0.112577[/C][C]-1.1645[/C][C]0.123404[/C][/ROW]
[ROW][C]22[/C][C]-0.036284[/C][C]-0.3753[/C][C]0.354081[/C][/ROW]
[ROW][C]23[/C][C]-0.156251[/C][C]-1.6163[/C][C]0.05449[/C][/ROW]
[ROW][C]24[/C][C]0.106723[/C][C]1.1039[/C][C]0.136046[/C][/ROW]
[ROW][C]25[/C][C]0.067063[/C][C]0.6937[/C][C]0.244684[/C][/ROW]
[ROW][C]26[/C][C]0.021746[/C][C]0.2249[/C][C]0.411225[/C][/ROW]
[ROW][C]27[/C][C]0.051811[/C][C]0.5359[/C][C]0.296556[/C][/ROW]
[ROW][C]28[/C][C]-0.079171[/C][C]-0.819[/C][C]0.207316[/C][/ROW]
[ROW][C]29[/C][C]-0.095557[/C][C]-0.9885[/C][C]0.162581[/C][/ROW]
[ROW][C]30[/C][C]-0.141692[/C][C]-1.4657[/C][C]0.072835[/C][/ROW]
[ROW][C]31[/C][C]-0.059165[/C][C]-0.612[/C][C]0.270917[/C][/ROW]
[ROW][C]32[/C][C]-0.069112[/C][C]-0.7149[/C][C]0.238115[/C][/ROW]
[ROW][C]33[/C][C]0.060192[/C][C]0.6226[/C][C]0.267424[/C][/ROW]
[ROW][C]34[/C][C]-0.112616[/C][C]-1.1649[/C][C]0.123323[/C][/ROW]
[ROW][C]35[/C][C]0.104094[/C][C]1.0768[/C][C]0.142004[/C][/ROW]
[ROW][C]36[/C][C]-0.015734[/C][C]-0.1628[/C][C]0.435508[/C][/ROW]
[ROW][C]37[/C][C]-0.078361[/C][C]-0.8106[/C][C]0.209706[/C][/ROW]
[ROW][C]38[/C][C]0.027071[/C][C]0.28[/C][C]0.390001[/C][/ROW]
[ROW][C]39[/C][C]0.002923[/C][C]0.0302[/C][C]0.487968[/C][/ROW]
[ROW][C]40[/C][C]-0.055182[/C][C]-0.5708[/C][C]0.284662[/C][/ROW]
[ROW][C]41[/C][C]0.062708[/C][C]0.6487[/C][C]0.258977[/C][/ROW]
[ROW][C]42[/C][C]0.002917[/C][C]0.0302[/C][C]0.48799[/C][/ROW]
[ROW][C]43[/C][C]-0.086348[/C][C]-0.8932[/C][C]0.186879[/C][/ROW]
[ROW][C]44[/C][C]-0.012207[/C][C]-0.1263[/C][C]0.449878[/C][/ROW]
[ROW][C]45[/C][C]0.057537[/C][C]0.5952[/C][C]0.276495[/C][/ROW]
[ROW][C]46[/C][C]-0.032545[/C][C]-0.3367[/C][C]0.36852[/C][/ROW]
[ROW][C]47[/C][C]-0.035787[/C][C]-0.3702[/C][C]0.355988[/C][/ROW]
[ROW][C]48[/C][C]0.038211[/C][C]0.3953[/C][C]0.346719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113328&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113328&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
1-0.078293-0.80990.209906
2-0.308064-3.18660.000943
3-0.036714-0.37980.352433
40.1081961.11920.132784
5-0.014881-0.15390.438977
6-0.033209-0.34350.365943
7-0.006569-0.06790.472978
8-0.008687-0.08990.464282
90.0975231.00880.157676
100.0299720.310.378571
110.0117320.12140.451819
120.0466350.48240.315256
13-0.148404-1.53510.063855
140.0038620.03990.484105
150.0274380.28380.388546
160.0834950.86370.194847
170.0439280.45440.325231
18-0.08277-0.85620.196907
190.0176910.1830.427575
200.0489070.50590.306986
21-0.112577-1.16450.123404
22-0.036284-0.37530.354081
23-0.156251-1.61630.05449
240.1067231.10390.136046
250.0670630.69370.244684
260.0217460.22490.411225
270.0518110.53590.296556
28-0.079171-0.8190.207316
29-0.095557-0.98850.162581
30-0.141692-1.46570.072835
31-0.059165-0.6120.270917
32-0.069112-0.71490.238115
330.0601920.62260.267424
34-0.112616-1.16490.123323
350.1040941.07680.142004
36-0.015734-0.16280.435508
37-0.078361-0.81060.209706
380.0270710.280.390001
390.0029230.03020.487968
40-0.055182-0.57080.284662
410.0627080.64870.258977
420.0029170.03020.48799
43-0.086348-0.89320.186879
44-0.012207-0.12630.449878
450.0575370.59520.276495
46-0.032545-0.33670.36852
47-0.035787-0.37020.355988
480.0382110.39530.346719



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')