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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 computationWed, 30 Dec 2009 02:06:41 -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/Dec/30/t1262164040zpe099r0l4lbin7.htm/, Retrieved Mon, 29 Apr 2024 03:02:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71222, Retrieved Mon, 29 Apr 2024 03:02:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161
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]
- RMPD        [Standard Deviation-Mean Plot] [Paper SMP] [2009-12-19 15:14:41] [85be98bd9ebcfd4d73e77f8552419c9a]
- RMP           [(Partial) Autocorrelation Function] [Paper ACF] [2009-12-19 16:26:13] [85be98bd9ebcfd4d73e77f8552419c9a]
-   P             [(Partial) Autocorrelation Function] [acf] [2009-12-28 12:35:39] [85be98bd9ebcfd4d73e77f8552419c9a]
-   P               [(Partial) Autocorrelation Function] [acf] [2009-12-28 12:39:59] [85be98bd9ebcfd4d73e77f8552419c9a]
-   P                 [(Partial) Autocorrelation Function] [acf] [2009-12-28 12:46:27] [85be98bd9ebcfd4d73e77f8552419c9a]
-   P                     [(Partial) Autocorrelation Function] [acf] [2009-12-30 09:06:41] [5cd0e65b1f56b3935a0672588b930e12] [Current]
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Dataseries X:
13.4
13.5
14.8
14.3
14.3
14
13.2
12.2
14.3
15.7
14.2
14.6
14.5
14.3
15.3
14.4
13.7
14.2
13.5
11.9
14.6
15.6
14.1
14.9
14.2
14.6
17.2
15.4
14.3
17.5
14.5
14.4
16.6
16.7
16.6
16.9
15.7
16.4
18.4
16.9
16.5
18.3
15.1
15.7
18.1
16.8
18.9
19
18.1
17.8
21.5
17.1
18.7
19
16.4
16.9
18.6
19.3
19.4
17.6
18.6
18.1
20.4
18.1
19.6
19.9
19.2
17.8
19.2
22
21.1
19.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71222&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71222&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71222&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2664312.06380.021687
20.3503792.7140.004333
30.4694783.63660.000288
40.1376511.06620.145294
50.1195960.92640.178978
60.1780031.37880.086536
7-0.123993-0.96040.170342
80.0254510.19710.422191
9-0.009812-0.0760.469834
10-0.229403-1.77690.040323
11-0.120402-0.93260.177375
12-0.213995-1.65760.051309
13-0.206915-1.60280.05712
14-0.040913-0.31690.376204
15-0.162193-1.25630.106931
16-0.129273-1.00130.160341
170.0957380.74160.230617
18-0.022176-0.17180.432097
19-0.014065-0.10890.456805
207.2e-056e-040.499777
210.0479480.37140.355823
22-0.128974-0.9990.160896
230.0425380.32950.371465
24-0.181668-1.40720.082265
25-0.187264-1.45050.076058
26-0.047563-0.36840.356927
27-0.21409-1.65830.051235
28-0.181903-1.4090.081996
29-0.09562-0.74070.230891
30-0.217551-1.68510.048578
31-0.104966-0.81310.209698
32-0.057769-0.44750.328071
33-0.209774-1.62490.054713
340.0186290.14430.442873
350.0959550.74330.230112
36-0.011427-0.08850.464881
370.18911.46480.074103
380.1199080.92880.178355
390.0885810.68610.247632
400.2325431.80130.038343
410.0663960.51430.304465
420.0741820.57460.283852
430.145021.12330.132888
440.0680930.52740.299916
450.0396150.30690.380007
460.0429220.33250.370346
47-0.032757-0.25370.400284
48-0.031866-0.24680.402941
49-0.041099-0.31840.375662
50-0.093815-0.72670.235121
51-0.057882-0.44840.327756
52-0.048848-0.37840.353243
53-0.062099-0.4810.316128
54-0.04864-0.37680.353839
55-0.045442-0.3520.363039
56-0.026528-0.20550.418945
57-0.010165-0.07870.468752
58-0.003601-0.02790.48892
590.0002220.00170.499318
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.266431 & 2.0638 & 0.021687 \tabularnewline
2 & 0.350379 & 2.714 & 0.004333 \tabularnewline
3 & 0.469478 & 3.6366 & 0.000288 \tabularnewline
4 & 0.137651 & 1.0662 & 0.145294 \tabularnewline
5 & 0.119596 & 0.9264 & 0.178978 \tabularnewline
6 & 0.178003 & 1.3788 & 0.086536 \tabularnewline
7 & -0.123993 & -0.9604 & 0.170342 \tabularnewline
8 & 0.025451 & 0.1971 & 0.422191 \tabularnewline
9 & -0.009812 & -0.076 & 0.469834 \tabularnewline
10 & -0.229403 & -1.7769 & 0.040323 \tabularnewline
11 & -0.120402 & -0.9326 & 0.177375 \tabularnewline
12 & -0.213995 & -1.6576 & 0.051309 \tabularnewline
13 & -0.206915 & -1.6028 & 0.05712 \tabularnewline
14 & -0.040913 & -0.3169 & 0.376204 \tabularnewline
15 & -0.162193 & -1.2563 & 0.106931 \tabularnewline
16 & -0.129273 & -1.0013 & 0.160341 \tabularnewline
17 & 0.095738 & 0.7416 & 0.230617 \tabularnewline
18 & -0.022176 & -0.1718 & 0.432097 \tabularnewline
19 & -0.014065 & -0.1089 & 0.456805 \tabularnewline
20 & 7.2e-05 & 6e-04 & 0.499777 \tabularnewline
21 & 0.047948 & 0.3714 & 0.355823 \tabularnewline
22 & -0.128974 & -0.999 & 0.160896 \tabularnewline
23 & 0.042538 & 0.3295 & 0.371465 \tabularnewline
24 & -0.181668 & -1.4072 & 0.082265 \tabularnewline
25 & -0.187264 & -1.4505 & 0.076058 \tabularnewline
26 & -0.047563 & -0.3684 & 0.356927 \tabularnewline
27 & -0.21409 & -1.6583 & 0.051235 \tabularnewline
28 & -0.181903 & -1.409 & 0.081996 \tabularnewline
29 & -0.09562 & -0.7407 & 0.230891 \tabularnewline
30 & -0.217551 & -1.6851 & 0.048578 \tabularnewline
31 & -0.104966 & -0.8131 & 0.209698 \tabularnewline
32 & -0.057769 & -0.4475 & 0.328071 \tabularnewline
33 & -0.209774 & -1.6249 & 0.054713 \tabularnewline
34 & 0.018629 & 0.1443 & 0.442873 \tabularnewline
35 & 0.095955 & 0.7433 & 0.230112 \tabularnewline
36 & -0.011427 & -0.0885 & 0.464881 \tabularnewline
37 & 0.1891 & 1.4648 & 0.074103 \tabularnewline
38 & 0.119908 & 0.9288 & 0.178355 \tabularnewline
39 & 0.088581 & 0.6861 & 0.247632 \tabularnewline
40 & 0.232543 & 1.8013 & 0.038343 \tabularnewline
41 & 0.066396 & 0.5143 & 0.304465 \tabularnewline
42 & 0.074182 & 0.5746 & 0.283852 \tabularnewline
43 & 0.14502 & 1.1233 & 0.132888 \tabularnewline
44 & 0.068093 & 0.5274 & 0.299916 \tabularnewline
45 & 0.039615 & 0.3069 & 0.380007 \tabularnewline
46 & 0.042922 & 0.3325 & 0.370346 \tabularnewline
47 & -0.032757 & -0.2537 & 0.400284 \tabularnewline
48 & -0.031866 & -0.2468 & 0.402941 \tabularnewline
49 & -0.041099 & -0.3184 & 0.375662 \tabularnewline
50 & -0.093815 & -0.7267 & 0.235121 \tabularnewline
51 & -0.057882 & -0.4484 & 0.327756 \tabularnewline
52 & -0.048848 & -0.3784 & 0.353243 \tabularnewline
53 & -0.062099 & -0.481 & 0.316128 \tabularnewline
54 & -0.04864 & -0.3768 & 0.353839 \tabularnewline
55 & -0.045442 & -0.352 & 0.363039 \tabularnewline
56 & -0.026528 & -0.2055 & 0.418945 \tabularnewline
57 & -0.010165 & -0.0787 & 0.468752 \tabularnewline
58 & -0.003601 & -0.0279 & 0.48892 \tabularnewline
59 & 0.000222 & 0.0017 & 0.499318 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71222&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]0.266431[/C][C]2.0638[/C][C]0.021687[/C][/ROW]
[ROW][C]2[/C][C]0.350379[/C][C]2.714[/C][C]0.004333[/C][/ROW]
[ROW][C]3[/C][C]0.469478[/C][C]3.6366[/C][C]0.000288[/C][/ROW]
[ROW][C]4[/C][C]0.137651[/C][C]1.0662[/C][C]0.145294[/C][/ROW]
[ROW][C]5[/C][C]0.119596[/C][C]0.9264[/C][C]0.178978[/C][/ROW]
[ROW][C]6[/C][C]0.178003[/C][C]1.3788[/C][C]0.086536[/C][/ROW]
[ROW][C]7[/C][C]-0.123993[/C][C]-0.9604[/C][C]0.170342[/C][/ROW]
[ROW][C]8[/C][C]0.025451[/C][C]0.1971[/C][C]0.422191[/C][/ROW]
[ROW][C]9[/C][C]-0.009812[/C][C]-0.076[/C][C]0.469834[/C][/ROW]
[ROW][C]10[/C][C]-0.229403[/C][C]-1.7769[/C][C]0.040323[/C][/ROW]
[ROW][C]11[/C][C]-0.120402[/C][C]-0.9326[/C][C]0.177375[/C][/ROW]
[ROW][C]12[/C][C]-0.213995[/C][C]-1.6576[/C][C]0.051309[/C][/ROW]
[ROW][C]13[/C][C]-0.206915[/C][C]-1.6028[/C][C]0.05712[/C][/ROW]
[ROW][C]14[/C][C]-0.040913[/C][C]-0.3169[/C][C]0.376204[/C][/ROW]
[ROW][C]15[/C][C]-0.162193[/C][C]-1.2563[/C][C]0.106931[/C][/ROW]
[ROW][C]16[/C][C]-0.129273[/C][C]-1.0013[/C][C]0.160341[/C][/ROW]
[ROW][C]17[/C][C]0.095738[/C][C]0.7416[/C][C]0.230617[/C][/ROW]
[ROW][C]18[/C][C]-0.022176[/C][C]-0.1718[/C][C]0.432097[/C][/ROW]
[ROW][C]19[/C][C]-0.014065[/C][C]-0.1089[/C][C]0.456805[/C][/ROW]
[ROW][C]20[/C][C]7.2e-05[/C][C]6e-04[/C][C]0.499777[/C][/ROW]
[ROW][C]21[/C][C]0.047948[/C][C]0.3714[/C][C]0.355823[/C][/ROW]
[ROW][C]22[/C][C]-0.128974[/C][C]-0.999[/C][C]0.160896[/C][/ROW]
[ROW][C]23[/C][C]0.042538[/C][C]0.3295[/C][C]0.371465[/C][/ROW]
[ROW][C]24[/C][C]-0.181668[/C][C]-1.4072[/C][C]0.082265[/C][/ROW]
[ROW][C]25[/C][C]-0.187264[/C][C]-1.4505[/C][C]0.076058[/C][/ROW]
[ROW][C]26[/C][C]-0.047563[/C][C]-0.3684[/C][C]0.356927[/C][/ROW]
[ROW][C]27[/C][C]-0.21409[/C][C]-1.6583[/C][C]0.051235[/C][/ROW]
[ROW][C]28[/C][C]-0.181903[/C][C]-1.409[/C][C]0.081996[/C][/ROW]
[ROW][C]29[/C][C]-0.09562[/C][C]-0.7407[/C][C]0.230891[/C][/ROW]
[ROW][C]30[/C][C]-0.217551[/C][C]-1.6851[/C][C]0.048578[/C][/ROW]
[ROW][C]31[/C][C]-0.104966[/C][C]-0.8131[/C][C]0.209698[/C][/ROW]
[ROW][C]32[/C][C]-0.057769[/C][C]-0.4475[/C][C]0.328071[/C][/ROW]
[ROW][C]33[/C][C]-0.209774[/C][C]-1.6249[/C][C]0.054713[/C][/ROW]
[ROW][C]34[/C][C]0.018629[/C][C]0.1443[/C][C]0.442873[/C][/ROW]
[ROW][C]35[/C][C]0.095955[/C][C]0.7433[/C][C]0.230112[/C][/ROW]
[ROW][C]36[/C][C]-0.011427[/C][C]-0.0885[/C][C]0.464881[/C][/ROW]
[ROW][C]37[/C][C]0.1891[/C][C]1.4648[/C][C]0.074103[/C][/ROW]
[ROW][C]38[/C][C]0.119908[/C][C]0.9288[/C][C]0.178355[/C][/ROW]
[ROW][C]39[/C][C]0.088581[/C][C]0.6861[/C][C]0.247632[/C][/ROW]
[ROW][C]40[/C][C]0.232543[/C][C]1.8013[/C][C]0.038343[/C][/ROW]
[ROW][C]41[/C][C]0.066396[/C][C]0.5143[/C][C]0.304465[/C][/ROW]
[ROW][C]42[/C][C]0.074182[/C][C]0.5746[/C][C]0.283852[/C][/ROW]
[ROW][C]43[/C][C]0.14502[/C][C]1.1233[/C][C]0.132888[/C][/ROW]
[ROW][C]44[/C][C]0.068093[/C][C]0.5274[/C][C]0.299916[/C][/ROW]
[ROW][C]45[/C][C]0.039615[/C][C]0.3069[/C][C]0.380007[/C][/ROW]
[ROW][C]46[/C][C]0.042922[/C][C]0.3325[/C][C]0.370346[/C][/ROW]
[ROW][C]47[/C][C]-0.032757[/C][C]-0.2537[/C][C]0.400284[/C][/ROW]
[ROW][C]48[/C][C]-0.031866[/C][C]-0.2468[/C][C]0.402941[/C][/ROW]
[ROW][C]49[/C][C]-0.041099[/C][C]-0.3184[/C][C]0.375662[/C][/ROW]
[ROW][C]50[/C][C]-0.093815[/C][C]-0.7267[/C][C]0.235121[/C][/ROW]
[ROW][C]51[/C][C]-0.057882[/C][C]-0.4484[/C][C]0.327756[/C][/ROW]
[ROW][C]52[/C][C]-0.048848[/C][C]-0.3784[/C][C]0.353243[/C][/ROW]
[ROW][C]53[/C][C]-0.062099[/C][C]-0.481[/C][C]0.316128[/C][/ROW]
[ROW][C]54[/C][C]-0.04864[/C][C]-0.3768[/C][C]0.353839[/C][/ROW]
[ROW][C]55[/C][C]-0.045442[/C][C]-0.352[/C][C]0.363039[/C][/ROW]
[ROW][C]56[/C][C]-0.026528[/C][C]-0.2055[/C][C]0.418945[/C][/ROW]
[ROW][C]57[/C][C]-0.010165[/C][C]-0.0787[/C][C]0.468752[/C][/ROW]
[ROW][C]58[/C][C]-0.003601[/C][C]-0.0279[/C][C]0.48892[/C][/ROW]
[ROW][C]59[/C][C]0.000222[/C][C]0.0017[/C][C]0.499318[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71222&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71222&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
10.2664312.06380.021687
20.3503792.7140.004333
30.4694783.63660.000288
40.1376511.06620.145294
50.1195960.92640.178978
60.1780031.37880.086536
7-0.123993-0.96040.170342
80.0254510.19710.422191
9-0.009812-0.0760.469834
10-0.229403-1.77690.040323
11-0.120402-0.93260.177375
12-0.213995-1.65760.051309
13-0.206915-1.60280.05712
14-0.040913-0.31690.376204
15-0.162193-1.25630.106931
16-0.129273-1.00130.160341
170.0957380.74160.230617
18-0.022176-0.17180.432097
19-0.014065-0.10890.456805
207.2e-056e-040.499777
210.0479480.37140.355823
22-0.128974-0.9990.160896
230.0425380.32950.371465
24-0.181668-1.40720.082265
25-0.187264-1.45050.076058
26-0.047563-0.36840.356927
27-0.21409-1.65830.051235
28-0.181903-1.4090.081996
29-0.09562-0.74070.230891
30-0.217551-1.68510.048578
31-0.104966-0.81310.209698
32-0.057769-0.44750.328071
33-0.209774-1.62490.054713
340.0186290.14430.442873
350.0959550.74330.230112
36-0.011427-0.08850.464881
370.18911.46480.074103
380.1199080.92880.178355
390.0885810.68610.247632
400.2325431.80130.038343
410.0663960.51430.304465
420.0741820.57460.283852
430.145021.12330.132888
440.0680930.52740.299916
450.0396150.30690.380007
460.0429220.33250.370346
47-0.032757-0.25370.400284
48-0.031866-0.24680.402941
49-0.041099-0.31840.375662
50-0.093815-0.72670.235121
51-0.057882-0.44840.327756
52-0.048848-0.37840.353243
53-0.062099-0.4810.316128
54-0.04864-0.37680.353839
55-0.045442-0.3520.363039
56-0.026528-0.20550.418945
57-0.010165-0.07870.468752
58-0.003601-0.02790.48892
590.0002220.00170.499318
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2664312.06380.021687
20.3007422.32950.011607
30.3835242.97080.002134
4-0.108485-0.84030.202032
5-0.173256-1.3420.09232
6-0.006563-0.05080.479814
7-0.197164-1.52720.06598
80.0528440.40930.34188
90.0357510.27690.391393
10-0.139951-1.08410.141338
11-0.117233-0.90810.183734
12-0.16523-1.27990.102759
130.0789610.61160.271546
140.2177391.68660.048437
150.0329210.2550.399797
16-0.097013-0.75150.227657
170.0523390.40540.343308
180.0686510.53180.298425
19-0.034647-0.26840.394665
20-0.20189-1.56380.061558
210.0752270.58270.281137
22-0.251844-1.95080.027879
230.0187260.14510.442578
24-0.194417-1.50590.068663
25-0.111096-0.86050.196457
260.112180.86890.19417
27-0.06658-0.51570.303971
280.0873790.67680.250555
290.0003680.00280.498868
30-0.053992-0.41820.33864
31-0.016576-0.12840.449131
32-0.057988-0.44920.327461
33-0.021373-0.16560.434531
34-0.007441-0.05760.477116
350.0915520.70920.240486
360.0290410.22490.411392
370.0019760.01530.493921
38-0.067313-0.52140.302001
39-0.00705-0.05460.478315
400.0037480.0290.488468
410.0613910.47550.318068
42-0.042615-0.33010.37124
430.0065290.05060.479918
44-0.029084-0.22530.411261
45-0.015872-0.12290.451281
46-0.040068-0.31040.37868
470.0037610.02910.488429
48-0.007244-0.05610.477721
49-0.121706-0.94270.1748
500.0355960.27570.391852
510.0302980.23470.407625
52-0.029538-0.22880.409902
53-0.055467-0.42960.334497
54-0.095576-0.74030.230993
55-0.011919-0.09230.463373
560.0288640.22360.411923
570.0013620.01060.495808
58-0.081056-0.62790.26624
590.0795290.6160.270102
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.266431 & 2.0638 & 0.021687 \tabularnewline
2 & 0.300742 & 2.3295 & 0.011607 \tabularnewline
3 & 0.383524 & 2.9708 & 0.002134 \tabularnewline
4 & -0.108485 & -0.8403 & 0.202032 \tabularnewline
5 & -0.173256 & -1.342 & 0.09232 \tabularnewline
6 & -0.006563 & -0.0508 & 0.479814 \tabularnewline
7 & -0.197164 & -1.5272 & 0.06598 \tabularnewline
8 & 0.052844 & 0.4093 & 0.34188 \tabularnewline
9 & 0.035751 & 0.2769 & 0.391393 \tabularnewline
10 & -0.139951 & -1.0841 & 0.141338 \tabularnewline
11 & -0.117233 & -0.9081 & 0.183734 \tabularnewline
12 & -0.16523 & -1.2799 & 0.102759 \tabularnewline
13 & 0.078961 & 0.6116 & 0.271546 \tabularnewline
14 & 0.217739 & 1.6866 & 0.048437 \tabularnewline
15 & 0.032921 & 0.255 & 0.399797 \tabularnewline
16 & -0.097013 & -0.7515 & 0.227657 \tabularnewline
17 & 0.052339 & 0.4054 & 0.343308 \tabularnewline
18 & 0.068651 & 0.5318 & 0.298425 \tabularnewline
19 & -0.034647 & -0.2684 & 0.394665 \tabularnewline
20 & -0.20189 & -1.5638 & 0.061558 \tabularnewline
21 & 0.075227 & 0.5827 & 0.281137 \tabularnewline
22 & -0.251844 & -1.9508 & 0.027879 \tabularnewline
23 & 0.018726 & 0.1451 & 0.442578 \tabularnewline
24 & -0.194417 & -1.5059 & 0.068663 \tabularnewline
25 & -0.111096 & -0.8605 & 0.196457 \tabularnewline
26 & 0.11218 & 0.8689 & 0.19417 \tabularnewline
27 & -0.06658 & -0.5157 & 0.303971 \tabularnewline
28 & 0.087379 & 0.6768 & 0.250555 \tabularnewline
29 & 0.000368 & 0.0028 & 0.498868 \tabularnewline
30 & -0.053992 & -0.4182 & 0.33864 \tabularnewline
31 & -0.016576 & -0.1284 & 0.449131 \tabularnewline
32 & -0.057988 & -0.4492 & 0.327461 \tabularnewline
33 & -0.021373 & -0.1656 & 0.434531 \tabularnewline
34 & -0.007441 & -0.0576 & 0.477116 \tabularnewline
35 & 0.091552 & 0.7092 & 0.240486 \tabularnewline
36 & 0.029041 & 0.2249 & 0.411392 \tabularnewline
37 & 0.001976 & 0.0153 & 0.493921 \tabularnewline
38 & -0.067313 & -0.5214 & 0.302001 \tabularnewline
39 & -0.00705 & -0.0546 & 0.478315 \tabularnewline
40 & 0.003748 & 0.029 & 0.488468 \tabularnewline
41 & 0.061391 & 0.4755 & 0.318068 \tabularnewline
42 & -0.042615 & -0.3301 & 0.37124 \tabularnewline
43 & 0.006529 & 0.0506 & 0.479918 \tabularnewline
44 & -0.029084 & -0.2253 & 0.411261 \tabularnewline
45 & -0.015872 & -0.1229 & 0.451281 \tabularnewline
46 & -0.040068 & -0.3104 & 0.37868 \tabularnewline
47 & 0.003761 & 0.0291 & 0.488429 \tabularnewline
48 & -0.007244 & -0.0561 & 0.477721 \tabularnewline
49 & -0.121706 & -0.9427 & 0.1748 \tabularnewline
50 & 0.035596 & 0.2757 & 0.391852 \tabularnewline
51 & 0.030298 & 0.2347 & 0.407625 \tabularnewline
52 & -0.029538 & -0.2288 & 0.409902 \tabularnewline
53 & -0.055467 & -0.4296 & 0.334497 \tabularnewline
54 & -0.095576 & -0.7403 & 0.230993 \tabularnewline
55 & -0.011919 & -0.0923 & 0.463373 \tabularnewline
56 & 0.028864 & 0.2236 & 0.411923 \tabularnewline
57 & 0.001362 & 0.0106 & 0.495808 \tabularnewline
58 & -0.081056 & -0.6279 & 0.26624 \tabularnewline
59 & 0.079529 & 0.616 & 0.270102 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71222&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]0.266431[/C][C]2.0638[/C][C]0.021687[/C][/ROW]
[ROW][C]2[/C][C]0.300742[/C][C]2.3295[/C][C]0.011607[/C][/ROW]
[ROW][C]3[/C][C]0.383524[/C][C]2.9708[/C][C]0.002134[/C][/ROW]
[ROW][C]4[/C][C]-0.108485[/C][C]-0.8403[/C][C]0.202032[/C][/ROW]
[ROW][C]5[/C][C]-0.173256[/C][C]-1.342[/C][C]0.09232[/C][/ROW]
[ROW][C]6[/C][C]-0.006563[/C][C]-0.0508[/C][C]0.479814[/C][/ROW]
[ROW][C]7[/C][C]-0.197164[/C][C]-1.5272[/C][C]0.06598[/C][/ROW]
[ROW][C]8[/C][C]0.052844[/C][C]0.4093[/C][C]0.34188[/C][/ROW]
[ROW][C]9[/C][C]0.035751[/C][C]0.2769[/C][C]0.391393[/C][/ROW]
[ROW][C]10[/C][C]-0.139951[/C][C]-1.0841[/C][C]0.141338[/C][/ROW]
[ROW][C]11[/C][C]-0.117233[/C][C]-0.9081[/C][C]0.183734[/C][/ROW]
[ROW][C]12[/C][C]-0.16523[/C][C]-1.2799[/C][C]0.102759[/C][/ROW]
[ROW][C]13[/C][C]0.078961[/C][C]0.6116[/C][C]0.271546[/C][/ROW]
[ROW][C]14[/C][C]0.217739[/C][C]1.6866[/C][C]0.048437[/C][/ROW]
[ROW][C]15[/C][C]0.032921[/C][C]0.255[/C][C]0.399797[/C][/ROW]
[ROW][C]16[/C][C]-0.097013[/C][C]-0.7515[/C][C]0.227657[/C][/ROW]
[ROW][C]17[/C][C]0.052339[/C][C]0.4054[/C][C]0.343308[/C][/ROW]
[ROW][C]18[/C][C]0.068651[/C][C]0.5318[/C][C]0.298425[/C][/ROW]
[ROW][C]19[/C][C]-0.034647[/C][C]-0.2684[/C][C]0.394665[/C][/ROW]
[ROW][C]20[/C][C]-0.20189[/C][C]-1.5638[/C][C]0.061558[/C][/ROW]
[ROW][C]21[/C][C]0.075227[/C][C]0.5827[/C][C]0.281137[/C][/ROW]
[ROW][C]22[/C][C]-0.251844[/C][C]-1.9508[/C][C]0.027879[/C][/ROW]
[ROW][C]23[/C][C]0.018726[/C][C]0.1451[/C][C]0.442578[/C][/ROW]
[ROW][C]24[/C][C]-0.194417[/C][C]-1.5059[/C][C]0.068663[/C][/ROW]
[ROW][C]25[/C][C]-0.111096[/C][C]-0.8605[/C][C]0.196457[/C][/ROW]
[ROW][C]26[/C][C]0.11218[/C][C]0.8689[/C][C]0.19417[/C][/ROW]
[ROW][C]27[/C][C]-0.06658[/C][C]-0.5157[/C][C]0.303971[/C][/ROW]
[ROW][C]28[/C][C]0.087379[/C][C]0.6768[/C][C]0.250555[/C][/ROW]
[ROW][C]29[/C][C]0.000368[/C][C]0.0028[/C][C]0.498868[/C][/ROW]
[ROW][C]30[/C][C]-0.053992[/C][C]-0.4182[/C][C]0.33864[/C][/ROW]
[ROW][C]31[/C][C]-0.016576[/C][C]-0.1284[/C][C]0.449131[/C][/ROW]
[ROW][C]32[/C][C]-0.057988[/C][C]-0.4492[/C][C]0.327461[/C][/ROW]
[ROW][C]33[/C][C]-0.021373[/C][C]-0.1656[/C][C]0.434531[/C][/ROW]
[ROW][C]34[/C][C]-0.007441[/C][C]-0.0576[/C][C]0.477116[/C][/ROW]
[ROW][C]35[/C][C]0.091552[/C][C]0.7092[/C][C]0.240486[/C][/ROW]
[ROW][C]36[/C][C]0.029041[/C][C]0.2249[/C][C]0.411392[/C][/ROW]
[ROW][C]37[/C][C]0.001976[/C][C]0.0153[/C][C]0.493921[/C][/ROW]
[ROW][C]38[/C][C]-0.067313[/C][C]-0.5214[/C][C]0.302001[/C][/ROW]
[ROW][C]39[/C][C]-0.00705[/C][C]-0.0546[/C][C]0.478315[/C][/ROW]
[ROW][C]40[/C][C]0.003748[/C][C]0.029[/C][C]0.488468[/C][/ROW]
[ROW][C]41[/C][C]0.061391[/C][C]0.4755[/C][C]0.318068[/C][/ROW]
[ROW][C]42[/C][C]-0.042615[/C][C]-0.3301[/C][C]0.37124[/C][/ROW]
[ROW][C]43[/C][C]0.006529[/C][C]0.0506[/C][C]0.479918[/C][/ROW]
[ROW][C]44[/C][C]-0.029084[/C][C]-0.2253[/C][C]0.411261[/C][/ROW]
[ROW][C]45[/C][C]-0.015872[/C][C]-0.1229[/C][C]0.451281[/C][/ROW]
[ROW][C]46[/C][C]-0.040068[/C][C]-0.3104[/C][C]0.37868[/C][/ROW]
[ROW][C]47[/C][C]0.003761[/C][C]0.0291[/C][C]0.488429[/C][/ROW]
[ROW][C]48[/C][C]-0.007244[/C][C]-0.0561[/C][C]0.477721[/C][/ROW]
[ROW][C]49[/C][C]-0.121706[/C][C]-0.9427[/C][C]0.1748[/C][/ROW]
[ROW][C]50[/C][C]0.035596[/C][C]0.2757[/C][C]0.391852[/C][/ROW]
[ROW][C]51[/C][C]0.030298[/C][C]0.2347[/C][C]0.407625[/C][/ROW]
[ROW][C]52[/C][C]-0.029538[/C][C]-0.2288[/C][C]0.409902[/C][/ROW]
[ROW][C]53[/C][C]-0.055467[/C][C]-0.4296[/C][C]0.334497[/C][/ROW]
[ROW][C]54[/C][C]-0.095576[/C][C]-0.7403[/C][C]0.230993[/C][/ROW]
[ROW][C]55[/C][C]-0.011919[/C][C]-0.0923[/C][C]0.463373[/C][/ROW]
[ROW][C]56[/C][C]0.028864[/C][C]0.2236[/C][C]0.411923[/C][/ROW]
[ROW][C]57[/C][C]0.001362[/C][C]0.0106[/C][C]0.495808[/C][/ROW]
[ROW][C]58[/C][C]-0.081056[/C][C]-0.6279[/C][C]0.26624[/C][/ROW]
[ROW][C]59[/C][C]0.079529[/C][C]0.616[/C][C]0.270102[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71222&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71222&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
10.2664312.06380.021687
20.3007422.32950.011607
30.3835242.97080.002134
4-0.108485-0.84030.202032
5-0.173256-1.3420.09232
6-0.006563-0.05080.479814
7-0.197164-1.52720.06598
80.0528440.40930.34188
90.0357510.27690.391393
10-0.139951-1.08410.141338
11-0.117233-0.90810.183734
12-0.16523-1.27990.102759
130.0789610.61160.271546
140.2177391.68660.048437
150.0329210.2550.399797
16-0.097013-0.75150.227657
170.0523390.40540.343308
180.0686510.53180.298425
19-0.034647-0.26840.394665
20-0.20189-1.56380.061558
210.0752270.58270.281137
22-0.251844-1.95080.027879
230.0187260.14510.442578
24-0.194417-1.50590.068663
25-0.111096-0.86050.196457
260.112180.86890.19417
27-0.06658-0.51570.303971
280.0873790.67680.250555
290.0003680.00280.498868
30-0.053992-0.41820.33864
31-0.016576-0.12840.449131
32-0.057988-0.44920.327461
33-0.021373-0.16560.434531
34-0.007441-0.05760.477116
350.0915520.70920.240486
360.0290410.22490.411392
370.0019760.01530.493921
38-0.067313-0.52140.302001
39-0.00705-0.05460.478315
400.0037480.0290.488468
410.0613910.47550.318068
42-0.042615-0.33010.37124
430.0065290.05060.479918
44-0.029084-0.22530.411261
45-0.015872-0.12290.451281
46-0.040068-0.31040.37868
470.0037610.02910.488429
48-0.007244-0.05610.477721
49-0.121706-0.94270.1748
500.0355960.27570.391852
510.0302980.23470.407625
52-0.029538-0.22880.409902
53-0.055467-0.42960.334497
54-0.095576-0.74030.230993
55-0.011919-0.09230.463373
560.0288640.22360.411923
570.0013620.01060.495808
58-0.081056-0.62790.26624
590.0795290.6160.270102
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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')