## 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 computationTue, 24 Nov 2009 08:58:42 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/24/t12590784025xwu8mbm68nydao.htm/, Retrieved Sun, 16 Jun 2024 22:28:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59137, Retrieved Sun, 16 Jun 2024 22:28:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact281
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [Workshop 8 - Meth...] [2009-11-24 15:58:42] [d904c6aa144b8c40108ebe5ec22fe1a0] [Current]
-    D            [(Partial) Autocorrelation Function] [Methode 1 ACF ] [2009-11-26 14:01:16] [23722951c28e05bb35cc9a97084fe0d9]
-   PD            [(Partial) Autocorrelation Function] [Methode 1 ACF D=1] [2009-11-26 14:08:23] [23722951c28e05bb35cc9a97084fe0d9]
-   PD            [(Partial) Autocorrelation Function] [methode 1 ACF d=1...] [2009-11-26 14:12:20] [23722951c28e05bb35cc9a97084fe0d9]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-28 00:42:43] [74be16979710d4c4e7c6647856088456]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-28 00:42:43] [74be16979710d4c4e7c6647856088456]
-   P               [(Partial) Autocorrelation Function] [] [2009-11-28 01:13:50] [74be16979710d4c4e7c6647856088456]
-   PD              [(Partial) Autocorrelation Function] [Workshop 8: Review] [2009-12-02 17:02:36] [3cb427d596a5d2eb77fa64560dc91319]
-   P               [(Partial) Autocorrelation Function] [Workshop 8: Review] [2009-12-02 17:40:29] [3cb427d596a5d2eb77fa64560dc91319]
-   PD              [(Partial) Autocorrelation Function] [Workshop 8: Review] [2009-12-02 17:50:22] [3cb427d596a5d2eb77fa64560dc91319]
-                 [(Partial) Autocorrelation Function] [workshop8/method1...] [2009-11-30 12:58:39] [24c4941ee50deadff4640c9c09cc70cb]
-                 [(Partial) Autocorrelation Function] [] [2009-11-30 16:42:34] [74be16979710d4c4e7c6647856088456]
-                   [(Partial) Autocorrelation Function] [] [2009-12-03 17:25:00] [74be16979710d4c4e7c6647856088456]
-   P             [(Partial) Autocorrelation Function] [WS 8 review] [2009-12-04 08:55:34] [830e13ac5e5ac1e5b21c6af0c149b21d]
-                 [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-12-07 12:43:58] [24c4941ee50deadff4640c9c09cc70cb]
-   P             [(Partial) Autocorrelation Function] [FINALE PAPER - he...] [2009-12-31 00:28:41] [1646a2766cb8c4a6f9d3b2fffef409b3]
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Dataseries X:
269645
267037
258113
262813
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710
295881

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59137&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59137&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59137&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.867341 7.3596 0 2 0.704692 5.9795 0 3 0.609126 5.1686 1e-06 4 0.56124 4.7623 5e-06 5 0.540757 4.5885 9e-06 6 0.494802 4.1985 3.8e-05 7 0.402055 3.4116 0.000531 8 0.283151 2.4026 0.009429 9 0.221334 1.8781 0.03221 10 0.221784 1.8819 0.031946 11 0.266107 2.258 0.013489 12 0.273964 2.3247 0.011457 13 0.12808 1.0868 0.140376 14 -0.020408 -0.1732 0.431503 15 -0.101877 -0.8645 0.195104 16 -0.13508 -1.1462 0.127755 17 -0.141203 -1.1981 0.117394 18 -0.163269 -1.3854 0.085106 19 -0.226888 -1.9252 0.029077 20 -0.310471 -2.6344 0.005156 21 -0.336733 -2.8573 0.002791 22 -0.308304 -2.616 0.005416 23 -0.254729 -2.1614 0.016993 24 -0.229649 -1.9486 0.027618 25 -0.320105 -2.7162 0.004132 26 -0.396017 -3.3603 0.000624 27 -0.402539 -3.4157 0.000525 28 -0.375808 -3.1888 0.001058 29 -0.328187 -2.7848 0.00342 30 -0.293699 -2.4921 0.007501 31 -0.299151 -2.5384 0.00665 32 -0.320168 -2.7167 0.004126 33 -0.286814 -2.4337 0.008714 34 -0.219001 -1.8583 0.033608 35 -0.13666 -1.1596 0.125022 36 -0.095312 -0.8088 0.210661

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.867341 & 7.3596 & 0 \tabularnewline
2 & 0.704692 & 5.9795 & 0 \tabularnewline
3 & 0.609126 & 5.1686 & 1e-06 \tabularnewline
4 & 0.56124 & 4.7623 & 5e-06 \tabularnewline
5 & 0.540757 & 4.5885 & 9e-06 \tabularnewline
6 & 0.494802 & 4.1985 & 3.8e-05 \tabularnewline
7 & 0.402055 & 3.4116 & 0.000531 \tabularnewline
8 & 0.283151 & 2.4026 & 0.009429 \tabularnewline
9 & 0.221334 & 1.8781 & 0.03221 \tabularnewline
10 & 0.221784 & 1.8819 & 0.031946 \tabularnewline
11 & 0.266107 & 2.258 & 0.013489 \tabularnewline
12 & 0.273964 & 2.3247 & 0.011457 \tabularnewline
13 & 0.12808 & 1.0868 & 0.140376 \tabularnewline
14 & -0.020408 & -0.1732 & 0.431503 \tabularnewline
15 & -0.101877 & -0.8645 & 0.195104 \tabularnewline
16 & -0.13508 & -1.1462 & 0.127755 \tabularnewline
17 & -0.141203 & -1.1981 & 0.117394 \tabularnewline
18 & -0.163269 & -1.3854 & 0.085106 \tabularnewline
19 & -0.226888 & -1.9252 & 0.029077 \tabularnewline
20 & -0.310471 & -2.6344 & 0.005156 \tabularnewline
21 & -0.336733 & -2.8573 & 0.002791 \tabularnewline
22 & -0.308304 & -2.616 & 0.005416 \tabularnewline
23 & -0.254729 & -2.1614 & 0.016993 \tabularnewline
24 & -0.229649 & -1.9486 & 0.027618 \tabularnewline
25 & -0.320105 & -2.7162 & 0.004132 \tabularnewline
26 & -0.396017 & -3.3603 & 0.000624 \tabularnewline
27 & -0.402539 & -3.4157 & 0.000525 \tabularnewline
28 & -0.375808 & -3.1888 & 0.001058 \tabularnewline
29 & -0.328187 & -2.7848 & 0.00342 \tabularnewline
30 & -0.293699 & -2.4921 & 0.007501 \tabularnewline
31 & -0.299151 & -2.5384 & 0.00665 \tabularnewline
32 & -0.320168 & -2.7167 & 0.004126 \tabularnewline
33 & -0.286814 & -2.4337 & 0.008714 \tabularnewline
34 & -0.219001 & -1.8583 & 0.033608 \tabularnewline
35 & -0.13666 & -1.1596 & 0.125022 \tabularnewline
36 & -0.095312 & -0.8088 & 0.210661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59137&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]0.867341[/C][C]7.3596[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.704692[/C][C]5.9795[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.609126[/C][C]5.1686[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.56124[/C][C]4.7623[/C][C]5e-06[/C][/ROW]
[ROW][C]5[/C][C]0.540757[/C][C]4.5885[/C][C]9e-06[/C][/ROW]
[ROW][C]6[/C][C]0.494802[/C][C]4.1985[/C][C]3.8e-05[/C][/ROW]
[ROW][C]7[/C][C]0.402055[/C][C]3.4116[/C][C]0.000531[/C][/ROW]
[ROW][C]8[/C][C]0.283151[/C][C]2.4026[/C][C]0.009429[/C][/ROW]
[ROW][C]9[/C][C]0.221334[/C][C]1.8781[/C][C]0.03221[/C][/ROW]
[ROW][C]10[/C][C]0.221784[/C][C]1.8819[/C][C]0.031946[/C][/ROW]
[ROW][C]11[/C][C]0.266107[/C][C]2.258[/C][C]0.013489[/C][/ROW]
[ROW][C]12[/C][C]0.273964[/C][C]2.3247[/C][C]0.011457[/C][/ROW]
[ROW][C]13[/C][C]0.12808[/C][C]1.0868[/C][C]0.140376[/C][/ROW]
[ROW][C]14[/C][C]-0.020408[/C][C]-0.1732[/C][C]0.431503[/C][/ROW]
[ROW][C]15[/C][C]-0.101877[/C][C]-0.8645[/C][C]0.195104[/C][/ROW]
[ROW][C]16[/C][C]-0.13508[/C][C]-1.1462[/C][C]0.127755[/C][/ROW]
[ROW][C]17[/C][C]-0.141203[/C][C]-1.1981[/C][C]0.117394[/C][/ROW]
[ROW][C]18[/C][C]-0.163269[/C][C]-1.3854[/C][C]0.085106[/C][/ROW]
[ROW][C]19[/C][C]-0.226888[/C][C]-1.9252[/C][C]0.029077[/C][/ROW]
[ROW][C]20[/C][C]-0.310471[/C][C]-2.6344[/C][C]0.005156[/C][/ROW]
[ROW][C]21[/C][C]-0.336733[/C][C]-2.8573[/C][C]0.002791[/C][/ROW]
[ROW][C]22[/C][C]-0.308304[/C][C]-2.616[/C][C]0.005416[/C][/ROW]
[ROW][C]23[/C][C]-0.254729[/C][C]-2.1614[/C][C]0.016993[/C][/ROW]
[ROW][C]24[/C][C]-0.229649[/C][C]-1.9486[/C][C]0.027618[/C][/ROW]
[ROW][C]25[/C][C]-0.320105[/C][C]-2.7162[/C][C]0.004132[/C][/ROW]
[ROW][C]26[/C][C]-0.396017[/C][C]-3.3603[/C][C]0.000624[/C][/ROW]
[ROW][C]27[/C][C]-0.402539[/C][C]-3.4157[/C][C]0.000525[/C][/ROW]
[ROW][C]28[/C][C]-0.375808[/C][C]-3.1888[/C][C]0.001058[/C][/ROW]
[ROW][C]29[/C][C]-0.328187[/C][C]-2.7848[/C][C]0.00342[/C][/ROW]
[ROW][C]30[/C][C]-0.293699[/C][C]-2.4921[/C][C]0.007501[/C][/ROW]
[ROW][C]31[/C][C]-0.299151[/C][C]-2.5384[/C][C]0.00665[/C][/ROW]
[ROW][C]32[/C][C]-0.320168[/C][C]-2.7167[/C][C]0.004126[/C][/ROW]
[ROW][C]33[/C][C]-0.286814[/C][C]-2.4337[/C][C]0.008714[/C][/ROW]
[ROW][C]34[/C][C]-0.219001[/C][C]-1.8583[/C][C]0.033608[/C][/ROW]
[ROW][C]35[/C][C]-0.13666[/C][C]-1.1596[/C][C]0.125022[/C][/ROW]
[ROW][C]36[/C][C]-0.095312[/C][C]-0.8088[/C][C]0.210661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59137&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59137&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 k ACF(k) T-STAT P-value 1 0.867341 7.3596 0 2 0.704692 5.9795 0 3 0.609126 5.1686 1e-06 4 0.56124 4.7623 5e-06 5 0.540757 4.5885 9e-06 6 0.494802 4.1985 3.8e-05 7 0.402055 3.4116 0.000531 8 0.283151 2.4026 0.009429 9 0.221334 1.8781 0.03221 10 0.221784 1.8819 0.031946 11 0.266107 2.258 0.013489 12 0.273964 2.3247 0.011457 13 0.12808 1.0868 0.140376 14 -0.020408 -0.1732 0.431503 15 -0.101877 -0.8645 0.195104 16 -0.13508 -1.1462 0.127755 17 -0.141203 -1.1981 0.117394 18 -0.163269 -1.3854 0.085106 19 -0.226888 -1.9252 0.029077 20 -0.310471 -2.6344 0.005156 21 -0.336733 -2.8573 0.002791 22 -0.308304 -2.616 0.005416 23 -0.254729 -2.1614 0.016993 24 -0.229649 -1.9486 0.027618 25 -0.320105 -2.7162 0.004132 26 -0.396017 -3.3603 0.000624 27 -0.402539 -3.4157 0.000525 28 -0.375808 -3.1888 0.001058 29 -0.328187 -2.7848 0.00342 30 -0.293699 -2.4921 0.007501 31 -0.299151 -2.5384 0.00665 32 -0.320168 -2.7167 0.004126 33 -0.286814 -2.4337 0.008714 34 -0.219001 -1.8583 0.033608 35 -0.13666 -1.1596 0.125022 36 -0.095312 -0.8088 0.210661

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.867341 7.3596 0 2 -0.192106 -1.6301 0.053727 3 0.19751 1.6759 0.049045 4 0.071061 0.603 0.274211 5 0.105884 0.8985 0.185968 6 -0.08858 -0.7516 0.227362 7 -0.134514 -1.1414 0.128745 8 -0.146787 -1.2455 0.108488 9 0.127074 1.0783 0.14226 10 0.081408 0.6908 0.245965 11 0.195346 1.6576 0.050878 12 -0.079754 -0.6767 0.25037 13 -0.527881 -4.4792 1.4e-05 14 0.010489 0.089 0.464664 15 -0.068907 -0.5847 0.280291 16 -0.005081 -0.0431 0.482865 17 0.052167 0.4426 0.329674 18 0.029985 0.2544 0.399943 19 -0.007695 -0.0653 0.47406 20 -0.040538 -0.344 0.365933 21 -0.061301 -0.5202 0.302276 22 -0.052447 -0.445 0.328819 23 -0.017157 -0.1456 0.442329 24 0.031969 0.2713 0.393483 25 -0.161621 -1.3714 0.087254 26 0.085523 0.7257 0.235191 27 0.017769 0.1508 0.440287 28 -0.050485 -0.4284 0.334828 29 0.039506 0.3352 0.369216 30 -0.00068 -0.0058 0.497705 31 -0.012524 -0.1063 0.457832 32 0.024981 0.212 0.416365 33 -0.00834 -0.0708 0.471889 34 -0.048245 -0.4094 0.34174 35 0.074893 0.6355 0.263562 36 -0.09786 -0.8304 0.204538

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.867341 & 7.3596 & 0 \tabularnewline
2 & -0.192106 & -1.6301 & 0.053727 \tabularnewline
3 & 0.19751 & 1.6759 & 0.049045 \tabularnewline
4 & 0.071061 & 0.603 & 0.274211 \tabularnewline
5 & 0.105884 & 0.8985 & 0.185968 \tabularnewline
6 & -0.08858 & -0.7516 & 0.227362 \tabularnewline
7 & -0.134514 & -1.1414 & 0.128745 \tabularnewline
8 & -0.146787 & -1.2455 & 0.108488 \tabularnewline
9 & 0.127074 & 1.0783 & 0.14226 \tabularnewline
10 & 0.081408 & 0.6908 & 0.245965 \tabularnewline
11 & 0.195346 & 1.6576 & 0.050878 \tabularnewline
12 & -0.079754 & -0.6767 & 0.25037 \tabularnewline
13 & -0.527881 & -4.4792 & 1.4e-05 \tabularnewline
14 & 0.010489 & 0.089 & 0.464664 \tabularnewline
15 & -0.068907 & -0.5847 & 0.280291 \tabularnewline
16 & -0.005081 & -0.0431 & 0.482865 \tabularnewline
17 & 0.052167 & 0.4426 & 0.329674 \tabularnewline
18 & 0.029985 & 0.2544 & 0.399943 \tabularnewline
19 & -0.007695 & -0.0653 & 0.47406 \tabularnewline
20 & -0.040538 & -0.344 & 0.365933 \tabularnewline
21 & -0.061301 & -0.5202 & 0.302276 \tabularnewline
22 & -0.052447 & -0.445 & 0.328819 \tabularnewline
23 & -0.017157 & -0.1456 & 0.442329 \tabularnewline
24 & 0.031969 & 0.2713 & 0.393483 \tabularnewline
25 & -0.161621 & -1.3714 & 0.087254 \tabularnewline
26 & 0.085523 & 0.7257 & 0.235191 \tabularnewline
27 & 0.017769 & 0.1508 & 0.440287 \tabularnewline
28 & -0.050485 & -0.4284 & 0.334828 \tabularnewline
29 & 0.039506 & 0.3352 & 0.369216 \tabularnewline
30 & -0.00068 & -0.0058 & 0.497705 \tabularnewline
31 & -0.012524 & -0.1063 & 0.457832 \tabularnewline
32 & 0.024981 & 0.212 & 0.416365 \tabularnewline
33 & -0.00834 & -0.0708 & 0.471889 \tabularnewline
34 & -0.048245 & -0.4094 & 0.34174 \tabularnewline
35 & 0.074893 & 0.6355 & 0.263562 \tabularnewline
36 & -0.09786 & -0.8304 & 0.204538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59137&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]0.867341[/C][C]7.3596[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.192106[/C][C]-1.6301[/C][C]0.053727[/C][/ROW]
[ROW][C]3[/C][C]0.19751[/C][C]1.6759[/C][C]0.049045[/C][/ROW]
[ROW][C]4[/C][C]0.071061[/C][C]0.603[/C][C]0.274211[/C][/ROW]
[ROW][C]5[/C][C]0.105884[/C][C]0.8985[/C][C]0.185968[/C][/ROW]
[ROW][C]6[/C][C]-0.08858[/C][C]-0.7516[/C][C]0.227362[/C][/ROW]
[ROW][C]7[/C][C]-0.134514[/C][C]-1.1414[/C][C]0.128745[/C][/ROW]
[ROW][C]8[/C][C]-0.146787[/C][C]-1.2455[/C][C]0.108488[/C][/ROW]
[ROW][C]9[/C][C]0.127074[/C][C]1.0783[/C][C]0.14226[/C][/ROW]
[ROW][C]10[/C][C]0.081408[/C][C]0.6908[/C][C]0.245965[/C][/ROW]
[ROW][C]11[/C][C]0.195346[/C][C]1.6576[/C][C]0.050878[/C][/ROW]
[ROW][C]12[/C][C]-0.079754[/C][C]-0.6767[/C][C]0.25037[/C][/ROW]
[ROW][C]13[/C][C]-0.527881[/C][C]-4.4792[/C][C]1.4e-05[/C][/ROW]
[ROW][C]14[/C][C]0.010489[/C][C]0.089[/C][C]0.464664[/C][/ROW]
[ROW][C]15[/C][C]-0.068907[/C][C]-0.5847[/C][C]0.280291[/C][/ROW]
[ROW][C]16[/C][C]-0.005081[/C][C]-0.0431[/C][C]0.482865[/C][/ROW]
[ROW][C]17[/C][C]0.052167[/C][C]0.4426[/C][C]0.329674[/C][/ROW]
[ROW][C]18[/C][C]0.029985[/C][C]0.2544[/C][C]0.399943[/C][/ROW]
[ROW][C]19[/C][C]-0.007695[/C][C]-0.0653[/C][C]0.47406[/C][/ROW]
[ROW][C]20[/C][C]-0.040538[/C][C]-0.344[/C][C]0.365933[/C][/ROW]
[ROW][C]21[/C][C]-0.061301[/C][C]-0.5202[/C][C]0.302276[/C][/ROW]
[ROW][C]22[/C][C]-0.052447[/C][C]-0.445[/C][C]0.328819[/C][/ROW]
[ROW][C]23[/C][C]-0.017157[/C][C]-0.1456[/C][C]0.442329[/C][/ROW]
[ROW][C]24[/C][C]0.031969[/C][C]0.2713[/C][C]0.393483[/C][/ROW]
[ROW][C]25[/C][C]-0.161621[/C][C]-1.3714[/C][C]0.087254[/C][/ROW]
[ROW][C]26[/C][C]0.085523[/C][C]0.7257[/C][C]0.235191[/C][/ROW]
[ROW][C]27[/C][C]0.017769[/C][C]0.1508[/C][C]0.440287[/C][/ROW]
[ROW][C]28[/C][C]-0.050485[/C][C]-0.4284[/C][C]0.334828[/C][/ROW]
[ROW][C]29[/C][C]0.039506[/C][C]0.3352[/C][C]0.369216[/C][/ROW]
[ROW][C]30[/C][C]-0.00068[/C][C]-0.0058[/C][C]0.497705[/C][/ROW]
[ROW][C]31[/C][C]-0.012524[/C][C]-0.1063[/C][C]0.457832[/C][/ROW]
[ROW][C]32[/C][C]0.024981[/C][C]0.212[/C][C]0.416365[/C][/ROW]
[ROW][C]33[/C][C]-0.00834[/C][C]-0.0708[/C][C]0.471889[/C][/ROW]
[ROW][C]34[/C][C]-0.048245[/C][C]-0.4094[/C][C]0.34174[/C][/ROW]
[ROW][C]35[/C][C]0.074893[/C][C]0.6355[/C][C]0.263562[/C][/ROW]
[ROW][C]36[/C][C]-0.09786[/C][C]-0.8304[/C][C]0.204538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59137&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59137&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 k PACF(k) T-STAT P-value 1 0.867341 7.3596 0 2 -0.192106 -1.6301 0.053727 3 0.19751 1.6759 0.049045 4 0.071061 0.603 0.274211 5 0.105884 0.8985 0.185968 6 -0.08858 -0.7516 0.227362 7 -0.134514 -1.1414 0.128745 8 -0.146787 -1.2455 0.108488 9 0.127074 1.0783 0.14226 10 0.081408 0.6908 0.245965 11 0.195346 1.6576 0.050878 12 -0.079754 -0.6767 0.25037 13 -0.527881 -4.4792 1.4e-05 14 0.010489 0.089 0.464664 15 -0.068907 -0.5847 0.280291 16 -0.005081 -0.0431 0.482865 17 0.052167 0.4426 0.329674 18 0.029985 0.2544 0.399943 19 -0.007695 -0.0653 0.47406 20 -0.040538 -0.344 0.365933 21 -0.061301 -0.5202 0.302276 22 -0.052447 -0.445 0.328819 23 -0.017157 -0.1456 0.442329 24 0.031969 0.2713 0.393483 25 -0.161621 -1.3714 0.087254 26 0.085523 0.7257 0.235191 27 0.017769 0.1508 0.440287 28 -0.050485 -0.4284 0.334828 29 0.039506 0.3352 0.369216 30 -0.00068 -0.0058 0.497705 31 -0.012524 -0.1063 0.457832 32 0.024981 0.212 0.416365 33 -0.00834 -0.0708 0.471889 34 -0.048245 -0.4094 0.34174 35 0.074893 0.6355 0.263562 36 -0.09786 -0.8304 0.204538

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]*sqrtna<-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]*sqrtna<-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')