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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, 15 Dec 2010 16:41:13 +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/15/t12924311510gdynr2tejy1rme.htm/, Retrieved Wed, 01 May 2024 13:26:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110551, Retrieved Wed, 01 May 2024 13:26:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
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] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-    D                [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-17 16:51:16] [7773f496f69461f4a67891f0ef752622]
- R PD                    [(Partial) Autocorrelation Function] [autocorrelatie] [2010-12-15 16:41:13] [c1f1b5e209adb4577289f490325e36f2] [Current]
-   P                       [(Partial) Autocorrelation Function] [autocorrelatie d=...] [2010-12-17 15:00:38] [717f3d787904f94c39256c5c1fc72d4c]
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Dataseries X:
1.3031
1.3241
1.2961
1.2865
1.2305
1.2101
1.2125
1.2350
1.2014
1.1992
1.1791
1.1832
1.2159
1.1922
1.2114
1.2614
1.2812
1.2786
1.2772
1.2815
1.2679
1.2765
1.3247
1.3191
1.3029
1.3234
1.3354
1.3651
1.3453
1.3534
1.3706
1.3638
1.4268
1.4485
1.4635
1.4587
1.4876
1.5189
1.5783
1.5633
1.5554
1.5757
1.5593
1.4660
1.4065
1.2759
1.2705
1.3954
1.2793
1.2694
1.3282
1.3230
1.4135
1.4042
1.4253
1.4322
1.4632
1.4713
1.5016
1.4318




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110551&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110551&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110551&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1949271.33640.093934
2-0.068698-0.4710.319921
30.0129840.0890.464726
4-0.051592-0.35370.362573
50.178371.22280.113742
60.040650.27870.390855
7-0.255549-1.7520.043152
8-0.153646-1.05330.148784
9-0.097456-0.66810.25366
10-0.003858-0.02640.489506
110.0440660.30210.381954
12-0.431824-2.96040.002401
13-0.250996-1.72070.045938
140.0995570.68250.249127
150.1601831.09820.138865
160.1018250.69810.244283
170.0732780.50240.308877
188e-040.00550.497823
19-0.003757-0.02580.489781
200.1147810.78690.217646
210.0107120.07340.470884
220.0379120.25990.398034
23-0.14887-1.02060.156334
240.0138010.09460.46251
250.1218560.83540.203858
26-0.026911-0.18450.42721
27-0.111496-0.76440.224231
28-0.151354-1.03760.152375
29-0.133726-0.91680.18197
30-0.02834-0.19430.423393
310.0386950.26530.395978
320.0453330.31080.378667
33-0.026007-0.17830.42963
34-0.090871-0.6230.268154
350.1272790.87260.193664
360.0642670.44060.330764
37-0.040311-0.27640.391743
380.0078340.05370.478698
39-0.00233-0.0160.493662
400.0976260.66930.253294
410.0902050.61840.269645
420.0300660.20610.418792
43-0.049435-0.33890.368094
44-0.075243-0.51580.304192
45-0.048095-0.32970.371537
460.0433570.29720.383796
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.194927 & 1.3364 & 0.093934 \tabularnewline
2 & -0.068698 & -0.471 & 0.319921 \tabularnewline
3 & 0.012984 & 0.089 & 0.464726 \tabularnewline
4 & -0.051592 & -0.3537 & 0.362573 \tabularnewline
5 & 0.17837 & 1.2228 & 0.113742 \tabularnewline
6 & 0.04065 & 0.2787 & 0.390855 \tabularnewline
7 & -0.255549 & -1.752 & 0.043152 \tabularnewline
8 & -0.153646 & -1.0533 & 0.148784 \tabularnewline
9 & -0.097456 & -0.6681 & 0.25366 \tabularnewline
10 & -0.003858 & -0.0264 & 0.489506 \tabularnewline
11 & 0.044066 & 0.3021 & 0.381954 \tabularnewline
12 & -0.431824 & -2.9604 & 0.002401 \tabularnewline
13 & -0.250996 & -1.7207 & 0.045938 \tabularnewline
14 & 0.099557 & 0.6825 & 0.249127 \tabularnewline
15 & 0.160183 & 1.0982 & 0.138865 \tabularnewline
16 & 0.101825 & 0.6981 & 0.244283 \tabularnewline
17 & 0.073278 & 0.5024 & 0.308877 \tabularnewline
18 & 8e-04 & 0.0055 & 0.497823 \tabularnewline
19 & -0.003757 & -0.0258 & 0.489781 \tabularnewline
20 & 0.114781 & 0.7869 & 0.217646 \tabularnewline
21 & 0.010712 & 0.0734 & 0.470884 \tabularnewline
22 & 0.037912 & 0.2599 & 0.398034 \tabularnewline
23 & -0.14887 & -1.0206 & 0.156334 \tabularnewline
24 & 0.013801 & 0.0946 & 0.46251 \tabularnewline
25 & 0.121856 & 0.8354 & 0.203858 \tabularnewline
26 & -0.026911 & -0.1845 & 0.42721 \tabularnewline
27 & -0.111496 & -0.7644 & 0.224231 \tabularnewline
28 & -0.151354 & -1.0376 & 0.152375 \tabularnewline
29 & -0.133726 & -0.9168 & 0.18197 \tabularnewline
30 & -0.02834 & -0.1943 & 0.423393 \tabularnewline
31 & 0.038695 & 0.2653 & 0.395978 \tabularnewline
32 & 0.045333 & 0.3108 & 0.378667 \tabularnewline
33 & -0.026007 & -0.1783 & 0.42963 \tabularnewline
34 & -0.090871 & -0.623 & 0.268154 \tabularnewline
35 & 0.127279 & 0.8726 & 0.193664 \tabularnewline
36 & 0.064267 & 0.4406 & 0.330764 \tabularnewline
37 & -0.040311 & -0.2764 & 0.391743 \tabularnewline
38 & 0.007834 & 0.0537 & 0.478698 \tabularnewline
39 & -0.00233 & -0.016 & 0.493662 \tabularnewline
40 & 0.097626 & 0.6693 & 0.253294 \tabularnewline
41 & 0.090205 & 0.6184 & 0.269645 \tabularnewline
42 & 0.030066 & 0.2061 & 0.418792 \tabularnewline
43 & -0.049435 & -0.3389 & 0.368094 \tabularnewline
44 & -0.075243 & -0.5158 & 0.304192 \tabularnewline
45 & -0.048095 & -0.3297 & 0.371537 \tabularnewline
46 & 0.043357 & 0.2972 & 0.383796 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110551&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]0.194927[/C][C]1.3364[/C][C]0.093934[/C][/ROW]
[ROW][C]2[/C][C]-0.068698[/C][C]-0.471[/C][C]0.319921[/C][/ROW]
[ROW][C]3[/C][C]0.012984[/C][C]0.089[/C][C]0.464726[/C][/ROW]
[ROW][C]4[/C][C]-0.051592[/C][C]-0.3537[/C][C]0.362573[/C][/ROW]
[ROW][C]5[/C][C]0.17837[/C][C]1.2228[/C][C]0.113742[/C][/ROW]
[ROW][C]6[/C][C]0.04065[/C][C]0.2787[/C][C]0.390855[/C][/ROW]
[ROW][C]7[/C][C]-0.255549[/C][C]-1.752[/C][C]0.043152[/C][/ROW]
[ROW][C]8[/C][C]-0.153646[/C][C]-1.0533[/C][C]0.148784[/C][/ROW]
[ROW][C]9[/C][C]-0.097456[/C][C]-0.6681[/C][C]0.25366[/C][/ROW]
[ROW][C]10[/C][C]-0.003858[/C][C]-0.0264[/C][C]0.489506[/C][/ROW]
[ROW][C]11[/C][C]0.044066[/C][C]0.3021[/C][C]0.381954[/C][/ROW]
[ROW][C]12[/C][C]-0.431824[/C][C]-2.9604[/C][C]0.002401[/C][/ROW]
[ROW][C]13[/C][C]-0.250996[/C][C]-1.7207[/C][C]0.045938[/C][/ROW]
[ROW][C]14[/C][C]0.099557[/C][C]0.6825[/C][C]0.249127[/C][/ROW]
[ROW][C]15[/C][C]0.160183[/C][C]1.0982[/C][C]0.138865[/C][/ROW]
[ROW][C]16[/C][C]0.101825[/C][C]0.6981[/C][C]0.244283[/C][/ROW]
[ROW][C]17[/C][C]0.073278[/C][C]0.5024[/C][C]0.308877[/C][/ROW]
[ROW][C]18[/C][C]8e-04[/C][C]0.0055[/C][C]0.497823[/C][/ROW]
[ROW][C]19[/C][C]-0.003757[/C][C]-0.0258[/C][C]0.489781[/C][/ROW]
[ROW][C]20[/C][C]0.114781[/C][C]0.7869[/C][C]0.217646[/C][/ROW]
[ROW][C]21[/C][C]0.010712[/C][C]0.0734[/C][C]0.470884[/C][/ROW]
[ROW][C]22[/C][C]0.037912[/C][C]0.2599[/C][C]0.398034[/C][/ROW]
[ROW][C]23[/C][C]-0.14887[/C][C]-1.0206[/C][C]0.156334[/C][/ROW]
[ROW][C]24[/C][C]0.013801[/C][C]0.0946[/C][C]0.46251[/C][/ROW]
[ROW][C]25[/C][C]0.121856[/C][C]0.8354[/C][C]0.203858[/C][/ROW]
[ROW][C]26[/C][C]-0.026911[/C][C]-0.1845[/C][C]0.42721[/C][/ROW]
[ROW][C]27[/C][C]-0.111496[/C][C]-0.7644[/C][C]0.224231[/C][/ROW]
[ROW][C]28[/C][C]-0.151354[/C][C]-1.0376[/C][C]0.152375[/C][/ROW]
[ROW][C]29[/C][C]-0.133726[/C][C]-0.9168[/C][C]0.18197[/C][/ROW]
[ROW][C]30[/C][C]-0.02834[/C][C]-0.1943[/C][C]0.423393[/C][/ROW]
[ROW][C]31[/C][C]0.038695[/C][C]0.2653[/C][C]0.395978[/C][/ROW]
[ROW][C]32[/C][C]0.045333[/C][C]0.3108[/C][C]0.378667[/C][/ROW]
[ROW][C]33[/C][C]-0.026007[/C][C]-0.1783[/C][C]0.42963[/C][/ROW]
[ROW][C]34[/C][C]-0.090871[/C][C]-0.623[/C][C]0.268154[/C][/ROW]
[ROW][C]35[/C][C]0.127279[/C][C]0.8726[/C][C]0.193664[/C][/ROW]
[ROW][C]36[/C][C]0.064267[/C][C]0.4406[/C][C]0.330764[/C][/ROW]
[ROW][C]37[/C][C]-0.040311[/C][C]-0.2764[/C][C]0.391743[/C][/ROW]
[ROW][C]38[/C][C]0.007834[/C][C]0.0537[/C][C]0.478698[/C][/ROW]
[ROW][C]39[/C][C]-0.00233[/C][C]-0.016[/C][C]0.493662[/C][/ROW]
[ROW][C]40[/C][C]0.097626[/C][C]0.6693[/C][C]0.253294[/C][/ROW]
[ROW][C]41[/C][C]0.090205[/C][C]0.6184[/C][C]0.269645[/C][/ROW]
[ROW][C]42[/C][C]0.030066[/C][C]0.2061[/C][C]0.418792[/C][/ROW]
[ROW][C]43[/C][C]-0.049435[/C][C]-0.3389[/C][C]0.368094[/C][/ROW]
[ROW][C]44[/C][C]-0.075243[/C][C]-0.5158[/C][C]0.304192[/C][/ROW]
[ROW][C]45[/C][C]-0.048095[/C][C]-0.3297[/C][C]0.371537[/C][/ROW]
[ROW][C]46[/C][C]0.043357[/C][C]0.2972[/C][C]0.383796[/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]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/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=110551&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110551&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
10.1949271.33640.093934
2-0.068698-0.4710.319921
30.0129840.0890.464726
4-0.051592-0.35370.362573
50.178371.22280.113742
60.040650.27870.390855
7-0.255549-1.7520.043152
8-0.153646-1.05330.148784
9-0.097456-0.66810.25366
10-0.003858-0.02640.489506
110.0440660.30210.381954
12-0.431824-2.96040.002401
13-0.250996-1.72070.045938
140.0995570.68250.249127
150.1601831.09820.138865
160.1018250.69810.244283
170.0732780.50240.308877
188e-040.00550.497823
19-0.003757-0.02580.489781
200.1147810.78690.217646
210.0107120.07340.470884
220.0379120.25990.398034
23-0.14887-1.02060.156334
240.0138010.09460.46251
250.1218560.83540.203858
26-0.026911-0.18450.42721
27-0.111496-0.76440.224231
28-0.151354-1.03760.152375
29-0.133726-0.91680.18197
30-0.02834-0.19430.423393
310.0386950.26530.395978
320.0453330.31080.378667
33-0.026007-0.17830.42963
34-0.090871-0.6230.268154
350.1272790.87260.193664
360.0642670.44060.330764
37-0.040311-0.27640.391743
380.0078340.05370.478698
39-0.00233-0.0160.493662
400.0976260.66930.253294
410.0902050.61840.269645
420.0300660.20610.418792
43-0.049435-0.33890.368094
44-0.075243-0.51580.304192
45-0.048095-0.32970.371537
460.0433570.29720.383796
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1949271.33640.093934
2-0.110908-0.76040.225421
30.0520740.3570.361345
4-0.077062-0.52830.299885
50.2245641.53950.06519
6-0.071821-0.49240.312372
7-0.225135-1.54340.064714
8-0.078375-0.53730.296793
9-0.069443-0.47610.318113
100.002050.01410.494423
11-0.001835-0.01260.495007
12-0.432164-2.96280.002386
13-0.055671-0.38170.352217
140.0902230.61850.269604
150.1469441.00740.159451
16-0.088763-0.60850.272884
170.1936781.32780.09533
180.0501770.3440.366191
19-0.217174-1.48890.071601
20-0.058696-0.40240.344608
21-0.080594-0.55250.291603
220.1179820.80880.211341
23-0.202139-1.38580.086175
240.032040.21970.413545
25-0.019259-0.1320.44776
260.0544310.37320.355352
27-0.026206-0.17970.429096
28-0.169726-1.16360.125233
290.0184910.12680.449833
30-0.008719-0.05980.476293
31-0.106293-0.72870.234897
32-0.004448-0.03050.487901
33-0.087049-0.59680.27676
340.0479440.32870.371926
35-0.054065-0.37070.356281
36-0.02426-0.16630.434309
37-0.067267-0.46120.323406
380.0679020.46550.321857
39-0.031177-0.21370.415839
40-0.081433-0.55830.289653
410.0035340.02420.490386
42-0.012395-0.0850.46632
43-0.037675-0.25830.398657
44-0.052459-0.35960.360364
45-0.016683-0.11440.454714
46-0.032967-0.2260.411088
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.194927 & 1.3364 & 0.093934 \tabularnewline
2 & -0.110908 & -0.7604 & 0.225421 \tabularnewline
3 & 0.052074 & 0.357 & 0.361345 \tabularnewline
4 & -0.077062 & -0.5283 & 0.299885 \tabularnewline
5 & 0.224564 & 1.5395 & 0.06519 \tabularnewline
6 & -0.071821 & -0.4924 & 0.312372 \tabularnewline
7 & -0.225135 & -1.5434 & 0.064714 \tabularnewline
8 & -0.078375 & -0.5373 & 0.296793 \tabularnewline
9 & -0.069443 & -0.4761 & 0.318113 \tabularnewline
10 & 0.00205 & 0.0141 & 0.494423 \tabularnewline
11 & -0.001835 & -0.0126 & 0.495007 \tabularnewline
12 & -0.432164 & -2.9628 & 0.002386 \tabularnewline
13 & -0.055671 & -0.3817 & 0.352217 \tabularnewline
14 & 0.090223 & 0.6185 & 0.269604 \tabularnewline
15 & 0.146944 & 1.0074 & 0.159451 \tabularnewline
16 & -0.088763 & -0.6085 & 0.272884 \tabularnewline
17 & 0.193678 & 1.3278 & 0.09533 \tabularnewline
18 & 0.050177 & 0.344 & 0.366191 \tabularnewline
19 & -0.217174 & -1.4889 & 0.071601 \tabularnewline
20 & -0.058696 & -0.4024 & 0.344608 \tabularnewline
21 & -0.080594 & -0.5525 & 0.291603 \tabularnewline
22 & 0.117982 & 0.8088 & 0.211341 \tabularnewline
23 & -0.202139 & -1.3858 & 0.086175 \tabularnewline
24 & 0.03204 & 0.2197 & 0.413545 \tabularnewline
25 & -0.019259 & -0.132 & 0.44776 \tabularnewline
26 & 0.054431 & 0.3732 & 0.355352 \tabularnewline
27 & -0.026206 & -0.1797 & 0.429096 \tabularnewline
28 & -0.169726 & -1.1636 & 0.125233 \tabularnewline
29 & 0.018491 & 0.1268 & 0.449833 \tabularnewline
30 & -0.008719 & -0.0598 & 0.476293 \tabularnewline
31 & -0.106293 & -0.7287 & 0.234897 \tabularnewline
32 & -0.004448 & -0.0305 & 0.487901 \tabularnewline
33 & -0.087049 & -0.5968 & 0.27676 \tabularnewline
34 & 0.047944 & 0.3287 & 0.371926 \tabularnewline
35 & -0.054065 & -0.3707 & 0.356281 \tabularnewline
36 & -0.02426 & -0.1663 & 0.434309 \tabularnewline
37 & -0.067267 & -0.4612 & 0.323406 \tabularnewline
38 & 0.067902 & 0.4655 & 0.321857 \tabularnewline
39 & -0.031177 & -0.2137 & 0.415839 \tabularnewline
40 & -0.081433 & -0.5583 & 0.289653 \tabularnewline
41 & 0.003534 & 0.0242 & 0.490386 \tabularnewline
42 & -0.012395 & -0.085 & 0.46632 \tabularnewline
43 & -0.037675 & -0.2583 & 0.398657 \tabularnewline
44 & -0.052459 & -0.3596 & 0.360364 \tabularnewline
45 & -0.016683 & -0.1144 & 0.454714 \tabularnewline
46 & -0.032967 & -0.226 & 0.411088 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110551&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]0.194927[/C][C]1.3364[/C][C]0.093934[/C][/ROW]
[ROW][C]2[/C][C]-0.110908[/C][C]-0.7604[/C][C]0.225421[/C][/ROW]
[ROW][C]3[/C][C]0.052074[/C][C]0.357[/C][C]0.361345[/C][/ROW]
[ROW][C]4[/C][C]-0.077062[/C][C]-0.5283[/C][C]0.299885[/C][/ROW]
[ROW][C]5[/C][C]0.224564[/C][C]1.5395[/C][C]0.06519[/C][/ROW]
[ROW][C]6[/C][C]-0.071821[/C][C]-0.4924[/C][C]0.312372[/C][/ROW]
[ROW][C]7[/C][C]-0.225135[/C][C]-1.5434[/C][C]0.064714[/C][/ROW]
[ROW][C]8[/C][C]-0.078375[/C][C]-0.5373[/C][C]0.296793[/C][/ROW]
[ROW][C]9[/C][C]-0.069443[/C][C]-0.4761[/C][C]0.318113[/C][/ROW]
[ROW][C]10[/C][C]0.00205[/C][C]0.0141[/C][C]0.494423[/C][/ROW]
[ROW][C]11[/C][C]-0.001835[/C][C]-0.0126[/C][C]0.495007[/C][/ROW]
[ROW][C]12[/C][C]-0.432164[/C][C]-2.9628[/C][C]0.002386[/C][/ROW]
[ROW][C]13[/C][C]-0.055671[/C][C]-0.3817[/C][C]0.352217[/C][/ROW]
[ROW][C]14[/C][C]0.090223[/C][C]0.6185[/C][C]0.269604[/C][/ROW]
[ROW][C]15[/C][C]0.146944[/C][C]1.0074[/C][C]0.159451[/C][/ROW]
[ROW][C]16[/C][C]-0.088763[/C][C]-0.6085[/C][C]0.272884[/C][/ROW]
[ROW][C]17[/C][C]0.193678[/C][C]1.3278[/C][C]0.09533[/C][/ROW]
[ROW][C]18[/C][C]0.050177[/C][C]0.344[/C][C]0.366191[/C][/ROW]
[ROW][C]19[/C][C]-0.217174[/C][C]-1.4889[/C][C]0.071601[/C][/ROW]
[ROW][C]20[/C][C]-0.058696[/C][C]-0.4024[/C][C]0.344608[/C][/ROW]
[ROW][C]21[/C][C]-0.080594[/C][C]-0.5525[/C][C]0.291603[/C][/ROW]
[ROW][C]22[/C][C]0.117982[/C][C]0.8088[/C][C]0.211341[/C][/ROW]
[ROW][C]23[/C][C]-0.202139[/C][C]-1.3858[/C][C]0.086175[/C][/ROW]
[ROW][C]24[/C][C]0.03204[/C][C]0.2197[/C][C]0.413545[/C][/ROW]
[ROW][C]25[/C][C]-0.019259[/C][C]-0.132[/C][C]0.44776[/C][/ROW]
[ROW][C]26[/C][C]0.054431[/C][C]0.3732[/C][C]0.355352[/C][/ROW]
[ROW][C]27[/C][C]-0.026206[/C][C]-0.1797[/C][C]0.429096[/C][/ROW]
[ROW][C]28[/C][C]-0.169726[/C][C]-1.1636[/C][C]0.125233[/C][/ROW]
[ROW][C]29[/C][C]0.018491[/C][C]0.1268[/C][C]0.449833[/C][/ROW]
[ROW][C]30[/C][C]-0.008719[/C][C]-0.0598[/C][C]0.476293[/C][/ROW]
[ROW][C]31[/C][C]-0.106293[/C][C]-0.7287[/C][C]0.234897[/C][/ROW]
[ROW][C]32[/C][C]-0.004448[/C][C]-0.0305[/C][C]0.487901[/C][/ROW]
[ROW][C]33[/C][C]-0.087049[/C][C]-0.5968[/C][C]0.27676[/C][/ROW]
[ROW][C]34[/C][C]0.047944[/C][C]0.3287[/C][C]0.371926[/C][/ROW]
[ROW][C]35[/C][C]-0.054065[/C][C]-0.3707[/C][C]0.356281[/C][/ROW]
[ROW][C]36[/C][C]-0.02426[/C][C]-0.1663[/C][C]0.434309[/C][/ROW]
[ROW][C]37[/C][C]-0.067267[/C][C]-0.4612[/C][C]0.323406[/C][/ROW]
[ROW][C]38[/C][C]0.067902[/C][C]0.4655[/C][C]0.321857[/C][/ROW]
[ROW][C]39[/C][C]-0.031177[/C][C]-0.2137[/C][C]0.415839[/C][/ROW]
[ROW][C]40[/C][C]-0.081433[/C][C]-0.5583[/C][C]0.289653[/C][/ROW]
[ROW][C]41[/C][C]0.003534[/C][C]0.0242[/C][C]0.490386[/C][/ROW]
[ROW][C]42[/C][C]-0.012395[/C][C]-0.085[/C][C]0.46632[/C][/ROW]
[ROW][C]43[/C][C]-0.037675[/C][C]-0.2583[/C][C]0.398657[/C][/ROW]
[ROW][C]44[/C][C]-0.052459[/C][C]-0.3596[/C][C]0.360364[/C][/ROW]
[ROW][C]45[/C][C]-0.016683[/C][C]-0.1144[/C][C]0.454714[/C][/ROW]
[ROW][C]46[/C][C]-0.032967[/C][C]-0.226[/C][C]0.411088[/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]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/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=110551&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110551&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
10.1949271.33640.093934
2-0.110908-0.76040.225421
30.0520740.3570.361345
4-0.077062-0.52830.299885
50.2245641.53950.06519
6-0.071821-0.49240.312372
7-0.225135-1.54340.064714
8-0.078375-0.53730.296793
9-0.069443-0.47610.318113
100.002050.01410.494423
11-0.001835-0.01260.495007
12-0.432164-2.96280.002386
13-0.055671-0.38170.352217
140.0902230.61850.269604
150.1469441.00740.159451
16-0.088763-0.60850.272884
170.1936781.32780.09533
180.0501770.3440.366191
19-0.217174-1.48890.071601
20-0.058696-0.40240.344608
21-0.080594-0.55250.291603
220.1179820.80880.211341
23-0.202139-1.38580.086175
240.032040.21970.413545
25-0.019259-0.1320.44776
260.0544310.37320.355352
27-0.026206-0.17970.429096
28-0.169726-1.16360.125233
290.0184910.12680.449833
30-0.008719-0.05980.476293
31-0.106293-0.72870.234897
32-0.004448-0.03050.487901
33-0.087049-0.59680.27676
340.0479440.32870.371926
35-0.054065-0.37070.356281
36-0.02426-0.16630.434309
37-0.067267-0.46120.323406
380.0679020.46550.321857
39-0.031177-0.21370.415839
40-0.081433-0.55830.289653
410.0035340.02420.490386
42-0.012395-0.0850.46632
43-0.037675-0.25830.398657
44-0.052459-0.35960.360364
45-0.016683-0.11440.454714
46-0.032967-0.2260.411088
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')