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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 31 Dec 2014 08:19:08 +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/2014/Dec/31/t1420015229tel5hgsvgie8l9q.htm/, Retrieved Thu, 31 Oct 2024 23:54:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271778, Retrieved Thu, 31 Oct 2024 23:54:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2014-12-31 08:19:08] [062c419fa600f620f2df94d64c8876ba] [Current]
-    D    [(Partial) Autocorrelation Function] [] [2014-12-31 09:17:49] [4df2cd86c9043e1a56e9383f8c504201]
- R PD    [(Partial) Autocorrelation Function] [] [2014-12-31 09:22:47] [4df2cd86c9043e1a56e9383f8c504201]
- RMPD    [Bootstrap Plot - Central Tendency] [] [2014-12-31 10:06:48] [4df2cd86c9043e1a56e9383f8c504201]
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Dataseries X:
1,38
1,96
1,36
1,24
1,35
1,23
1,09
1,08
1,33
1,35
1,38
1,5
1,47
2,09
1,52
1,29
1,52
1,27
1,35
1,29
1,41
1,39
1,45
1,53
1,45
2,11
1,53
1,38
1,54
1,35
1,29
1,33
1,47
1,47
1,54
1,59
1,5
2
1,51
1,4
1,62
1,44
1,29
1,28
1,4
1,39
1,46
1,49
1,45
2,05
1,59
1,42
1,73
1,39
1,23
1,37
1,51
1,47
1,5
1,54
1,54
2,15
1,62
1,4
1,65
1,49
1,45
1,45
1,51
1,48
1,56
1,57




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271778&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271778&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271778&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'Gertrude Mary Cox' @ cox.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2194231.86190.033351
20.0738810.62690.266354
30.2036641.72810.044125
4-0.116841-0.99140.162398
5-0.225143-1.91040.030032
6-0.342338-2.90480.002439
7-0.247975-2.10410.01943
8-0.17469-1.48230.071313
90.117740.99910.160557
100.0137070.11630.453867
110.0976950.8290.204932
120.7258946.15940
130.1146460.97280.166953
140.021050.17860.42937
150.160821.36460.088314
16-0.126316-1.07180.143689
17-0.201179-1.70710.04606
18-0.288484-2.44790.008405
19-0.208732-1.77120.040384
20-0.16009-1.35840.089287
210.0477680.40530.343222
22-0.02121-0.180.428839
230.0453510.38480.350753
240.5538744.69986e-06
250.0870680.73880.231216
260.0241410.20480.419136
270.1413051.1990.117227
28-0.089331-0.7580.225462
29-0.173321-1.47070.072868
30-0.223659-1.89780.030865
31-0.164105-1.39250.084032
32-0.14487-1.22930.111488
330.0045330.03850.484712
34-0.034885-0.2960.384038
350.0251330.21330.415865
360.423423.59280.000297
370.0759070.64410.260782
380.0263990.2240.411696
390.1315521.11630.134013
40-0.05016-0.42560.335825
41-0.122803-1.0420.150444
42-0.167915-1.42480.079267
43-0.120859-1.02550.154274
44-0.117203-0.99450.161654
45-0.02453-0.20810.417852
46-0.053849-0.45690.324551
47-0.004022-0.03410.486435
480.2661332.25820.013482

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.219423 & 1.8619 & 0.033351 \tabularnewline
2 & 0.073881 & 0.6269 & 0.266354 \tabularnewline
3 & 0.203664 & 1.7281 & 0.044125 \tabularnewline
4 & -0.116841 & -0.9914 & 0.162398 \tabularnewline
5 & -0.225143 & -1.9104 & 0.030032 \tabularnewline
6 & -0.342338 & -2.9048 & 0.002439 \tabularnewline
7 & -0.247975 & -2.1041 & 0.01943 \tabularnewline
8 & -0.17469 & -1.4823 & 0.071313 \tabularnewline
9 & 0.11774 & 0.9991 & 0.160557 \tabularnewline
10 & 0.013707 & 0.1163 & 0.453867 \tabularnewline
11 & 0.097695 & 0.829 & 0.204932 \tabularnewline
12 & 0.725894 & 6.1594 & 0 \tabularnewline
13 & 0.114646 & 0.9728 & 0.166953 \tabularnewline
14 & 0.02105 & 0.1786 & 0.42937 \tabularnewline
15 & 0.16082 & 1.3646 & 0.088314 \tabularnewline
16 & -0.126316 & -1.0718 & 0.143689 \tabularnewline
17 & -0.201179 & -1.7071 & 0.04606 \tabularnewline
18 & -0.288484 & -2.4479 & 0.008405 \tabularnewline
19 & -0.208732 & -1.7712 & 0.040384 \tabularnewline
20 & -0.16009 & -1.3584 & 0.089287 \tabularnewline
21 & 0.047768 & 0.4053 & 0.343222 \tabularnewline
22 & -0.02121 & -0.18 & 0.428839 \tabularnewline
23 & 0.045351 & 0.3848 & 0.350753 \tabularnewline
24 & 0.553874 & 4.6998 & 6e-06 \tabularnewline
25 & 0.087068 & 0.7388 & 0.231216 \tabularnewline
26 & 0.024141 & 0.2048 & 0.419136 \tabularnewline
27 & 0.141305 & 1.199 & 0.117227 \tabularnewline
28 & -0.089331 & -0.758 & 0.225462 \tabularnewline
29 & -0.173321 & -1.4707 & 0.072868 \tabularnewline
30 & -0.223659 & -1.8978 & 0.030865 \tabularnewline
31 & -0.164105 & -1.3925 & 0.084032 \tabularnewline
32 & -0.14487 & -1.2293 & 0.111488 \tabularnewline
33 & 0.004533 & 0.0385 & 0.484712 \tabularnewline
34 & -0.034885 & -0.296 & 0.384038 \tabularnewline
35 & 0.025133 & 0.2133 & 0.415865 \tabularnewline
36 & 0.42342 & 3.5928 & 0.000297 \tabularnewline
37 & 0.075907 & 0.6441 & 0.260782 \tabularnewline
38 & 0.026399 & 0.224 & 0.411696 \tabularnewline
39 & 0.131552 & 1.1163 & 0.134013 \tabularnewline
40 & -0.05016 & -0.4256 & 0.335825 \tabularnewline
41 & -0.122803 & -1.042 & 0.150444 \tabularnewline
42 & -0.167915 & -1.4248 & 0.079267 \tabularnewline
43 & -0.120859 & -1.0255 & 0.154274 \tabularnewline
44 & -0.117203 & -0.9945 & 0.161654 \tabularnewline
45 & -0.02453 & -0.2081 & 0.417852 \tabularnewline
46 & -0.053849 & -0.4569 & 0.324551 \tabularnewline
47 & -0.004022 & -0.0341 & 0.486435 \tabularnewline
48 & 0.266133 & 2.2582 & 0.013482 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271778&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]0.219423[/C][C]1.8619[/C][C]0.033351[/C][/ROW]
[ROW][C]2[/C][C]0.073881[/C][C]0.6269[/C][C]0.266354[/C][/ROW]
[ROW][C]3[/C][C]0.203664[/C][C]1.7281[/C][C]0.044125[/C][/ROW]
[ROW][C]4[/C][C]-0.116841[/C][C]-0.9914[/C][C]0.162398[/C][/ROW]
[ROW][C]5[/C][C]-0.225143[/C][C]-1.9104[/C][C]0.030032[/C][/ROW]
[ROW][C]6[/C][C]-0.342338[/C][C]-2.9048[/C][C]0.002439[/C][/ROW]
[ROW][C]7[/C][C]-0.247975[/C][C]-2.1041[/C][C]0.01943[/C][/ROW]
[ROW][C]8[/C][C]-0.17469[/C][C]-1.4823[/C][C]0.071313[/C][/ROW]
[ROW][C]9[/C][C]0.11774[/C][C]0.9991[/C][C]0.160557[/C][/ROW]
[ROW][C]10[/C][C]0.013707[/C][C]0.1163[/C][C]0.453867[/C][/ROW]
[ROW][C]11[/C][C]0.097695[/C][C]0.829[/C][C]0.204932[/C][/ROW]
[ROW][C]12[/C][C]0.725894[/C][C]6.1594[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.114646[/C][C]0.9728[/C][C]0.166953[/C][/ROW]
[ROW][C]14[/C][C]0.02105[/C][C]0.1786[/C][C]0.42937[/C][/ROW]
[ROW][C]15[/C][C]0.16082[/C][C]1.3646[/C][C]0.088314[/C][/ROW]
[ROW][C]16[/C][C]-0.126316[/C][C]-1.0718[/C][C]0.143689[/C][/ROW]
[ROW][C]17[/C][C]-0.201179[/C][C]-1.7071[/C][C]0.04606[/C][/ROW]
[ROW][C]18[/C][C]-0.288484[/C][C]-2.4479[/C][C]0.008405[/C][/ROW]
[ROW][C]19[/C][C]-0.208732[/C][C]-1.7712[/C][C]0.040384[/C][/ROW]
[ROW][C]20[/C][C]-0.16009[/C][C]-1.3584[/C][C]0.089287[/C][/ROW]
[ROW][C]21[/C][C]0.047768[/C][C]0.4053[/C][C]0.343222[/C][/ROW]
[ROW][C]22[/C][C]-0.02121[/C][C]-0.18[/C][C]0.428839[/C][/ROW]
[ROW][C]23[/C][C]0.045351[/C][C]0.3848[/C][C]0.350753[/C][/ROW]
[ROW][C]24[/C][C]0.553874[/C][C]4.6998[/C][C]6e-06[/C][/ROW]
[ROW][C]25[/C][C]0.087068[/C][C]0.7388[/C][C]0.231216[/C][/ROW]
[ROW][C]26[/C][C]0.024141[/C][C]0.2048[/C][C]0.419136[/C][/ROW]
[ROW][C]27[/C][C]0.141305[/C][C]1.199[/C][C]0.117227[/C][/ROW]
[ROW][C]28[/C][C]-0.089331[/C][C]-0.758[/C][C]0.225462[/C][/ROW]
[ROW][C]29[/C][C]-0.173321[/C][C]-1.4707[/C][C]0.072868[/C][/ROW]
[ROW][C]30[/C][C]-0.223659[/C][C]-1.8978[/C][C]0.030865[/C][/ROW]
[ROW][C]31[/C][C]-0.164105[/C][C]-1.3925[/C][C]0.084032[/C][/ROW]
[ROW][C]32[/C][C]-0.14487[/C][C]-1.2293[/C][C]0.111488[/C][/ROW]
[ROW][C]33[/C][C]0.004533[/C][C]0.0385[/C][C]0.484712[/C][/ROW]
[ROW][C]34[/C][C]-0.034885[/C][C]-0.296[/C][C]0.384038[/C][/ROW]
[ROW][C]35[/C][C]0.025133[/C][C]0.2133[/C][C]0.415865[/C][/ROW]
[ROW][C]36[/C][C]0.42342[/C][C]3.5928[/C][C]0.000297[/C][/ROW]
[ROW][C]37[/C][C]0.075907[/C][C]0.6441[/C][C]0.260782[/C][/ROW]
[ROW][C]38[/C][C]0.026399[/C][C]0.224[/C][C]0.411696[/C][/ROW]
[ROW][C]39[/C][C]0.131552[/C][C]1.1163[/C][C]0.134013[/C][/ROW]
[ROW][C]40[/C][C]-0.05016[/C][C]-0.4256[/C][C]0.335825[/C][/ROW]
[ROW][C]41[/C][C]-0.122803[/C][C]-1.042[/C][C]0.150444[/C][/ROW]
[ROW][C]42[/C][C]-0.167915[/C][C]-1.4248[/C][C]0.079267[/C][/ROW]
[ROW][C]43[/C][C]-0.120859[/C][C]-1.0255[/C][C]0.154274[/C][/ROW]
[ROW][C]44[/C][C]-0.117203[/C][C]-0.9945[/C][C]0.161654[/C][/ROW]
[ROW][C]45[/C][C]-0.02453[/C][C]-0.2081[/C][C]0.417852[/C][/ROW]
[ROW][C]46[/C][C]-0.053849[/C][C]-0.4569[/C][C]0.324551[/C][/ROW]
[ROW][C]47[/C][C]-0.004022[/C][C]-0.0341[/C][C]0.486435[/C][/ROW]
[ROW][C]48[/C][C]0.266133[/C][C]2.2582[/C][C]0.013482[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271778&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271778&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
10.2194231.86190.033351
20.0738810.62690.266354
30.2036641.72810.044125
4-0.116841-0.99140.162398
5-0.225143-1.91040.030032
6-0.342338-2.90480.002439
7-0.247975-2.10410.01943
8-0.17469-1.48230.071313
90.117740.99910.160557
100.0137070.11630.453867
110.0976950.8290.204932
120.7258946.15940
130.1146460.97280.166953
140.021050.17860.42937
150.160821.36460.088314
16-0.126316-1.07180.143689
17-0.201179-1.70710.04606
18-0.288484-2.44790.008405
19-0.208732-1.77120.040384
20-0.16009-1.35840.089287
210.0477680.40530.343222
22-0.02121-0.180.428839
230.0453510.38480.350753
240.5538744.69986e-06
250.0870680.73880.231216
260.0241410.20480.419136
270.1413051.1990.117227
28-0.089331-0.7580.225462
29-0.173321-1.47070.072868
30-0.223659-1.89780.030865
31-0.164105-1.39250.084032
32-0.14487-1.22930.111488
330.0045330.03850.484712
34-0.034885-0.2960.384038
350.0251330.21330.415865
360.423423.59280.000297
370.0759070.64410.260782
380.0263990.2240.411696
390.1315521.11630.134013
40-0.05016-0.42560.335825
41-0.122803-1.0420.150444
42-0.167915-1.42480.079267
43-0.120859-1.02550.154274
44-0.117203-0.99450.161654
45-0.02453-0.20810.417852
46-0.053849-0.45690.324551
47-0.004022-0.03410.486435
480.2661332.25820.013482







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2194231.86190.033351
20.0270360.22940.409601
30.1913021.62330.054453
4-0.218502-1.85410.033914
5-0.185704-1.57580.059734
6-0.33961-2.88170.002605
7-0.069968-0.59370.277286
8-0.057703-0.48960.312944
90.3580363.0380.001658
10-0.107467-0.91190.182436
110.0491440.4170.338959
120.5997235.08881e-06
13-0.328382-2.78640.003404
14-0.035128-0.29810.383255
15-0.094838-0.80470.211812
16-0.010894-0.09240.463302
170.0267770.22720.410452
180.0373870.31720.375992
190.0073990.06280.475057
200.0066840.05670.477463
21-0.138711-1.1770.121535
22-0.0056-0.04750.481116
230.0234040.19860.421572
240.0466940.39620.346562
250.0630990.53540.297008
26-0.001537-0.0130.494816
27-0.084118-0.71380.238839
280.0232550.19730.422064
29-0.103557-0.87870.191242
300.0929590.78880.216414
31-0.002563-0.02180.491354
320.0062340.05290.478981
33-0.039708-0.33690.368572
34-0.019516-0.16560.434468
35-0.013871-0.11770.453316
360.0219930.18660.426241
370.0099850.08470.466356
380.0044050.03740.485145
39-0.003479-0.02950.488267
40-0.017298-0.14680.441857
410.0483850.41060.341308
42-0.034481-0.29260.385342
430.0163550.13880.445008
440.0002020.00170.499319
45-0.04207-0.3570.361078
46-0.023602-0.20030.420918
47-0.015133-0.12840.449091
48-0.127673-1.08330.141135

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.219423 & 1.8619 & 0.033351 \tabularnewline
2 & 0.027036 & 0.2294 & 0.409601 \tabularnewline
3 & 0.191302 & 1.6233 & 0.054453 \tabularnewline
4 & -0.218502 & -1.8541 & 0.033914 \tabularnewline
5 & -0.185704 & -1.5758 & 0.059734 \tabularnewline
6 & -0.33961 & -2.8817 & 0.002605 \tabularnewline
7 & -0.069968 & -0.5937 & 0.277286 \tabularnewline
8 & -0.057703 & -0.4896 & 0.312944 \tabularnewline
9 & 0.358036 & 3.038 & 0.001658 \tabularnewline
10 & -0.107467 & -0.9119 & 0.182436 \tabularnewline
11 & 0.049144 & 0.417 & 0.338959 \tabularnewline
12 & 0.599723 & 5.0888 & 1e-06 \tabularnewline
13 & -0.328382 & -2.7864 & 0.003404 \tabularnewline
14 & -0.035128 & -0.2981 & 0.383255 \tabularnewline
15 & -0.094838 & -0.8047 & 0.211812 \tabularnewline
16 & -0.010894 & -0.0924 & 0.463302 \tabularnewline
17 & 0.026777 & 0.2272 & 0.410452 \tabularnewline
18 & 0.037387 & 0.3172 & 0.375992 \tabularnewline
19 & 0.007399 & 0.0628 & 0.475057 \tabularnewline
20 & 0.006684 & 0.0567 & 0.477463 \tabularnewline
21 & -0.138711 & -1.177 & 0.121535 \tabularnewline
22 & -0.0056 & -0.0475 & 0.481116 \tabularnewline
23 & 0.023404 & 0.1986 & 0.421572 \tabularnewline
24 & 0.046694 & 0.3962 & 0.346562 \tabularnewline
25 & 0.063099 & 0.5354 & 0.297008 \tabularnewline
26 & -0.001537 & -0.013 & 0.494816 \tabularnewline
27 & -0.084118 & -0.7138 & 0.238839 \tabularnewline
28 & 0.023255 & 0.1973 & 0.422064 \tabularnewline
29 & -0.103557 & -0.8787 & 0.191242 \tabularnewline
30 & 0.092959 & 0.7888 & 0.216414 \tabularnewline
31 & -0.002563 & -0.0218 & 0.491354 \tabularnewline
32 & 0.006234 & 0.0529 & 0.478981 \tabularnewline
33 & -0.039708 & -0.3369 & 0.368572 \tabularnewline
34 & -0.019516 & -0.1656 & 0.434468 \tabularnewline
35 & -0.013871 & -0.1177 & 0.453316 \tabularnewline
36 & 0.021993 & 0.1866 & 0.426241 \tabularnewline
37 & 0.009985 & 0.0847 & 0.466356 \tabularnewline
38 & 0.004405 & 0.0374 & 0.485145 \tabularnewline
39 & -0.003479 & -0.0295 & 0.488267 \tabularnewline
40 & -0.017298 & -0.1468 & 0.441857 \tabularnewline
41 & 0.048385 & 0.4106 & 0.341308 \tabularnewline
42 & -0.034481 & -0.2926 & 0.385342 \tabularnewline
43 & 0.016355 & 0.1388 & 0.445008 \tabularnewline
44 & 0.000202 & 0.0017 & 0.499319 \tabularnewline
45 & -0.04207 & -0.357 & 0.361078 \tabularnewline
46 & -0.023602 & -0.2003 & 0.420918 \tabularnewline
47 & -0.015133 & -0.1284 & 0.449091 \tabularnewline
48 & -0.127673 & -1.0833 & 0.141135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271778&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]0.219423[/C][C]1.8619[/C][C]0.033351[/C][/ROW]
[ROW][C]2[/C][C]0.027036[/C][C]0.2294[/C][C]0.409601[/C][/ROW]
[ROW][C]3[/C][C]0.191302[/C][C]1.6233[/C][C]0.054453[/C][/ROW]
[ROW][C]4[/C][C]-0.218502[/C][C]-1.8541[/C][C]0.033914[/C][/ROW]
[ROW][C]5[/C][C]-0.185704[/C][C]-1.5758[/C][C]0.059734[/C][/ROW]
[ROW][C]6[/C][C]-0.33961[/C][C]-2.8817[/C][C]0.002605[/C][/ROW]
[ROW][C]7[/C][C]-0.069968[/C][C]-0.5937[/C][C]0.277286[/C][/ROW]
[ROW][C]8[/C][C]-0.057703[/C][C]-0.4896[/C][C]0.312944[/C][/ROW]
[ROW][C]9[/C][C]0.358036[/C][C]3.038[/C][C]0.001658[/C][/ROW]
[ROW][C]10[/C][C]-0.107467[/C][C]-0.9119[/C][C]0.182436[/C][/ROW]
[ROW][C]11[/C][C]0.049144[/C][C]0.417[/C][C]0.338959[/C][/ROW]
[ROW][C]12[/C][C]0.599723[/C][C]5.0888[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.328382[/C][C]-2.7864[/C][C]0.003404[/C][/ROW]
[ROW][C]14[/C][C]-0.035128[/C][C]-0.2981[/C][C]0.383255[/C][/ROW]
[ROW][C]15[/C][C]-0.094838[/C][C]-0.8047[/C][C]0.211812[/C][/ROW]
[ROW][C]16[/C][C]-0.010894[/C][C]-0.0924[/C][C]0.463302[/C][/ROW]
[ROW][C]17[/C][C]0.026777[/C][C]0.2272[/C][C]0.410452[/C][/ROW]
[ROW][C]18[/C][C]0.037387[/C][C]0.3172[/C][C]0.375992[/C][/ROW]
[ROW][C]19[/C][C]0.007399[/C][C]0.0628[/C][C]0.475057[/C][/ROW]
[ROW][C]20[/C][C]0.006684[/C][C]0.0567[/C][C]0.477463[/C][/ROW]
[ROW][C]21[/C][C]-0.138711[/C][C]-1.177[/C][C]0.121535[/C][/ROW]
[ROW][C]22[/C][C]-0.0056[/C][C]-0.0475[/C][C]0.481116[/C][/ROW]
[ROW][C]23[/C][C]0.023404[/C][C]0.1986[/C][C]0.421572[/C][/ROW]
[ROW][C]24[/C][C]0.046694[/C][C]0.3962[/C][C]0.346562[/C][/ROW]
[ROW][C]25[/C][C]0.063099[/C][C]0.5354[/C][C]0.297008[/C][/ROW]
[ROW][C]26[/C][C]-0.001537[/C][C]-0.013[/C][C]0.494816[/C][/ROW]
[ROW][C]27[/C][C]-0.084118[/C][C]-0.7138[/C][C]0.238839[/C][/ROW]
[ROW][C]28[/C][C]0.023255[/C][C]0.1973[/C][C]0.422064[/C][/ROW]
[ROW][C]29[/C][C]-0.103557[/C][C]-0.8787[/C][C]0.191242[/C][/ROW]
[ROW][C]30[/C][C]0.092959[/C][C]0.7888[/C][C]0.216414[/C][/ROW]
[ROW][C]31[/C][C]-0.002563[/C][C]-0.0218[/C][C]0.491354[/C][/ROW]
[ROW][C]32[/C][C]0.006234[/C][C]0.0529[/C][C]0.478981[/C][/ROW]
[ROW][C]33[/C][C]-0.039708[/C][C]-0.3369[/C][C]0.368572[/C][/ROW]
[ROW][C]34[/C][C]-0.019516[/C][C]-0.1656[/C][C]0.434468[/C][/ROW]
[ROW][C]35[/C][C]-0.013871[/C][C]-0.1177[/C][C]0.453316[/C][/ROW]
[ROW][C]36[/C][C]0.021993[/C][C]0.1866[/C][C]0.426241[/C][/ROW]
[ROW][C]37[/C][C]0.009985[/C][C]0.0847[/C][C]0.466356[/C][/ROW]
[ROW][C]38[/C][C]0.004405[/C][C]0.0374[/C][C]0.485145[/C][/ROW]
[ROW][C]39[/C][C]-0.003479[/C][C]-0.0295[/C][C]0.488267[/C][/ROW]
[ROW][C]40[/C][C]-0.017298[/C][C]-0.1468[/C][C]0.441857[/C][/ROW]
[ROW][C]41[/C][C]0.048385[/C][C]0.4106[/C][C]0.341308[/C][/ROW]
[ROW][C]42[/C][C]-0.034481[/C][C]-0.2926[/C][C]0.385342[/C][/ROW]
[ROW][C]43[/C][C]0.016355[/C][C]0.1388[/C][C]0.445008[/C][/ROW]
[ROW][C]44[/C][C]0.000202[/C][C]0.0017[/C][C]0.499319[/C][/ROW]
[ROW][C]45[/C][C]-0.04207[/C][C]-0.357[/C][C]0.361078[/C][/ROW]
[ROW][C]46[/C][C]-0.023602[/C][C]-0.2003[/C][C]0.420918[/C][/ROW]
[ROW][C]47[/C][C]-0.015133[/C][C]-0.1284[/C][C]0.449091[/C][/ROW]
[ROW][C]48[/C][C]-0.127673[/C][C]-1.0833[/C][C]0.141135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271778&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271778&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
10.2194231.86190.033351
20.0270360.22940.409601
30.1913021.62330.054453
4-0.218502-1.85410.033914
5-0.185704-1.57580.059734
6-0.33961-2.88170.002605
7-0.069968-0.59370.277286
8-0.057703-0.48960.312944
90.3580363.0380.001658
10-0.107467-0.91190.182436
110.0491440.4170.338959
120.5997235.08881e-06
13-0.328382-2.78640.003404
14-0.035128-0.29810.383255
15-0.094838-0.80470.211812
16-0.010894-0.09240.463302
170.0267770.22720.410452
180.0373870.31720.375992
190.0073990.06280.475057
200.0066840.05670.477463
21-0.138711-1.1770.121535
22-0.0056-0.04750.481116
230.0234040.19860.421572
240.0466940.39620.346562
250.0630990.53540.297008
26-0.001537-0.0130.494816
27-0.084118-0.71380.238839
280.0232550.19730.422064
29-0.103557-0.87870.191242
300.0929590.78880.216414
31-0.002563-0.02180.491354
320.0062340.05290.478981
33-0.039708-0.33690.368572
34-0.019516-0.16560.434468
35-0.013871-0.11770.453316
360.0219930.18660.426241
370.0099850.08470.466356
380.0044050.03740.485145
39-0.003479-0.02950.488267
40-0.017298-0.14680.441857
410.0483850.41060.341308
42-0.034481-0.29260.385342
430.0163550.13880.445008
440.0002020.00170.499319
45-0.04207-0.3570.361078
46-0.023602-0.20030.420918
47-0.015133-0.12840.449091
48-0.127673-1.08330.141135



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (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')