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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 computationThu, 06 Sep 2018 14:26:07 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Sep/06/t1536236778hmybluoyuroaxz5.htm/, Retrieved Thu, 02 May 2024 13:23:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315462, Retrieved Thu, 02 May 2024 13:23:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact29
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2018-09-06 12:26:07] [27993148ab1aadc826ce6032b83fbe19] [Current]
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Dataseries X:
97.7
88.9
96.5
89.5
85.4
84.3
83.7
86.2
90.7
95.7
95.6
97
97.2
86.6
88.4
81.4
86.9
84.9
83.7
86.8
88.3
92.5
94.7
94.5
98.7
88.6
95.2
91.3
91.7
89.3
88.7
91.2
88.6
94.6
96
94.3
102
93.4
96.7
93.7
91.6
89.6
92.9
94.1
92
97.5
92.7
100.7
105.9
95.3
99.8
91.3
90.8
87.1
91.4
86.1
87.1
92.6
96.6
105.3
102.4
98.2
98.6
92.6
87.9
84.1
86.7
84.4
86
90.4
92.9
105.8
106
99.1
99.9
88.1
87.8
87.1
85.9
86.5
84.1
92.1
93.3
98.9
103
98.4
100.7
92.3
89
88.9
85.5
90.1
87
97.1
101.5
103
106.1
96.1
94.2
89.1
85.2
86.5
88
88.4
87.9
95.7
94.8
105.2
108.7
96.1
98.3
88.6
90.8
88.1
91.9
98.5
98.6
100.3
98.7
110.7
115.4
105.4
108
94.5
96.5
91
94.1
96.4
93.1
97.5
102.5
105.7
109.1
97.2
100.3
91.3
94.3
89.5
89.3
93.4
91.9
92.9
93.7
100.1
105.5
110.5
89.5
90.4
89.9
84.6
86.2
83.4
82.9
81.8
87.6
94.6
99.6
96.7
99.8
83.8
82.4
86.8
91
85.3
83.6
94
100.3
107.1
100.7
95.5
92.9
79.2
82
79.3
81.5
76
73.1
80.4
82.1
90.5
98.1
89.5
86.5
77
74.7
73.4
72.5
69.3
75.2
83.5
90.5
92.2
110.5
101.8
107.4
95.5
84.5
81.1
86.2
91.5
84.7
92.2
99.2
104.5
113
100.4
101
84.8
86.5
91.7
94.8
95




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315462&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315462&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315462&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 Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.31638-4.46317e-06
2-0.048086-0.67830.249172
3-0.070325-0.99210.161188
4-0.016415-0.23160.408557
50.124841.76110.03988
6-0.086181-1.21570.112764
7-0.001862-0.02630.489536
8-0.037016-0.52220.301067
90.08091.14120.127572
10-0.027552-0.38870.348971
110.1539772.17210.015515
12-0.382006-5.38890
130.0874821.23410.109314
140.0556030.78440.216874
150.0421730.59490.276287
16-0.083114-1.17250.121205
17-0.059099-0.83370.202726
180.1010021.42480.07789
19-0.070525-0.99490.160501
200.0157730.22250.412072
21-0.045597-0.64320.260408
220.1024021.44460.075077
230.0399360.56340.286909
24-0.135618-1.91310.028584
250.0118070.16660.433943
26-0.030198-0.4260.335284
270.0291120.41070.340874
280.1087971.53480.063214
290.0013130.01850.492621
30-0.016555-0.23350.407794
31-0.034803-0.4910.311999
320.0629590.88810.187769
33-0.021211-0.29920.382543
34-0.052696-0.74340.229067
350.0123880.17480.430726
360.0588860.83070.203573
370.0631410.89070.187078
383.1e-054e-040.499824
39-0.196094-2.76630.003102
400.0443050.6250.266343
41-0.006157-0.08690.465438
42-0.083522-1.17820.120057
430.1516242.13890.01683
44-0.067699-0.9550.170365
450.1158871.63480.051838
46-0.053247-0.75110.226727
47-0.011975-0.16890.43301
48-0.033204-0.46840.320007

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.31638 & -4.4631 & 7e-06 \tabularnewline
2 & -0.048086 & -0.6783 & 0.249172 \tabularnewline
3 & -0.070325 & -0.9921 & 0.161188 \tabularnewline
4 & -0.016415 & -0.2316 & 0.408557 \tabularnewline
5 & 0.12484 & 1.7611 & 0.03988 \tabularnewline
6 & -0.086181 & -1.2157 & 0.112764 \tabularnewline
7 & -0.001862 & -0.0263 & 0.489536 \tabularnewline
8 & -0.037016 & -0.5222 & 0.301067 \tabularnewline
9 & 0.0809 & 1.1412 & 0.127572 \tabularnewline
10 & -0.027552 & -0.3887 & 0.348971 \tabularnewline
11 & 0.153977 & 2.1721 & 0.015515 \tabularnewline
12 & -0.382006 & -5.3889 & 0 \tabularnewline
13 & 0.087482 & 1.2341 & 0.109314 \tabularnewline
14 & 0.055603 & 0.7844 & 0.216874 \tabularnewline
15 & 0.042173 & 0.5949 & 0.276287 \tabularnewline
16 & -0.083114 & -1.1725 & 0.121205 \tabularnewline
17 & -0.059099 & -0.8337 & 0.202726 \tabularnewline
18 & 0.101002 & 1.4248 & 0.07789 \tabularnewline
19 & -0.070525 & -0.9949 & 0.160501 \tabularnewline
20 & 0.015773 & 0.2225 & 0.412072 \tabularnewline
21 & -0.045597 & -0.6432 & 0.260408 \tabularnewline
22 & 0.102402 & 1.4446 & 0.075077 \tabularnewline
23 & 0.039936 & 0.5634 & 0.286909 \tabularnewline
24 & -0.135618 & -1.9131 & 0.028584 \tabularnewline
25 & 0.011807 & 0.1666 & 0.433943 \tabularnewline
26 & -0.030198 & -0.426 & 0.335284 \tabularnewline
27 & 0.029112 & 0.4107 & 0.340874 \tabularnewline
28 & 0.108797 & 1.5348 & 0.063214 \tabularnewline
29 & 0.001313 & 0.0185 & 0.492621 \tabularnewline
30 & -0.016555 & -0.2335 & 0.407794 \tabularnewline
31 & -0.034803 & -0.491 & 0.311999 \tabularnewline
32 & 0.062959 & 0.8881 & 0.187769 \tabularnewline
33 & -0.021211 & -0.2992 & 0.382543 \tabularnewline
34 & -0.052696 & -0.7434 & 0.229067 \tabularnewline
35 & 0.012388 & 0.1748 & 0.430726 \tabularnewline
36 & 0.058886 & 0.8307 & 0.203573 \tabularnewline
37 & 0.063141 & 0.8907 & 0.187078 \tabularnewline
38 & 3.1e-05 & 4e-04 & 0.499824 \tabularnewline
39 & -0.196094 & -2.7663 & 0.003102 \tabularnewline
40 & 0.044305 & 0.625 & 0.266343 \tabularnewline
41 & -0.006157 & -0.0869 & 0.465438 \tabularnewline
42 & -0.083522 & -1.1782 & 0.120057 \tabularnewline
43 & 0.151624 & 2.1389 & 0.01683 \tabularnewline
44 & -0.067699 & -0.955 & 0.170365 \tabularnewline
45 & 0.115887 & 1.6348 & 0.051838 \tabularnewline
46 & -0.053247 & -0.7511 & 0.226727 \tabularnewline
47 & -0.011975 & -0.1689 & 0.43301 \tabularnewline
48 & -0.033204 & -0.4684 & 0.320007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315462&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]-0.31638[/C][C]-4.4631[/C][C]7e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.048086[/C][C]-0.6783[/C][C]0.249172[/C][/ROW]
[ROW][C]3[/C][C]-0.070325[/C][C]-0.9921[/C][C]0.161188[/C][/ROW]
[ROW][C]4[/C][C]-0.016415[/C][C]-0.2316[/C][C]0.408557[/C][/ROW]
[ROW][C]5[/C][C]0.12484[/C][C]1.7611[/C][C]0.03988[/C][/ROW]
[ROW][C]6[/C][C]-0.086181[/C][C]-1.2157[/C][C]0.112764[/C][/ROW]
[ROW][C]7[/C][C]-0.001862[/C][C]-0.0263[/C][C]0.489536[/C][/ROW]
[ROW][C]8[/C][C]-0.037016[/C][C]-0.5222[/C][C]0.301067[/C][/ROW]
[ROW][C]9[/C][C]0.0809[/C][C]1.1412[/C][C]0.127572[/C][/ROW]
[ROW][C]10[/C][C]-0.027552[/C][C]-0.3887[/C][C]0.348971[/C][/ROW]
[ROW][C]11[/C][C]0.153977[/C][C]2.1721[/C][C]0.015515[/C][/ROW]
[ROW][C]12[/C][C]-0.382006[/C][C]-5.3889[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.087482[/C][C]1.2341[/C][C]0.109314[/C][/ROW]
[ROW][C]14[/C][C]0.055603[/C][C]0.7844[/C][C]0.216874[/C][/ROW]
[ROW][C]15[/C][C]0.042173[/C][C]0.5949[/C][C]0.276287[/C][/ROW]
[ROW][C]16[/C][C]-0.083114[/C][C]-1.1725[/C][C]0.121205[/C][/ROW]
[ROW][C]17[/C][C]-0.059099[/C][C]-0.8337[/C][C]0.202726[/C][/ROW]
[ROW][C]18[/C][C]0.101002[/C][C]1.4248[/C][C]0.07789[/C][/ROW]
[ROW][C]19[/C][C]-0.070525[/C][C]-0.9949[/C][C]0.160501[/C][/ROW]
[ROW][C]20[/C][C]0.015773[/C][C]0.2225[/C][C]0.412072[/C][/ROW]
[ROW][C]21[/C][C]-0.045597[/C][C]-0.6432[/C][C]0.260408[/C][/ROW]
[ROW][C]22[/C][C]0.102402[/C][C]1.4446[/C][C]0.075077[/C][/ROW]
[ROW][C]23[/C][C]0.039936[/C][C]0.5634[/C][C]0.286909[/C][/ROW]
[ROW][C]24[/C][C]-0.135618[/C][C]-1.9131[/C][C]0.028584[/C][/ROW]
[ROW][C]25[/C][C]0.011807[/C][C]0.1666[/C][C]0.433943[/C][/ROW]
[ROW][C]26[/C][C]-0.030198[/C][C]-0.426[/C][C]0.335284[/C][/ROW]
[ROW][C]27[/C][C]0.029112[/C][C]0.4107[/C][C]0.340874[/C][/ROW]
[ROW][C]28[/C][C]0.108797[/C][C]1.5348[/C][C]0.063214[/C][/ROW]
[ROW][C]29[/C][C]0.001313[/C][C]0.0185[/C][C]0.492621[/C][/ROW]
[ROW][C]30[/C][C]-0.016555[/C][C]-0.2335[/C][C]0.407794[/C][/ROW]
[ROW][C]31[/C][C]-0.034803[/C][C]-0.491[/C][C]0.311999[/C][/ROW]
[ROW][C]32[/C][C]0.062959[/C][C]0.8881[/C][C]0.187769[/C][/ROW]
[ROW][C]33[/C][C]-0.021211[/C][C]-0.2992[/C][C]0.382543[/C][/ROW]
[ROW][C]34[/C][C]-0.052696[/C][C]-0.7434[/C][C]0.229067[/C][/ROW]
[ROW][C]35[/C][C]0.012388[/C][C]0.1748[/C][C]0.430726[/C][/ROW]
[ROW][C]36[/C][C]0.058886[/C][C]0.8307[/C][C]0.203573[/C][/ROW]
[ROW][C]37[/C][C]0.063141[/C][C]0.8907[/C][C]0.187078[/C][/ROW]
[ROW][C]38[/C][C]3.1e-05[/C][C]4e-04[/C][C]0.499824[/C][/ROW]
[ROW][C]39[/C][C]-0.196094[/C][C]-2.7663[/C][C]0.003102[/C][/ROW]
[ROW][C]40[/C][C]0.044305[/C][C]0.625[/C][C]0.266343[/C][/ROW]
[ROW][C]41[/C][C]-0.006157[/C][C]-0.0869[/C][C]0.465438[/C][/ROW]
[ROW][C]42[/C][C]-0.083522[/C][C]-1.1782[/C][C]0.120057[/C][/ROW]
[ROW][C]43[/C][C]0.151624[/C][C]2.1389[/C][C]0.01683[/C][/ROW]
[ROW][C]44[/C][C]-0.067699[/C][C]-0.955[/C][C]0.170365[/C][/ROW]
[ROW][C]45[/C][C]0.115887[/C][C]1.6348[/C][C]0.051838[/C][/ROW]
[ROW][C]46[/C][C]-0.053247[/C][C]-0.7511[/C][C]0.226727[/C][/ROW]
[ROW][C]47[/C][C]-0.011975[/C][C]-0.1689[/C][C]0.43301[/C][/ROW]
[ROW][C]48[/C][C]-0.033204[/C][C]-0.4684[/C][C]0.320007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315462&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315462&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
1-0.31638-4.46317e-06
2-0.048086-0.67830.249172
3-0.070325-0.99210.161188
4-0.016415-0.23160.408557
50.124841.76110.03988
6-0.086181-1.21570.112764
7-0.001862-0.02630.489536
8-0.037016-0.52220.301067
90.08091.14120.127572
10-0.027552-0.38870.348971
110.1539772.17210.015515
12-0.382006-5.38890
130.0874821.23410.109314
140.0556030.78440.216874
150.0421730.59490.276287
16-0.083114-1.17250.121205
17-0.059099-0.83370.202726
180.1010021.42480.07789
19-0.070525-0.99490.160501
200.0157730.22250.412072
21-0.045597-0.64320.260408
220.1024021.44460.075077
230.0399360.56340.286909
24-0.135618-1.91310.028584
250.0118070.16660.433943
26-0.030198-0.4260.335284
270.0291120.41070.340874
280.1087971.53480.063214
290.0013130.01850.492621
30-0.016555-0.23350.407794
31-0.034803-0.4910.311999
320.0629590.88810.187769
33-0.021211-0.29920.382543
34-0.052696-0.74340.229067
350.0123880.17480.430726
360.0588860.83070.203573
370.0631410.89070.187078
383.1e-054e-040.499824
39-0.196094-2.76630.003102
400.0443050.6250.266343
41-0.006157-0.08690.465438
42-0.083522-1.17820.120057
430.1516242.13890.01683
44-0.067699-0.9550.170365
450.1158871.63480.051838
46-0.053247-0.75110.226727
47-0.011975-0.16890.43301
48-0.033204-0.46840.320007







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.31638-4.46317e-06
2-0.164665-2.32290.010598
3-0.160068-2.2580.012514
4-0.123763-1.74590.041187
50.06090.85910.19566
6-0.045837-0.64660.259314
7-0.03574-0.50420.30735
8-0.055855-0.78790.215837
90.0454490.64110.261086
10-0.012111-0.17080.432262
110.1927152.71860.003568
12-0.310616-4.38181e-05
13-0.130331-1.83850.033737
14-0.0549-0.77450.219787
150.0037650.05310.478848
16-0.161002-2.27120.012102
17-0.051743-0.72990.233146
18-0.009455-0.13340.447013
19-0.09647-1.36090.087545
20-0.111273-1.56970.059037
21-0.03557-0.50180.308191
220.0458360.64660.259319
230.1840432.59620.005064
24-0.242334-3.41850.000382
25-0.142234-2.00650.023081
26-0.111847-1.57780.058101
27-0.029442-0.41530.339174
28-0.012645-0.17840.429301
290.0559820.78970.215314
300.0652140.920.179354
31-0.059626-0.84110.200643
32-0.031849-0.44930.326858
33-0.058316-0.82270.205844
34-0.011338-0.15990.436545
350.1520722.14520.016573
36-0.066945-0.94440.173062
370.0096580.13620.445885
380.0476150.67170.251281
39-0.230429-3.25060.000676
40-0.103812-1.46440.072325
41-0.037751-0.53250.29747
42-0.155472-2.19320.014726
43-0.001161-0.01640.493474
440.0246490.34770.364209
450.0986611.39180.082771
460.027450.38720.349499
470.146932.07270.019744
48-0.083517-1.17820.120071

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.31638 & -4.4631 & 7e-06 \tabularnewline
2 & -0.164665 & -2.3229 & 0.010598 \tabularnewline
3 & -0.160068 & -2.258 & 0.012514 \tabularnewline
4 & -0.123763 & -1.7459 & 0.041187 \tabularnewline
5 & 0.0609 & 0.8591 & 0.19566 \tabularnewline
6 & -0.045837 & -0.6466 & 0.259314 \tabularnewline
7 & -0.03574 & -0.5042 & 0.30735 \tabularnewline
8 & -0.055855 & -0.7879 & 0.215837 \tabularnewline
9 & 0.045449 & 0.6411 & 0.261086 \tabularnewline
10 & -0.012111 & -0.1708 & 0.432262 \tabularnewline
11 & 0.192715 & 2.7186 & 0.003568 \tabularnewline
12 & -0.310616 & -4.3818 & 1e-05 \tabularnewline
13 & -0.130331 & -1.8385 & 0.033737 \tabularnewline
14 & -0.0549 & -0.7745 & 0.219787 \tabularnewline
15 & 0.003765 & 0.0531 & 0.478848 \tabularnewline
16 & -0.161002 & -2.2712 & 0.012102 \tabularnewline
17 & -0.051743 & -0.7299 & 0.233146 \tabularnewline
18 & -0.009455 & -0.1334 & 0.447013 \tabularnewline
19 & -0.09647 & -1.3609 & 0.087545 \tabularnewline
20 & -0.111273 & -1.5697 & 0.059037 \tabularnewline
21 & -0.03557 & -0.5018 & 0.308191 \tabularnewline
22 & 0.045836 & 0.6466 & 0.259319 \tabularnewline
23 & 0.184043 & 2.5962 & 0.005064 \tabularnewline
24 & -0.242334 & -3.4185 & 0.000382 \tabularnewline
25 & -0.142234 & -2.0065 & 0.023081 \tabularnewline
26 & -0.111847 & -1.5778 & 0.058101 \tabularnewline
27 & -0.029442 & -0.4153 & 0.339174 \tabularnewline
28 & -0.012645 & -0.1784 & 0.429301 \tabularnewline
29 & 0.055982 & 0.7897 & 0.215314 \tabularnewline
30 & 0.065214 & 0.92 & 0.179354 \tabularnewline
31 & -0.059626 & -0.8411 & 0.200643 \tabularnewline
32 & -0.031849 & -0.4493 & 0.326858 \tabularnewline
33 & -0.058316 & -0.8227 & 0.205844 \tabularnewline
34 & -0.011338 & -0.1599 & 0.436545 \tabularnewline
35 & 0.152072 & 2.1452 & 0.016573 \tabularnewline
36 & -0.066945 & -0.9444 & 0.173062 \tabularnewline
37 & 0.009658 & 0.1362 & 0.445885 \tabularnewline
38 & 0.047615 & 0.6717 & 0.251281 \tabularnewline
39 & -0.230429 & -3.2506 & 0.000676 \tabularnewline
40 & -0.103812 & -1.4644 & 0.072325 \tabularnewline
41 & -0.037751 & -0.5325 & 0.29747 \tabularnewline
42 & -0.155472 & -2.1932 & 0.014726 \tabularnewline
43 & -0.001161 & -0.0164 & 0.493474 \tabularnewline
44 & 0.024649 & 0.3477 & 0.364209 \tabularnewline
45 & 0.098661 & 1.3918 & 0.082771 \tabularnewline
46 & 0.02745 & 0.3872 & 0.349499 \tabularnewline
47 & 0.14693 & 2.0727 & 0.019744 \tabularnewline
48 & -0.083517 & -1.1782 & 0.120071 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315462&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]-0.31638[/C][C]-4.4631[/C][C]7e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.164665[/C][C]-2.3229[/C][C]0.010598[/C][/ROW]
[ROW][C]3[/C][C]-0.160068[/C][C]-2.258[/C][C]0.012514[/C][/ROW]
[ROW][C]4[/C][C]-0.123763[/C][C]-1.7459[/C][C]0.041187[/C][/ROW]
[ROW][C]5[/C][C]0.0609[/C][C]0.8591[/C][C]0.19566[/C][/ROW]
[ROW][C]6[/C][C]-0.045837[/C][C]-0.6466[/C][C]0.259314[/C][/ROW]
[ROW][C]7[/C][C]-0.03574[/C][C]-0.5042[/C][C]0.30735[/C][/ROW]
[ROW][C]8[/C][C]-0.055855[/C][C]-0.7879[/C][C]0.215837[/C][/ROW]
[ROW][C]9[/C][C]0.045449[/C][C]0.6411[/C][C]0.261086[/C][/ROW]
[ROW][C]10[/C][C]-0.012111[/C][C]-0.1708[/C][C]0.432262[/C][/ROW]
[ROW][C]11[/C][C]0.192715[/C][C]2.7186[/C][C]0.003568[/C][/ROW]
[ROW][C]12[/C][C]-0.310616[/C][C]-4.3818[/C][C]1e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.130331[/C][C]-1.8385[/C][C]0.033737[/C][/ROW]
[ROW][C]14[/C][C]-0.0549[/C][C]-0.7745[/C][C]0.219787[/C][/ROW]
[ROW][C]15[/C][C]0.003765[/C][C]0.0531[/C][C]0.478848[/C][/ROW]
[ROW][C]16[/C][C]-0.161002[/C][C]-2.2712[/C][C]0.012102[/C][/ROW]
[ROW][C]17[/C][C]-0.051743[/C][C]-0.7299[/C][C]0.233146[/C][/ROW]
[ROW][C]18[/C][C]-0.009455[/C][C]-0.1334[/C][C]0.447013[/C][/ROW]
[ROW][C]19[/C][C]-0.09647[/C][C]-1.3609[/C][C]0.087545[/C][/ROW]
[ROW][C]20[/C][C]-0.111273[/C][C]-1.5697[/C][C]0.059037[/C][/ROW]
[ROW][C]21[/C][C]-0.03557[/C][C]-0.5018[/C][C]0.308191[/C][/ROW]
[ROW][C]22[/C][C]0.045836[/C][C]0.6466[/C][C]0.259319[/C][/ROW]
[ROW][C]23[/C][C]0.184043[/C][C]2.5962[/C][C]0.005064[/C][/ROW]
[ROW][C]24[/C][C]-0.242334[/C][C]-3.4185[/C][C]0.000382[/C][/ROW]
[ROW][C]25[/C][C]-0.142234[/C][C]-2.0065[/C][C]0.023081[/C][/ROW]
[ROW][C]26[/C][C]-0.111847[/C][C]-1.5778[/C][C]0.058101[/C][/ROW]
[ROW][C]27[/C][C]-0.029442[/C][C]-0.4153[/C][C]0.339174[/C][/ROW]
[ROW][C]28[/C][C]-0.012645[/C][C]-0.1784[/C][C]0.429301[/C][/ROW]
[ROW][C]29[/C][C]0.055982[/C][C]0.7897[/C][C]0.215314[/C][/ROW]
[ROW][C]30[/C][C]0.065214[/C][C]0.92[/C][C]0.179354[/C][/ROW]
[ROW][C]31[/C][C]-0.059626[/C][C]-0.8411[/C][C]0.200643[/C][/ROW]
[ROW][C]32[/C][C]-0.031849[/C][C]-0.4493[/C][C]0.326858[/C][/ROW]
[ROW][C]33[/C][C]-0.058316[/C][C]-0.8227[/C][C]0.205844[/C][/ROW]
[ROW][C]34[/C][C]-0.011338[/C][C]-0.1599[/C][C]0.436545[/C][/ROW]
[ROW][C]35[/C][C]0.152072[/C][C]2.1452[/C][C]0.016573[/C][/ROW]
[ROW][C]36[/C][C]-0.066945[/C][C]-0.9444[/C][C]0.173062[/C][/ROW]
[ROW][C]37[/C][C]0.009658[/C][C]0.1362[/C][C]0.445885[/C][/ROW]
[ROW][C]38[/C][C]0.047615[/C][C]0.6717[/C][C]0.251281[/C][/ROW]
[ROW][C]39[/C][C]-0.230429[/C][C]-3.2506[/C][C]0.000676[/C][/ROW]
[ROW][C]40[/C][C]-0.103812[/C][C]-1.4644[/C][C]0.072325[/C][/ROW]
[ROW][C]41[/C][C]-0.037751[/C][C]-0.5325[/C][C]0.29747[/C][/ROW]
[ROW][C]42[/C][C]-0.155472[/C][C]-2.1932[/C][C]0.014726[/C][/ROW]
[ROW][C]43[/C][C]-0.001161[/C][C]-0.0164[/C][C]0.493474[/C][/ROW]
[ROW][C]44[/C][C]0.024649[/C][C]0.3477[/C][C]0.364209[/C][/ROW]
[ROW][C]45[/C][C]0.098661[/C][C]1.3918[/C][C]0.082771[/C][/ROW]
[ROW][C]46[/C][C]0.02745[/C][C]0.3872[/C][C]0.349499[/C][/ROW]
[ROW][C]47[/C][C]0.14693[/C][C]2.0727[/C][C]0.019744[/C][/ROW]
[ROW][C]48[/C][C]-0.083517[/C][C]-1.1782[/C][C]0.120071[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315462&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315462&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
1-0.31638-4.46317e-06
2-0.164665-2.32290.010598
3-0.160068-2.2580.012514
4-0.123763-1.74590.041187
50.06090.85910.19566
6-0.045837-0.64660.259314
7-0.03574-0.50420.30735
8-0.055855-0.78790.215837
90.0454490.64110.261086
10-0.012111-0.17080.432262
110.1927152.71860.003568
12-0.310616-4.38181e-05
13-0.130331-1.83850.033737
14-0.0549-0.77450.219787
150.0037650.05310.478848
16-0.161002-2.27120.012102
17-0.051743-0.72990.233146
18-0.009455-0.13340.447013
19-0.09647-1.36090.087545
20-0.111273-1.56970.059037
21-0.03557-0.50180.308191
220.0458360.64660.259319
230.1840432.59620.005064
24-0.242334-3.41850.000382
25-0.142234-2.00650.023081
26-0.111847-1.57780.058101
27-0.029442-0.41530.339174
28-0.012645-0.17840.429301
290.0559820.78970.215314
300.0652140.920.179354
31-0.059626-0.84110.200643
32-0.031849-0.44930.326858
33-0.058316-0.82270.205844
34-0.011338-0.15990.436545
350.1520722.14520.016573
36-0.066945-0.94440.173062
370.0096580.13620.445885
380.0476150.67170.251281
39-0.230429-3.25060.000676
40-0.103812-1.46440.072325
41-0.037751-0.53250.29747
42-0.155472-2.19320.014726
43-0.001161-0.01640.493474
440.0246490.34770.364209
450.0986611.39180.082771
460.027450.38720.349499
470.146932.07270.019744
48-0.083517-1.17820.120071



Parameters (Session):
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.99 ; par8 = ;
R code (references can be found in the software module):
par8 <- ''
par7 <- '0.99'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '1'
par2 <- '1'
par1 <- '48'
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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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')